diff --git a/selfdrive/monitoring/helpers.py b/selfdrive/monitoring/helpers.py index 3f9307c9..18df6f74 100644 --- a/selfdrive/monitoring/helpers.py +++ b/selfdrive/monitoring/helpers.py @@ -1,4 +1,4 @@ -from math import atan2 +from math import atan2, radians import numpy as np from cereal import car, log @@ -43,6 +43,9 @@ class DRIVER_MONITOR_SETTINGS: self._POSE_YAW_THRESHOLD = 0.4020 self._POSE_YAW_THRESHOLD_SLACK = 0.5042 self._POSE_YAW_THRESHOLD_STRICT = self._POSE_YAW_THRESHOLD + self._POSE_YAW_MIN_STEER_DEG = 30 + self._POSE_YAW_STEER_FACTOR = 0.15 + self._POSE_YAW_STEER_MAX_OFFSET = 0.3927 self._PITCH_NATURAL_OFFSET = 0.011 # initial value before offset is learned self._PITCH_NATURAL_THRESHOLD = 0.449 self._YAW_NATURAL_OFFSET = 0.075 # initial value before offset is learned @@ -59,7 +62,6 @@ class DRIVER_MONITOR_SETTINGS: self._POSESTD_THRESHOLD = 0.3 self._HI_STD_FALLBACK_TIME = int(10 / self._DT_DMON) # fall back to wheel touch if model is uncertain for 10s self._DISTRACTED_FILTER_TS = 0.25 # 0.6Hz - self._ALWAYS_ON_ALERT_MIN_SPEED = 11 self._POSE_CALIB_MIN_SPEED = 13 # 30 mph self._POSE_OFFSET_MIN_COUNT = int(60 / self._DT_DMON) # valid data counts before calibration completes, 1min cumulative @@ -100,6 +102,7 @@ class DriverPose: self.low_std = True self.cfactor_pitch = 1. self.cfactor_yaw = 1. + self.steer_yaw_offset = 0. class DriverProb: def __init__(self, raw_priors, max_trackable): @@ -237,7 +240,11 @@ class DriverMonitoring: yaw_error = self.pose.yaw - min(max(self.pose.yaw_offseter.filtered_stat.mean(), self.settings._YAW_MIN_OFFSET), self.settings._YAW_MAX_OFFSET) pitch_error = 0 if pitch_error > 0 else abs(pitch_error) # no positive pitch limit - yaw_error = abs(yaw_error) + + if yaw_error * self.pose.steer_yaw_offset > 0: # unidirectional + yaw_error = max(abs(yaw_error) - min(abs(self.pose.steer_yaw_offset), self.settings._POSE_YAW_STEER_MAX_OFFSET), 0.) + else: + yaw_error = abs(yaw_error) pitch_threshold = self.settings._POSE_PITCH_THRESHOLD * self.pose.cfactor_pitch if self.pose.calibrated else self.settings._PITCH_NATURAL_THRESHOLD yaw_threshold = self.settings._POSE_YAW_THRESHOLD * self.pose.cfactor_yaw @@ -253,7 +260,7 @@ class DriverMonitoring: return distracted_types - def _update_states(self, driver_state, cal_rpy, car_speed, op_engaged, standstill, demo_mode=False): + def _update_states(self, driver_state, cal_rpy, car_speed, op_engaged, standstill, demo_mode=False, steering_angle_deg=0.): rhd_pred = driver_state.wheelOnRightProb # calibrates only when there's movement and either face detected if car_speed > self.settings._WHEELPOS_CALIB_MIN_SPEED and (driver_state.leftDriverData.faceProb > self.settings._FACE_THRESHOLD or @@ -275,8 +282,11 @@ class DriverMonitoring: self.face_detected = driver_data.faceProb > self.settings._FACE_THRESHOLD self.pose.roll, self.pose.pitch, self.pose.yaw = face_orientation_from_net(driver_data.faceOrientation, driver_data.facePosition, cal_rpy) + steer_d = max(abs(steering_angle_deg) - self.settings._POSE_YAW_MIN_STEER_DEG, 0.) + self.pose.steer_yaw_offset = radians(steer_d) * -np.sign(steering_angle_deg) * self.settings._POSE_YAW_STEER_FACTOR if self.wheel_on_right: self.pose.yaw *= -1 + self.pose.steer_yaw_offset *= -1 self.wheel_on_right_last = self.wheel_on_right self.pose.pitch_std = driver_data.faceOrientationStd[0] self.pose.yaw_std = driver_data.faceOrientationStd[1] @@ -358,19 +368,19 @@ class DriverMonitoring: if self.awareness > self.threshold_prompt: return + _reaching_pre = self.awareness - self.step_change <= self.threshold_pre _reaching_audible = self.awareness - self.step_change <= self.threshold_prompt _reaching_terminal = self.awareness - self.step_change <= 0 - standstill_orange_exemption = standstill and _reaching_audible + standstill_exemption = standstill and _reaching_pre always_on_red_exemption = always_on_valid and not op_engaged and _reaching_terminal - always_on_lowspeed_exemption = always_on_valid and not op_engaged and car_speed < self.settings._ALWAYS_ON_ALERT_MIN_SPEED certainly_distracted = self.driver_distraction_filter.x > 0.63 and self.driver_distracted and self.face_detected maybe_distracted = self.hi_stds > self.settings._HI_STD_FALLBACK_TIME or not self.face_detected if certainly_distracted or maybe_distracted: - # should always be counting if distracted unless at standstill (lowspeed for always-on) and reaching orange + # should always be counting if distracted unless at standstill and reaching green # also will not be reaching 0 if DM is active when not engaged - if not (standstill_orange_exemption or always_on_red_exemption or (always_on_lowspeed_exemption and _reaching_audible)): + if not (standstill_exemption or always_on_red_exemption): self.awareness = max(self.awareness - self.step_change, -0.1) alert = None @@ -383,7 +393,7 @@ class DriverMonitoring: elif self.awareness <= self.threshold_prompt: # prompt orange alert alert = EventName.promptDriverDistracted if self.active_monitoring_mode else EventName.promptDriverUnresponsive - elif self.awareness <= self.threshold_pre and not always_on_lowspeed_exemption: + elif self.awareness <= self.threshold_pre: # pre green alert alert = EventName.preDriverDistracted if self.active_monitoring_mode else EventName.preDriverUnresponsive @@ -451,6 +461,7 @@ class DriverMonitoring: op_engaged=enabled, standstill=standstill, demo_mode=demo, + steering_angle_deg=sm['carState'].steeringAngleDeg, ) # Update distraction events diff --git a/selfdrive/monitoring/test_monitoring.py b/selfdrive/monitoring/test_monitoring.py index 6ea9b802..4a334787 100644 --- a/selfdrive/monitoring/test_monitoring.py +++ b/selfdrive/monitoring/test_monitoring.py @@ -186,10 +186,10 @@ class TestMonitoring: standstill_vector = always_true[:] standstill_vector[int(_redlight_time/DT_DMON):] = [False] * int((TEST_TIMESPAN-_redlight_time)/DT_DMON) events, d_status = self._run_seq(always_distracted, always_false, always_true, standstill_vector) - assert events[int((d_status.settings._DISTRACTED_TIME-d_status.settings._DISTRACTED_PRE_TIME_TILL_TERMINAL+1)/DT_DMON)].names[0] == \ - EventName.preDriverDistracted - assert events[int((_redlight_time-0.1)/DT_DMON)].names[0] == EventName.preDriverDistracted - assert events[int((_redlight_time+0.5)/DT_DMON)].names[0] == EventName.promptDriverDistracted + assert len(events[int((_redlight_time-0.1)/DT_DMON)]) == 0 + _pre_to_prompt = d_status.settings._DISTRACTED_PRE_TIME_TILL_TERMINAL - d_status.settings._DISTRACTED_PROMPT_TIME_TILL_TERMINAL + assert events[int((_redlight_time+0.5)/DT_DMON)].names[0] == EventName.preDriverDistracted + assert events[int((_redlight_time+_pre_to_prompt+0.5)/DT_DMON)].names[0] == EventName.promptDriverDistracted # engaged, model is somehow uncertain and driver is distracted # - should fall back to wheel touch after uncertain alert @@ -203,4 +203,3 @@ class TestMonitoring: events[int((INVISIBLE_SECONDS_TO_ORANGE-1+DT_DMON*d_status.settings._HI_STD_FALLBACK_TIME+0.1)/DT_DMON)].names assert EventName.driverUnresponsive in \ events[int((INVISIBLE_SECONDS_TO_RED-1+DT_DMON*d_status.settings._HI_STD_FALLBACK_TIME+0.1)/DT_DMON)].names - diff --git a/uncompiledmodels/driving_off_policy.onnx b/uncompiledmodels/driving_off_policy.onnx index b221dcbe..57cb0baf 100644 Binary files a/uncompiledmodels/driving_off_policy.onnx and b/uncompiledmodels/driving_off_policy.onnx differ diff --git a/uncompiledmodels/driving_policy.onnx b/uncompiledmodels/driving_policy.onnx index a1eaf73f..974a2e81 100644 Binary files a/uncompiledmodels/driving_policy.onnx and b/uncompiledmodels/driving_policy.onnx differ diff --git a/uncompiledmodels/driving_vision.onnx b/uncompiledmodels/driving_vision.onnx index 484af70f..497a782c 100644 --- a/uncompiledmodels/driving_vision.onnx +++ b/uncompiledmodels/driving_vision.onnx @@ -8,7 +8,7 @@ pkg.torch.onnx.class_hierarchy:['__main__.FlattenedVisionModel', 'aten._to_copy.default']J¤ pkg.torch.onnx.fx_node‰%_to_copy : [num_users=1] = call_function[target=torch.ops.aten._to_copy.default](args = (%inputs_img,), kwargs = {dtype: torch.float16})J. pkg.torch.onnx.name_scopes['', '_to_copy']JÊ -pkg.torch.onnx.stack_trace«File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace«File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) ‘ big_img @@ -19,7 +19,7 @@ _to_copy_1node__to_copy_1"Cast* pkg.torch.onnx.class_hierarchy:['__main__.FlattenedVisionModel', 'aten._to_copy.default']Jª pkg.torch.onnx.fx_node%_to_copy_1 : [num_users=1] = call_function[target=torch.ops.aten._to_copy.default](args = (%inputs_big_img,), kwargs = {dtype: torch.float16})J0 pkg.torch.onnx.name_scopes['', '_to_copy_1']JÊ -pkg.torch.onnx.stack_trace«File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace«File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) æ _to_copy @@ -30,7 +30,7 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchy5['__main__.FlattenedVisionModel', 'aten.cat.default']J” pkg.torch.onnx.fx_nodez%cat : [num_users=1] = call_function[target=torch.ops.aten.cat.default](args = ([%_to_copy, %_to_copy_1], 1), kwargs = {})J) pkg.torch.onnx.name_scopes ['', 'cat']JÊ -pkg.torch.onnx.stack_trace«File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace«File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) Í cat @@ -39,9 +39,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyZ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'aten.sub.Tensor']J› pkg.torch.onnx.fx_node€%sub : [num_users=1] = call_function[target=torch.ops.aten.sub.Tensor](args = (%cat, %b_vision_model_vision__mean), kwargs = {})J@ pkg.torch.onnx.name_scopes"['', 'vision_model.vision', 'sub']J½ -pkg.torch.onnx.stack_tracežFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_tracežFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 186, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 184, in forward x = (x - self._mean) / self._std Ê sub @@ -50,9 +50,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyZ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'aten.div.Tensor']J™ pkg.torch.onnx.fx_node%div : [num_users=1] = call_function[target=torch.ops.aten.div.Tensor](args = (%sub, %b_vision_model_vision__std), kwargs = {})J@ pkg.torch.onnx.name_scopes"['', 'vision_model.vision', 'div']J½ -pkg.torch.onnx.stack_tracežFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_tracežFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 186, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 184, in forward x = (x - self._mean) / self._std ì div @@ -67,9 +67,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyì['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J€ pkg.torch.onnx.fx_nodeå%conv2d : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%div, %p_vision_model_vision__en_stem_0_reparam_conv_weight, %p_vision_model_vision__en_stem_0_reparam_conv_bias, [2, 2], [1, 1]), kwargs = {})JÐ pkg.torch.onnx.name_scopes±['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.0', 'vision_model.vision._en.stem.0.reparam_conv', 'conv2d']J“ -pkg.torch.onnx.stack_traceôFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceôFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -86,9 +86,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyî['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J” pkg.torch.onnx.fx_nodez%gelu : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d,), kwargs = {approximate: tanh})JÅ pkg.torch.onnx.name_scopes¦['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.0', 'vision_model.vision._en.stem.0.act', 'gelu']J… -pkg.torch.onnx.stack_traceæFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceæFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -111,9 +111,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyì['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_nodeô%conv2d_1 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu, %p_vision_model_vision__en_stem_1_reparam_conv_weight, %p_vision_model_vision__en_stem_1_reparam_conv_bias, [2, 2], [1, 1], [1, 1], 64), kwargs = {})JÒ pkg.torch.onnx.name_scopes³['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.1', 'vision_model.vision._en.stem.1.reparam_conv', 'conv2d_1']J“ -pkg.torch.onnx.stack_traceôFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceôFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -130,9 +130,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyî['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J˜ pkg.torch.onnx.fx_node~%gelu_1 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_1,), kwargs = {approximate: tanh})JÇ pkg.torch.onnx.name_scopes¨['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.1', 'vision_model.vision._en.stem.1.act', 'gelu_1']J… -pkg.torch.onnx.stack_traceæFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceæFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -155,9 +155,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyì['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jõ pkg.torch.onnx.fx_nodeÚ%conv2d_2 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_1, %p_vision_model_vision__en_stem_2_reparam_conv_weight, %p_vision_model_vision__en_stem_2_reparam_conv_bias), kwargs = {})JÒ pkg.torch.onnx.name_scopes³['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.2', 'vision_model.vision._en.stem.2.reparam_conv', 'conv2d_2']J“ -pkg.torch.onnx.stack_traceôFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceôFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -174,9 +174,9 @@ _to_copy_1catnode_cat"Concat* pkg.torch.onnx.class_hierarchyî['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J˜ pkg.torch.onnx.fx_node~%gelu_2 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_2,), kwargs = {approximate: tanh})JÇ pkg.torch.onnx.name_scopes¨['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stem', 'vision_model.vision._en.stem.2', 'vision_model.vision._en.stem.2.act', 'gelu_2']J… -pkg.torch.onnx.stack_traceæFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceæFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -199,9 +199,9 @@ Gvision_model.vision._en.stages.0.blocks.0.token_mixer.reparam_conv.biasconv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J¿ pkg.torch.onnx.fx_node¤%conv2d_3 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_2, %p_vision_model_vision__en_stages_0_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_0_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 64), kwargs = {})JÜ pkg.torch.onnx.name_scopes½['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.token_mixer', 'vision_model.vision._en.stages.0.blocks.0.token_mixer.reparam_conv', 'conv2d_3']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -229,9 +229,9 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']JÞ pkg.torch.onnx.fx_nodeÃ%_native_batch_norm_legit_no_training : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_4, %p_vision_model_vision__en_stages_0_blocks_0_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_0_blocks_0_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_0_blocks_0_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_0_blocks_0_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J™ pkg.torch.onnx.name_scopesú['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.conv', 'vision_model.vision._en.stages.0.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -260,9 +260,9 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J‚ pkg.torch.onnx.fx_nodeç%conv2d_5 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc1_bias), kwargs = {})Jà pkg.torch.onnx.name_scopes¤['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.fc1', 'conv2d_5']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -283,9 +283,9 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J˜ pkg.torch.onnx.fx_node~%gelu_3 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_5,), kwargs = {approximate: tanh})JÁ pkg.torch.onnx.name_scopes¢['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.act', 'gelu_3']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -312,9 +312,9 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J€ pkg.torch.onnx.fx_nodeå%conv2d_6 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_0_blocks_0_mlp_fc2_bias), kwargs = {})Jà pkg.torch.onnx.name_scopes¤['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.mlp', 'vision_model.vision._en.stages.0.blocks.0.mlp.fc2', 'conv2d_6']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -335,9 +335,9 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']JÁ pkg.torch.onnx.fx_node¦%mul : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_1, %p_vision_model_vision__en_stages_0_blocks_0_layer_scale_gamma), kwargs = {})J‘ pkg.torch.onnx.name_scopesò['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'vision_model.vision._en.stages.0.blocks.0.layer_scale', 'mul']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -356,9 +356,9 @@ Cvision_model.vision._en.stages.0.blocks.0.mlp.conv.conv.weight_biasgetitem n pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J‡ pkg.torch.onnx.fx_nodem%add : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_3, %mul), kwargs = {})JØ pkg.torch.onnx.name_scopes¹['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.0', 'add']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -381,9 +381,9 @@ Gvision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv.biasconv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J¼ pkg.torch.onnx.fx_node¡%conv2d_7 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add, %p_vision_model_vision__en_stages_0_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_0_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 64), kwargs = {})JÜ pkg.torch.onnx.name_scopes½['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.token_mixer', 'vision_model.vision._en.stages.0.blocks.1.token_mixer.reparam_conv', 'conv2d_7']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -411,9 +411,9 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Jà pkg.torch.onnx.fx_nodeÅ%_native_batch_norm_legit_no_training_1 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_8, %p_vision_model_vision__en_stages_0_blocks_1_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_0_blocks_1_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_0_blocks_1_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_0_blocks_1_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.conv', 'vision_model.vision._en.stages.0.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_1']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -442,9 +442,9 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J„ pkg.torch.onnx.fx_nodeé%conv2d_9 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_3, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc1_bias), kwargs = {})Jà pkg.torch.onnx.name_scopes¤['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.fc1', 'conv2d_9']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -465,9 +465,9 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J˜ pkg.torch.onnx.fx_node~%gelu_4 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_9,), kwargs = {approximate: tanh})JÁ pkg.torch.onnx.name_scopes¢['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.act', 'gelu_4']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -494,9 +494,9 @@ Cvision_model.vision._en.stages.0.blocks.1.mlp.conv.conv.weight_bias getitem_3 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jƒ pkg.torch.onnx.fx_nodeè%conv2d_10 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_2, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_0_blocks_1_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.mlp', 'vision_model.vision._en.stages.0.blocks.1.mlp.fc2', 'conv2d_10']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -518,9 +518,9 @@ node_mul_1"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']Jà pkg.torch.onnx.fx_node¨%mul_1 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_3, %p_vision_model_vision__en_stages_0_blocks_1_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'vision_model.vision._en.stages.0.blocks.1.layer_scale', 'mul_1']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -540,9 +540,9 @@ node_add_1"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']J‹ pkg.torch.onnx.fx_nodeq%add_1 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_7, %mul_1), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.0', 'vision_model.vision._en.stages.0.blocks', 'vision_model.vision._en.stages.0.blocks.1', 'add_1']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -565,9 +565,9 @@ Dvision_model.vision._en.stages.1.downsample.proj.0.reparam_conv.bias conv2d_11 pkg.torch.onnx.class_hierarchyº['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J¹ pkg.torch.onnx.fx_nodež%conv2d_11 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_1, %p_vision_model_vision__en_stages_1_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_1_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 64), kwargs = {})Jâ pkg.torch.onnx.name_scopesÃ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.0', 'vision_model.vision._en.stages.1.downsample.proj.0.reparam_conv', 'conv2d_11']J‚ -pkg.torch.onnx.stack_traceãFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceãFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -594,9 +594,9 @@ Dvision_model.vision._en.stages.1.downsample.proj.1.reparam_conv.bias conv2d_12 pkg.torch.onnx.class_hierarchy²['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J¡ pkg.torch.onnx.fx_node†%conv2d_12 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_11, %p_vision_model_vision__en_stages_1_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_1_downsample_proj_1_reparam_conv_bias), kwargs = {})Jâ pkg.torch.onnx.name_scopesÃ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.1', 'vision_model.vision._en.stages.1.downsample.proj.1.reparam_conv', 'conv2d_12']J– -pkg.torch.onnx.stack_trace÷File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace÷File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -617,9 +617,9 @@ Dvision_model.vision._en.stages.1.downsample.proj.1.reparam_conv.bias conv2d_12 pkg.torch.onnx.class_hierarchy´['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J™ pkg.torch.onnx.fx_node%gelu_5 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_12,), kwargs = {approximate: tanh})JÖ pkg.torch.onnx.name_scopes·['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.downsample', 'vision_model.vision._en.stages.1.downsample.proj', 'vision_model.vision._en.stages.1.downsample.proj.1', 'vision_model.vision._en.stages.1.downsample.proj.1.act', 'gelu_5']Jˆ -pkg.torch.onnx.stack_traceéFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceéFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -646,9 +646,9 @@ Gvision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÁ pkg.torch.onnx.fx_node¦%conv2d_13 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_5, %p_vision_model_vision__en_stages_1_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_1_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 128), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.token_mixer', 'vision_model.vision._en.stages.1.blocks.0.token_mixer.reparam_conv', 'conv2d_13']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -676,9 +676,9 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Já pkg.torch.onnx.fx_nodeÆ%_native_batch_norm_legit_no_training_2 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_14, %p_vision_model_vision__en_stages_1_blocks_0_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_1_blocks_0_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_1_blocks_0_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_1_blocks_0_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.conv', 'vision_model.vision._en.stages.1.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_2']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -707,9 +707,9 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J… pkg.torch.onnx.fx_nodeê%conv2d_15 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_6, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.fc1', 'conv2d_15']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -730,9 +730,9 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J™ pkg.torch.onnx.fx_node%gelu_6 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_15,), kwargs = {approximate: tanh})JÁ pkg.torch.onnx.name_scopes¢['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.act', 'gelu_6']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -759,9 +759,9 @@ Cvision_model.vision._en.stages.1.blocks.0.mlp.conv.conv.weight_bias getitem_6 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jƒ pkg.torch.onnx.fx_nodeè%conv2d_16 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_4, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_1_blocks_0_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.mlp', 'vision_model.vision._en.stages.1.blocks.0.mlp.fc2', 'conv2d_16']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -783,9 +783,9 @@ node_mul_2"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']Jà pkg.torch.onnx.fx_node¨%mul_2 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_5, %p_vision_model_vision__en_stages_1_blocks_0_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'vision_model.vision._en.stages.1.blocks.0.layer_scale', 'mul_2']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -805,9 +805,9 @@ node_add_2"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŒ pkg.torch.onnx.fx_noder%add_2 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_13, %mul_2), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.0', 'add_2']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -830,9 +830,9 @@ Gvision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÀ pkg.torch.onnx.fx_node¥%conv2d_17 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_2, %p_vision_model_vision__en_stages_1_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_1_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 128), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.token_mixer', 'vision_model.vision._en.stages.1.blocks.1.token_mixer.reparam_conv', 'conv2d_17']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -860,9 +860,9 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Já pkg.torch.onnx.fx_nodeÆ%_native_batch_norm_legit_no_training_3 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_18, %p_vision_model_vision__en_stages_1_blocks_1_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_1_blocks_1_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_1_blocks_1_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_1_blocks_1_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.conv', 'vision_model.vision._en.stages.1.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_3']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -891,9 +891,9 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J… pkg.torch.onnx.fx_nodeê%conv2d_19 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_9, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.fc1', 'conv2d_19']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -914,9 +914,9 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J™ pkg.torch.onnx.fx_node%gelu_7 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_19,), kwargs = {approximate: tanh})JÁ pkg.torch.onnx.name_scopes¢['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.act', 'gelu_7']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -943,9 +943,9 @@ Cvision_model.vision._en.stages.1.blocks.1.mlp.conv.conv.weight_bias getitem_9 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jƒ pkg.torch.onnx.fx_nodeè%conv2d_20 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_6, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_1_blocks_1_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.mlp', 'vision_model.vision._en.stages.1.blocks.1.mlp.fc2', 'conv2d_20']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -967,9 +967,9 @@ node_mul_3"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']Jà pkg.torch.onnx.fx_node¨%mul_3 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_7, %p_vision_model_vision__en_stages_1_blocks_1_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'vision_model.vision._en.stages.1.blocks.1.layer_scale', 'mul_3']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -989,9 +989,9 @@ node_add_3"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŒ pkg.torch.onnx.fx_noder%add_3 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_17, %mul_3), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.1', 'vision_model.vision._en.stages.1.blocks', 'vision_model.vision._en.stages.1.blocks.1', 'add_3']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1014,9 +1014,9 @@ Dvision_model.vision._en.stages.2.downsample.proj.0.reparam_conv.bias conv2d_21 pkg.torch.onnx.class_hierarchyº['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jº pkg.torch.onnx.fx_nodeŸ%conv2d_21 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_3, %p_vision_model_vision__en_stages_2_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_2_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 128), kwargs = {})Jâ pkg.torch.onnx.name_scopesÃ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.0', 'vision_model.vision._en.stages.2.downsample.proj.0.reparam_conv', 'conv2d_21']J‚ -pkg.torch.onnx.stack_traceãFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceãFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1043,9 +1043,9 @@ Dvision_model.vision._en.stages.2.downsample.proj.1.reparam_conv.bias conv2d_22 pkg.torch.onnx.class_hierarchy²['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J¡ pkg.torch.onnx.fx_node†%conv2d_22 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_21, %p_vision_model_vision__en_stages_2_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_2_downsample_proj_1_reparam_conv_bias), kwargs = {})Jâ pkg.torch.onnx.name_scopesÃ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.1', 'vision_model.vision._en.stages.2.downsample.proj.1.reparam_conv', 'conv2d_22']J– -pkg.torch.onnx.stack_trace÷File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace÷File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1066,9 +1066,9 @@ Dvision_model.vision._en.stages.2.downsample.proj.1.reparam_conv.bias conv2d_22 pkg.torch.onnx.class_hierarchy´['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J™ pkg.torch.onnx.fx_node%gelu_8 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_22,), kwargs = {approximate: tanh})JÖ pkg.torch.onnx.name_scopes·['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.downsample', 'vision_model.vision._en.stages.2.downsample.proj', 'vision_model.vision._en.stages.2.downsample.proj.1', 'vision_model.vision._en.stages.2.downsample.proj.1.act', 'gelu_8']Jˆ -pkg.torch.onnx.stack_traceéFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceéFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1095,9 +1095,9 @@ Gvision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÁ pkg.torch.onnx.fx_node¦%conv2d_23 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_8, %p_vision_model_vision__en_stages_2_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.token_mixer', 'vision_model.vision._en.stages.2.blocks.0.token_mixer.reparam_conv', 'conv2d_23']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1126,9 +1126,9 @@ getitem_12 node_Conv_190"Conv* pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Já pkg.torch.onnx.fx_nodeÆ%_native_batch_norm_legit_no_training_4 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_24, %p_vision_model_vision__en_stages_2_blocks_0_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_0_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_0_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_0_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.conv', 'vision_model.vision._en.stages.2.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_4']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1158,9 +1158,9 @@ getitem_12 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J† pkg.torch.onnx.fx_nodeë%conv2d_25 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_12, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.fc1', 'conv2d_25']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1181,9 +1181,9 @@ getitem_12 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J™ pkg.torch.onnx.fx_node%gelu_9 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_25,), kwargs = {approximate: tanh})JÁ pkg.torch.onnx.name_scopes¢['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.act', 'gelu_9']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1210,9 +1210,9 @@ getitem_12 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jƒ pkg.torch.onnx.fx_nodeè%conv2d_26 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_8, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_0_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.mlp', 'vision_model.vision._en.stages.2.blocks.0.mlp.fc2', 'conv2d_26']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1234,9 +1234,9 @@ node_mul_4"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']Jà pkg.torch.onnx.fx_node¨%mul_4 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_9, %p_vision_model_vision__en_stages_2_blocks_0_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'vision_model.vision._en.stages.2.blocks.0.layer_scale', 'mul_4']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1256,9 +1256,9 @@ node_add_4"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŒ pkg.torch.onnx.fx_noder%add_4 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_23, %mul_4), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.0', 'add_4']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1281,9 +1281,9 @@ Gvision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÀ pkg.torch.onnx.fx_node¥%conv2d_27 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_4, %p_vision_model_vision__en_stages_2_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.token_mixer', 'vision_model.vision._en.stages.2.blocks.1.token_mixer.reparam_conv', 'conv2d_27']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1312,9 +1312,9 @@ getitem_15 node_Conv_192"Conv* pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Já pkg.torch.onnx.fx_nodeÆ%_native_batch_norm_legit_no_training_5 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_28, %p_vision_model_vision__en_stages_2_blocks_1_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_1_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_1_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_1_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.conv', 'vision_model.vision._en.stages.2.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_5']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1344,9 +1344,9 @@ getitem_15 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J† pkg.torch.onnx.fx_nodeë%conv2d_29 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_15, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.fc1', 'conv2d_29']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1367,9 +1367,9 @@ getitem_15 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J› pkg.torch.onnx.fx_node€%gelu_10 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_29,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes£['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.act', 'gelu_10']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1396,9 +1396,9 @@ getitem_15 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J„ pkg.torch.onnx.fx_nodeé%conv2d_30 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_10, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_1_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.mlp', 'vision_model.vision._en.stages.2.blocks.1.mlp.fc2', 'conv2d_30']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1420,9 +1420,9 @@ node_mul_5"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']JÄ pkg.torch.onnx.fx_node©%mul_5 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_11, %p_vision_model_vision__en_stages_2_blocks_1_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'vision_model.vision._en.stages.2.blocks.1.layer_scale', 'mul_5']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1442,9 +1442,9 @@ node_add_5"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŒ pkg.torch.onnx.fx_noder%add_5 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_27, %mul_5), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.1', 'add_5']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1467,9 +1467,9 @@ Gvision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÀ pkg.torch.onnx.fx_node¥%conv2d_31 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_5, %p_vision_model_vision__en_stages_2_blocks_2_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_2_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.token_mixer', 'vision_model.vision._en.stages.2.blocks.2.token_mixer.reparam_conv', 'conv2d_31']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1498,9 +1498,9 @@ getitem_18 node_Conv_194"Conv* pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Já pkg.torch.onnx.fx_nodeÆ%_native_batch_norm_legit_no_training_6 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_32, %p_vision_model_vision__en_stages_2_blocks_2_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_2_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_2_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_2_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.conv', 'vision_model.vision._en.stages.2.blocks.2.mlp.conv.bn', '_native_batch_norm_legit_no_training_6']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1530,9 +1530,9 @@ getitem_18 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J† pkg.torch.onnx.fx_nodeë%conv2d_33 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_18, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.fc1', 'conv2d_33']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1553,9 +1553,9 @@ getitem_18 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J› pkg.torch.onnx.fx_node€%gelu_11 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_33,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes£['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.act', 'gelu_11']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1582,9 +1582,9 @@ getitem_18 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J„ pkg.torch.onnx.fx_nodeé%conv2d_34 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_12, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_2_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.mlp', 'vision_model.vision._en.stages.2.blocks.2.mlp.fc2', 'conv2d_34']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1606,9 +1606,9 @@ node_mul_6"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']JÄ pkg.torch.onnx.fx_node©%mul_6 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_13, %p_vision_model_vision__en_stages_2_blocks_2_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'vision_model.vision._en.stages.2.blocks.2.layer_scale', 'mul_6']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1628,9 +1628,9 @@ node_add_6"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŒ pkg.torch.onnx.fx_noder%add_6 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_31, %mul_6), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.2', 'add_6']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1653,9 +1653,9 @@ Gvision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÀ pkg.torch.onnx.fx_node¥%conv2d_35 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_6, %p_vision_model_vision__en_stages_2_blocks_3_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_3_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.token_mixer', 'vision_model.vision._en.stages.2.blocks.3.token_mixer.reparam_conv', 'conv2d_35']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1684,9 +1684,9 @@ getitem_21 node_Conv_196"Conv* pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Já pkg.torch.onnx.fx_nodeÆ%_native_batch_norm_legit_no_training_7 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_36, %p_vision_model_vision__en_stages_2_blocks_3_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_3_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_3_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_3_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.conv', 'vision_model.vision._en.stages.2.blocks.3.mlp.conv.bn', '_native_batch_norm_legit_no_training_7']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1716,9 +1716,9 @@ getitem_21 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J† pkg.torch.onnx.fx_nodeë%conv2d_37 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_21, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.fc1', 'conv2d_37']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1739,9 +1739,9 @@ getitem_21 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J› pkg.torch.onnx.fx_node€%gelu_12 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_37,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes£['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.act', 'gelu_12']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1768,9 +1768,9 @@ getitem_21 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J„ pkg.torch.onnx.fx_nodeé%conv2d_38 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_14, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_3_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.mlp', 'vision_model.vision._en.stages.2.blocks.3.mlp.fc2', 'conv2d_38']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1792,9 +1792,9 @@ node_mul_7"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']JÄ pkg.torch.onnx.fx_node©%mul_7 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_15, %p_vision_model_vision__en_stages_2_blocks_3_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'vision_model.vision._en.stages.2.blocks.3.layer_scale', 'mul_7']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1814,9 +1814,9 @@ node_add_7"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŒ pkg.torch.onnx.fx_noder%add_7 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_35, %mul_7), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.3', 'add_7']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1839,9 +1839,9 @@ Gvision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÀ pkg.torch.onnx.fx_node¥%conv2d_39 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_7, %p_vision_model_vision__en_stages_2_blocks_4_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_4_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.token_mixer', 'vision_model.vision._en.stages.2.blocks.4.token_mixer.reparam_conv', 'conv2d_39']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1870,9 +1870,9 @@ getitem_24 node_Conv_198"Conv* pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Já pkg.torch.onnx.fx_nodeÆ%_native_batch_norm_legit_no_training_8 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_40, %p_vision_model_vision__en_stages_2_blocks_4_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_4_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_4_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_4_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.conv', 'vision_model.vision._en.stages.2.blocks.4.mlp.conv.bn', '_native_batch_norm_legit_no_training_8']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1902,9 +1902,9 @@ getitem_24 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J† pkg.torch.onnx.fx_nodeë%conv2d_41 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_24, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.fc1', 'conv2d_41']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1925,9 +1925,9 @@ getitem_24 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J› pkg.torch.onnx.fx_node€%gelu_13 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_41,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes£['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.act', 'gelu_13']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1954,9 +1954,9 @@ getitem_24 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J„ pkg.torch.onnx.fx_nodeé%conv2d_42 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_16, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_4_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.mlp', 'vision_model.vision._en.stages.2.blocks.4.mlp.fc2', 'conv2d_42']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -1978,9 +1978,9 @@ node_mul_8"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']JÄ pkg.torch.onnx.fx_node©%mul_8 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_17, %p_vision_model_vision__en_stages_2_blocks_4_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'vision_model.vision._en.stages.2.blocks.4.layer_scale', 'mul_8']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2000,9 +2000,9 @@ node_add_8"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŒ pkg.torch.onnx.fx_noder%add_8 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_39, %mul_8), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.4', 'add_8']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2025,9 +2025,9 @@ Gvision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÀ pkg.torch.onnx.fx_node¥%conv2d_43 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_8, %p_vision_model_vision__en_stages_2_blocks_5_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_2_blocks_5_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 256), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.token_mixer', 'vision_model.vision._en.stages.2.blocks.5.token_mixer.reparam_conv', 'conv2d_43']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2056,9 +2056,9 @@ getitem_27 node_Conv_200"Conv* pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Já pkg.torch.onnx.fx_nodeÆ%_native_batch_norm_legit_no_training_9 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_44, %p_vision_model_vision__en_stages_2_blocks_5_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_2_blocks_5_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_2_blocks_5_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_2_blocks_5_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.conv', 'vision_model.vision._en.stages.2.blocks.5.mlp.conv.bn', '_native_batch_norm_legit_no_training_9']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2088,9 +2088,9 @@ getitem_27 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J† pkg.torch.onnx.fx_nodeë%conv2d_45 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_27, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc1_weight, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.fc1', 'conv2d_45']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2111,9 +2111,9 @@ getitem_27 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J› pkg.torch.onnx.fx_node€%gelu_14 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_45,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes£['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.act', 'gelu_14']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2140,9 +2140,9 @@ getitem_27 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J„ pkg.torch.onnx.fx_nodeé%conv2d_46 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_18, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc2_weight, %p_vision_model_vision__en_stages_2_blocks_5_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.mlp', 'vision_model.vision._en.stages.2.blocks.5.mlp.fc2', 'conv2d_46']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2164,9 +2164,9 @@ node_mul_9"MulJ pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']JÄ pkg.torch.onnx.fx_node©%mul_9 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_19, %p_vision_model_vision__en_stages_2_blocks_5_layer_scale_gamma), kwargs = {})J“ pkg.torch.onnx.name_scopesô['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'vision_model.vision._en.stages.2.blocks.5.layer_scale', 'mul_9']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2186,9 +2186,9 @@ node_add_9"AddJ pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŒ pkg.torch.onnx.fx_noder%add_9 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_43, %mul_9), kwargs = {})JÚ pkg.torch.onnx.name_scopes»['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.2', 'vision_model.vision._en.stages.2.blocks', 'vision_model.vision._en.stages.2.blocks.5', 'add_9']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2211,9 +2211,9 @@ Dvision_model.vision._en.stages.3.downsample.proj.0.reparam_conv.bias conv2d_47 pkg.torch.onnx.class_hierarchyº['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.ReparamLargeKernelConv', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jº pkg.torch.onnx.fx_nodeŸ%conv2d_47 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_9, %p_vision_model_vision__en_stages_3_downsample_proj_0_reparam_conv_weight, %p_vision_model_vision__en_stages_3_downsample_proj_0_reparam_conv_bias, [2, 2], [3, 3], [1, 1], 256), kwargs = {})Jâ pkg.torch.onnx.name_scopesÃ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.0', 'vision_model.vision._en.stages.3.downsample.proj.0.reparam_conv', 'conv2d_47']J‚ -pkg.torch.onnx.stack_traceãFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceãFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2240,9 +2240,9 @@ Dvision_model.vision._en.stages.3.downsample.proj.1.reparam_conv.bias conv2d_48 pkg.torch.onnx.class_hierarchy²['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J¡ pkg.torch.onnx.fx_node†%conv2d_48 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%conv2d_47, %p_vision_model_vision__en_stages_3_downsample_proj_1_reparam_conv_weight, %p_vision_model_vision__en_stages_3_downsample_proj_1_reparam_conv_bias), kwargs = {})Jâ pkg.torch.onnx.name_scopesÃ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.1', 'vision_model.vision._en.stages.3.downsample.proj.1.reparam_conv', 'conv2d_48']J– -pkg.torch.onnx.stack_trace÷File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace÷File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2263,9 +2263,9 @@ Dvision_model.vision._en.stages.3.downsample.proj.1.reparam_conv.bias conv2d_48 pkg.torch.onnx.class_hierarchy´['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'timm.models.fastvit.PatchEmbed', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J› pkg.torch.onnx.fx_node€%gelu_15 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_48,), kwargs = {approximate: tanh})J× pkg.torch.onnx.name_scopes¸['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.downsample', 'vision_model.vision._en.stages.3.downsample.proj', 'vision_model.vision._en.stages.3.downsample.proj.1', 'vision_model.vision._en.stages.3.downsample.proj.1.act', 'gelu_15']Jˆ -pkg.torch.onnx.stack_traceéFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceéFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2292,9 +2292,9 @@ Gvision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J pkg.torch.onnx.fx_node§%conv2d_49 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%gelu_15, %p_vision_model_vision__en_stages_3_blocks_0_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_3_blocks_0_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.token_mixer', 'vision_model.vision._en.stages.3.blocks.0.token_mixer.reparam_conv', 'conv2d_49']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2323,9 +2323,9 @@ getitem_30 node_Conv_202"Conv* pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Jâ pkg.torch.onnx.fx_nodeÇ%_native_batch_norm_legit_no_training_10 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_50, %p_vision_model_vision__en_stages_3_blocks_0_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_3_blocks_0_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_3_blocks_0_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_3_blocks_0_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})Jœ pkg.torch.onnx.name_scopesý['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.conv', 'vision_model.vision._en.stages.3.blocks.0.mlp.conv.bn', '_native_batch_norm_legit_no_training_10']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2355,9 +2355,9 @@ getitem_30 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J† pkg.torch.onnx.fx_nodeë%conv2d_51 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_30, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc1_weight, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.fc1', 'conv2d_51']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2378,9 +2378,9 @@ getitem_30 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J› pkg.torch.onnx.fx_node€%gelu_16 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_51,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes£['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.act', 'gelu_16']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2407,9 +2407,9 @@ getitem_30 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J„ pkg.torch.onnx.fx_nodeé%conv2d_52 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_20, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc2_weight, %p_vision_model_vision__en_stages_3_blocks_0_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.mlp', 'vision_model.vision._en.stages.3.blocks.0.mlp.fc2', 'conv2d_52']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2430,9 +2430,9 @@ getitem_30 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']JÅ pkg.torch.onnx.fx_nodeª%mul_10 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_21, %p_vision_model_vision__en_stages_3_blocks_0_layer_scale_gamma), kwargs = {})J” pkg.torch.onnx.name_scopesõ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'vision_model.vision._en.stages.3.blocks.0.layer_scale', 'mul_10']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2451,9 +2451,9 @@ getitem_30 pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŽ pkg.torch.onnx.fx_nodet%add_10 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_49, %mul_10), kwargs = {})JÛ pkg.torch.onnx.name_scopes¼['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.0', 'add_10']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2476,9 +2476,9 @@ Gvision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv.bias conv2d pkg.torch.onnx.class_hierarchy¯['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.RepMixer', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']JÁ pkg.torch.onnx.fx_node¦%conv2d_53 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_10, %p_vision_model_vision__en_stages_3_blocks_1_token_mixer_reparam_conv_weight, %p_vision_model_vision__en_stages_3_blocks_1_token_mixer_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.token_mixer', 'vision_model.vision._en.stages.3.blocks.1.token_mixer.reparam_conv', 'conv2d_53']J„ -pkg.torch.onnx.stack_traceåFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceåFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2507,9 +2507,9 @@ getitem_33 node_Conv_204"Conv* pkg.torch.onnx.class_hierarchyú['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.conv_bn_act.ConvNormAct', 'timm.layers.norm_act.BatchNormAct2d', 'aten._native_batch_norm_legit_no_training.default']Jâ pkg.torch.onnx.fx_nodeÇ%_native_batch_norm_legit_no_training_11 : [num_users=1] = call_function[target=torch.ops.aten._native_batch_norm_legit_no_training.default](args = (%conv2d_54, %p_vision_model_vision__en_stages_3_blocks_1_mlp_conv_bn_weight, %p_vision_model_vision__en_stages_3_blocks_1_mlp_conv_bn_bias, %b_vision_model_vision__en_stages_3_blocks_1_mlp_conv_bn_running_mean, %b_vision_model_vision__en_stages_3_blocks_1_mlp_conv_bn_running_var, 0.1, 1e-05), kwargs = {})Jœ pkg.torch.onnx.name_scopesý['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.conv', 'vision_model.vision._en.stages.3.blocks.1.mlp.conv.bn', '_native_batch_norm_legit_no_training_11']Jñ -pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÒ File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2539,9 +2539,9 @@ getitem_33 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J† pkg.torch.onnx.fx_nodeë%conv2d_55 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%getitem_33, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc1_weight, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc1_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.fc1', 'conv2d_55']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2562,9 +2562,9 @@ getitem_33 pkg.torch.onnx.class_hierarchy°['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J› pkg.torch.onnx.fx_node€%gelu_17 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%conv2d_55,), kwargs = {approximate: tanh})J pkg.torch.onnx.name_scopes£['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.act', 'gelu_17']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2591,9 +2591,9 @@ getitem_33 pkg.torch.onnx.class_hierarchy®['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.ConvMlp', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J„ pkg.torch.onnx.fx_nodeé%conv2d_56 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%clone_22, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc2_weight, %p_vision_model_vision__en_stages_3_blocks_1_mlp_fc2_bias), kwargs = {})JÄ pkg.torch.onnx.name_scopes¥['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.mlp', 'vision_model.vision._en.stages.3.blocks.1.mlp.fc2', 'conv2d_56']J™ -pkg.torch.onnx.stack_traceúFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceúFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2614,9 +2614,9 @@ getitem_33 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'timm.models.fastvit.LayerScale2d', 'aten.mul.Tensor']JÅ pkg.torch.onnx.fx_nodeª%mul_11 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%clone_23, %p_vision_model_vision__en_stages_3_blocks_1_layer_scale_gamma), kwargs = {})J” pkg.torch.onnx.name_scopesõ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'vision_model.vision._en.stages.3.blocks.1.layer_scale', 'mul_11']JŸ -pkg.torch.onnx.stack_trace€File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace€File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2635,9 +2635,9 @@ getitem_33 pkg.torch.onnx.class_hierarchyë['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.FastVitStage', 'torch.nn.modules.container.Sequential', 'timm.models.fastvit.RepMixerBlock', 'aten.add.Tensor']JŽ pkg.torch.onnx.fx_nodet%add_11 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%conv2d_53, %mul_11), kwargs = {})JÛ pkg.torch.onnx.name_scopes¼['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.stages.3', 'vision_model.vision._en.stages.3.blocks', 'vision_model.vision._en.stages.3.blocks.1', 'add_11']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2660,9 +2660,9 @@ getitem_33 pkg.torch.onnx.class_hierarchyÃ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']J› pkg.torch.onnx.fx_node€%conv2d_57 : [num_users=2] = call_function[target=torch.ops.aten.conv2d.default](args = (%add_11, %p_vision_model_vision__en_final_conv_reparam_conv_weight, %p_vision_model_vision__en_final_conv_reparam_conv_bias, [1, 1], [1, 1], [1, 1], 512), kwargs = {})J» pkg.torch.onnx.name_scopesœ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.reparam_conv', 'conv2d_57']J‰ -pkg.torch.onnx.stack_traceêFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceêFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2680,9 +2680,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchyÄ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'aten.mean.dim']J pkg.torch.onnx.fx_nodeu%mean : [num_users=1] = call_function[target=torch.ops.aten.mean.dim](args = (%conv2d_57, [2, 3], True), kwargs = {})J¬ pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'mean']Jø -pkg.torch.onnx.stack_traceÙFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÙFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2703,9 +2703,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchyê['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jð pkg.torch.onnx.fx_nodeÕ%conv2d_58 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%mean, %p_vision_model_vision__en_final_conv_se_fc1_weight, %p_vision_model_vision__en_final_conv_se_fc1_bias), kwargs = {})JÞ pkg.torch.onnx.name_scopes¿['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.fc1', 'conv2d_58']J’ -pkg.torch.onnx.stack_traceóFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceóFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2721,9 +2721,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchyì['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J† pkg.torch.onnx.fx_nodel%relu : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%conv2d_58,), kwargs = {})JÙ pkg.torch.onnx.name_scopesº['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.act', 'relu']J“ -pkg.torch.onnx.stack_traceôFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceôFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2746,9 +2746,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchyê['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'torch.nn.modules.conv.Conv2d', 'aten.conv2d.default']Jð pkg.torch.onnx.fx_nodeÕ%conv2d_59 : [num_users=1] = call_function[target=torch.ops.aten.conv2d.default](args = (%relu, %p_vision_model_vision__en_final_conv_se_fc2_weight, %p_vision_model_vision__en_final_conv_se_fc2_bias), kwargs = {})JÞ pkg.torch.onnx.name_scopes¿['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.fc2', 'conv2d_59']J’ -pkg.torch.onnx.stack_traceóFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceóFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2764,9 +2764,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchyî['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'timm.layers.activations.Sigmoid', 'aten.sigmoid.default']JŒ pkg.torch.onnx.fx_noder%sigmoid : [num_users=1] = call_function[target=torch.ops.aten.sigmoid.default](args = (%conv2d_59,), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'vision_model.vision._en.final_conv.se.gate', 'sigmoid']J” -pkg.torch.onnx.stack_traceõFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceõFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2783,9 +2783,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchyÆ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.squeeze_excite.SEModule', 'aten.mul.Tensor']J pkg.torch.onnx.fx_nodeu%mul_12 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%conv2d_57, %sigmoid), kwargs = {})J® pkg.torch.onnx.name_scopes['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.se', 'mul_12']Jï -pkg.torch.onnx.stack_traceÐFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÐFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2800,9 +2800,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchyÅ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.models.fastvit.MobileOneBlock', 'timm.layers.activations.GELUTanh', 'aten.gelu.default']J— pkg.torch.onnx.fx_node}%gelu_18 : [num_users=1] = call_function[target=torch.ops.aten.gelu.default](args = (%mul_12,), kwargs = {approximate: tanh})J° pkg.torch.onnx.name_scopes‘['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.final_conv', 'vision_model.vision._en.final_conv.act', 'gelu_18']Jû -pkg.torch.onnx.stack_traceÜFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÜFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1418, in forward x = self.forward_features(x) @@ -2820,9 +2820,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchy‡['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d', 'torch.nn.modules.pooling.AdaptiveAvgPool2d', 'aten.mean.dim']J‘ pkg.torch.onnx.fx_nodew%mean_1 : [num_users=1] = call_function[target=torch.ops.aten.mean.dim](args = (%gelu_18, [-1, -2], True), kwargs = {})JÜ pkg.torch.onnx.name_scopes½['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.global_pool', 'vision_model.vision._en.head.global_pool.pool', 'mean_1']Jý -pkg.torch.onnx.stack_traceÞFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÞFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) @@ -2840,9 +2840,9 @@ ReduceMean* pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'timm.layers.adaptive_avgmax_pool.SelectAdaptivePool2d', 'torch.nn.modules.flatten.Flatten', 'aten.view.default']J pkg.torch.onnx.fx_nodes%view : [num_users=1] = call_function[target=torch.ops.aten.view.default](args = (%mean_1, [1, 1024]), kwargs = {})JÝ pkg.torch.onnx.name_scopes¾['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.global_pool', 'vision_model.vision._en.head.global_pool.flatten', 'view']Jû -pkg.torch.onnx.stack_traceÜFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÜFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) @@ -2864,9 +2864,9 @@ $vision_model.vision._en.head.fc.biaslinear node_linear"Gemm* pkg.torch.onnx.class_hierarchyÈ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Vision', 'timm.models.fastvit.FastVit', 'timm.layers.classifier.ClassifierHead', 'torch.nn.modules.linear.Linear', 'aten.linear.default']JÝ pkg.torch.onnx.fx_nodeÂ%linear : [num_users=3] = call_function[target=torch.ops.aten.linear.default](args = (%clone_24, %p_vision_model_vision__en_head_fc_weight, %p_vision_model_vision__en_head_fc_bias), kwargs = {})J¢ pkg.torch.onnx.name_scopesƒ['', 'vision_model.vision', 'vision_model.vision._en', 'vision_model.vision._en.head', 'vision_model.vision._en.head.fc', 'linear']Jà -pkg.torch.onnx.stack_traceÁFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÁFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 187, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 185, in forward return self._en(x).flatten(1) File "/home/batman/xx/.venv/lib/python3.12/site-packages/timm/models/fastvit.py", line 1421, in forward x = self.forward_head(x) @@ -2886,9 +2886,9 @@ $vision_model.vision._en.head.fc.biaslinear node_linear"Gemm* pkg.torch.onnx.class_hierarchyû['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeò%linear_1 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%linear, %p_vision_model_point_policy_summarizer_resblock_block_a_0_weight, %p_vision_model_point_policy_summarizer_resblock_block_a_0_bias), kwargs = {})J™ pkg.torch.onnx.name_scopesú['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.0', 'linear_1']J¼ -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -2911,9 +2911,9 @@ stash_type pkg.torch.onnx.class_hierarchy‰['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J pkg.torch.onnx.fx_node‚%layer_norm : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_1, [1024], %p_vision_model_point_policy_summarizer_resblock_block_a_1_weight, %p_vision_model_point_policy_summarizer_resblock_block_a_1_bias), kwargs = {})J› pkg.torch.onnx.name_scopesü['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.1', 'layer_norm']J© -pkg.torch.onnx.stack_traceŠFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceŠFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -2930,9 +2930,9 @@ layer_normrelu_1 node_relu_1"ReluJ pkg.torch.onnx.class_hierarchyû['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_1 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%layer_norm,), kwargs = {})J— pkg.torch.onnx.name_scopesø['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.2', 'relu_1']J¼ -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -2954,9 +2954,9 @@ layer_normrelu_1 node_relu_1"ReluJ pkg.torch.onnx.class_hierarchyû['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeò%linear_2 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_1, %p_vision_model_point_policy_summarizer_resblock_block_a_3_weight, %p_vision_model_point_policy_summarizer_resblock_block_a_3_bias), kwargs = {})J™ pkg.torch.onnx.name_scopesú['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.3', 'linear_2']J¼ -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -2978,9 +2978,9 @@ stash_type pkg.torch.onnx.class_hierarchy‰['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']Jž pkg.torch.onnx.fx_nodeƒ%layer_norm_1 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_2, [512], %p_vision_model_point_policy_summarizer_resblock_block_a_4_weight, %p_vision_model_point_policy_summarizer_resblock_block_a_4_bias), kwargs = {})J pkg.torch.onnx.name_scopesþ['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_a', 'vision_model.point_policy.summarizer.resblock.block_a.4', 'layer_norm_1']J© -pkg.torch.onnx.stack_traceŠFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceŠFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -2998,9 +2998,9 @@ stash_type pkg.torch.onnx.class_hierarchy¬['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'aten.add.Tensor']J‘ pkg.torch.onnx.fx_nodew%add_12 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%linear, %layer_norm_1), kwargs = {})J£ pkg.torch.onnx.name_scopes„['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'add_12']JŒ -pkg.torch.onnx.stack_traceíFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceíFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3012,9 +3012,9 @@ stash_type pkg.torch.onnx.class_hierarchyû['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J… pkg.torch.onnx.fx_nodek%relu_2 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%add_12,), kwargs = {})J— pkg.torch.onnx.name_scopesø['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.0', 'relu_2']JÀ -pkg.torch.onnx.stack_trace¡File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace¡File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3036,9 +3036,9 @@ stash_type pkg.torch.onnx.class_hierarchyû['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeò%linear_3 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_2, %p_vision_model_point_policy_summarizer_resblock_block_b_1_weight, %p_vision_model_point_policy_summarizer_resblock_block_b_1_bias), kwargs = {})J™ pkg.torch.onnx.name_scopesú['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.1', 'linear_3']JÀ -pkg.torch.onnx.stack_trace¡File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace¡File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3060,9 +3060,9 @@ stash_type pkg.torch.onnx.class_hierarchy‰['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']JŸ pkg.torch.onnx.fx_node„%layer_norm_2 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_3, [1024], %p_vision_model_point_policy_summarizer_resblock_block_b_2_weight, %p_vision_model_point_policy_summarizer_resblock_block_b_2_bias), kwargs = {})J pkg.torch.onnx.name_scopesþ['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.2', 'layer_norm_2']J­ -pkg.torch.onnx.stack_traceŽFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceŽFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3078,9 +3078,9 @@ stash_type pkg.torch.onnx.class_hierarchyû['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‹ pkg.torch.onnx.fx_nodeq%relu_3 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%layer_norm_2,), kwargs = {})J— pkg.torch.onnx.name_scopesø['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.3', 'relu_3']JÀ -pkg.torch.onnx.stack_trace¡File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace¡File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3102,9 +3102,9 @@ stash_type pkg.torch.onnx.class_hierarchyû['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeò%linear_4 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_3, %p_vision_model_point_policy_summarizer_resblock_block_b_4_weight, %p_vision_model_point_policy_summarizer_resblock_block_b_4_bias), kwargs = {})J™ pkg.torch.onnx.name_scopesú['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.4', 'linear_4']JÀ -pkg.torch.onnx.stack_trace¡File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace¡File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3126,9 +3126,9 @@ stash_type pkg.torch.onnx.class_hierarchy‰['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']Jž pkg.torch.onnx.fx_nodeƒ%layer_norm_3 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_4, [512], %p_vision_model_point_policy_summarizer_resblock_block_b_5_weight, %p_vision_model_point_policy_summarizer_resblock_block_b_5_bias), kwargs = {})J pkg.torch.onnx.name_scopesþ['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.block_b', 'vision_model.point_policy.summarizer.resblock.block_b.5', 'layer_norm_3']J­ -pkg.torch.onnx.stack_traceŽFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceŽFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3145,9 +3145,9 @@ stash_type pkg.torch.onnx.class_hierarchy¬['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'aten.add.Tensor']J‘ pkg.torch.onnx.fx_nodew%add_13 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_2, %layer_norm_3), kwargs = {})J£ pkg.torch.onnx.name_scopes„['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'add_13']J¡ -pkg.torch.onnx.stack_trace‚File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace‚File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3159,9 +3159,9 @@ stash_type pkg.torch.onnx.class_hierarchyÒ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.PointSummarizer', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J… pkg.torch.onnx.fx_nodek%relu_4 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%add_13,), kwargs = {})Jß pkg.torch.onnx.name_scopesÀ['', 'vision_model.point_policy', 'vision_model.point_policy.summarizer', 'vision_model.point_policy.summarizer.resblock', 'vision_model.point_policy.summarizer.resblock.final_relu', 'relu_4']JÁ -pkg.torch.onnx.stack_trace¢File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace¢File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 133, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 131, in forward summary_outs = self.summarizer(vision_features) File "/home/batman/xx/xx/training/path/supercombo.py", line 45, in forward x = self.resblock(x) @@ -3181,9 +3181,9 @@ stash_type pkg.torch.onnx.class_hierarchyñ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']Jƒ pkg.torch.onnx.fx_nodeè%linear_5 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_4, %p_vision_model_point_policy_hydra_resblock_block_a_0_weight, %p_vision_model_point_policy_hydra_resblock_block_a_0_bias), kwargs = {})J… pkg.torch.onnx.name_scopesæ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.0', 'linear_5']J» -pkg.torch.onnx.stack_traceœFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceœFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3205,9 +3205,9 @@ stash_type pkg.torch.onnx.class_hierarchyÿ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J• pkg.torch.onnx.fx_nodeú%layer_norm_4 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_5, [1024], %p_vision_model_point_policy_hydra_resblock_block_a_1_weight, %p_vision_model_point_policy_hydra_resblock_block_a_1_bias), kwargs = {})J‰ pkg.torch.onnx.name_scopesê['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.1', 'layer_norm_4']J¨ -pkg.torch.onnx.stack_trace‰File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace‰File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3223,9 +3223,9 @@ stash_type pkg.torch.onnx.class_hierarchyñ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‹ pkg.torch.onnx.fx_nodeq%relu_5 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%layer_norm_4,), kwargs = {})Jƒ pkg.torch.onnx.name_scopesä['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.2', 'relu_5']J» -pkg.torch.onnx.stack_traceœFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceœFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3247,9 +3247,9 @@ stash_type pkg.torch.onnx.class_hierarchyñ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']Jƒ pkg.torch.onnx.fx_nodeè%linear_6 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_5, %p_vision_model_point_policy_hydra_resblock_block_a_3_weight, %p_vision_model_point_policy_hydra_resblock_block_a_3_bias), kwargs = {})J… pkg.torch.onnx.name_scopesæ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.3', 'linear_6']J» -pkg.torch.onnx.stack_traceœFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceœFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3271,9 +3271,9 @@ stash_type pkg.torch.onnx.class_hierarchyÿ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J” pkg.torch.onnx.fx_nodeù%layer_norm_5 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_6, [512], %p_vision_model_point_policy_hydra_resblock_block_a_4_weight, %p_vision_model_point_policy_hydra_resblock_block_a_4_bias), kwargs = {})J‰ pkg.torch.onnx.name_scopesê['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_a', 'vision_model.point_policy.hydra.resblock.block_a.4', 'layer_norm_5']J¨ -pkg.torch.onnx.stack_trace‰File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace‰File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3291,9 +3291,9 @@ stash_type pkg.torch.onnx.class_hierarchy¢['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'aten.add.Tensor']J‘ pkg.torch.onnx.fx_nodew%add_14 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_4, %layer_norm_5), kwargs = {})J˜ pkg.torch.onnx.name_scopesz['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'add_14']J‹ -pkg.torch.onnx.stack_traceìFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceìFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3305,9 +3305,9 @@ stash_type pkg.torch.onnx.class_hierarchyñ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J… pkg.torch.onnx.fx_nodek%relu_6 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%add_14,), kwargs = {})Jƒ pkg.torch.onnx.name_scopesä['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.0', 'relu_6']J¿ -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3329,9 +3329,9 @@ stash_type pkg.torch.onnx.class_hierarchyñ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']Jƒ pkg.torch.onnx.fx_nodeè%linear_7 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_6, %p_vision_model_point_policy_hydra_resblock_block_b_1_weight, %p_vision_model_point_policy_hydra_resblock_block_b_1_bias), kwargs = {})J… pkg.torch.onnx.name_scopesæ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.1', 'linear_7']J¿ -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3353,9 +3353,9 @@ stash_type pkg.torch.onnx.class_hierarchyÿ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J• pkg.torch.onnx.fx_nodeú%layer_norm_6 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_7, [1024], %p_vision_model_point_policy_hydra_resblock_block_b_2_weight, %p_vision_model_point_policy_hydra_resblock_block_b_2_bias), kwargs = {})J‰ pkg.torch.onnx.name_scopesê['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.2', 'layer_norm_6']J¬ -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3371,9 +3371,9 @@ stash_type pkg.torch.onnx.class_hierarchyñ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‹ pkg.torch.onnx.fx_nodeq%relu_7 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%layer_norm_6,), kwargs = {})Jƒ pkg.torch.onnx.name_scopesä['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.3', 'relu_7']J¿ -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3395,9 +3395,9 @@ stash_type pkg.torch.onnx.class_hierarchyñ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']Jƒ pkg.torch.onnx.fx_nodeè%linear_8 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_7, %p_vision_model_point_policy_hydra_resblock_block_b_4_weight, %p_vision_model_point_policy_hydra_resblock_block_b_4_bias), kwargs = {})J… pkg.torch.onnx.name_scopesæ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.4', 'linear_8']J¿ -pkg.torch.onnx.stack_trace File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3419,9 +3419,9 @@ stash_type pkg.torch.onnx.class_hierarchyÿ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.normalization.LayerNorm', 'aten.layer_norm.default']J” pkg.torch.onnx.fx_nodeù%layer_norm_7 : [num_users=1] = call_function[target=torch.ops.aten.layer_norm.default](args = (%linear_8, [512], %p_vision_model_point_policy_hydra_resblock_block_b_5_weight, %p_vision_model_point_policy_hydra_resblock_block_b_5_bias), kwargs = {})J‰ pkg.torch.onnx.name_scopesê['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.block_b', 'vision_model.point_policy.hydra.resblock.block_b.5', 'layer_norm_7']J¬ -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3439,9 +3439,9 @@ stash_type pkg.torch.onnx.class_hierarchy¢['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'aten.add.Tensor']J‘ pkg.torch.onnx.fx_nodew%add_15 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_6, %layer_norm_7), kwargs = {})J˜ pkg.torch.onnx.name_scopesz['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'add_15']J  -pkg.torch.onnx.stack_traceFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3453,9 +3453,9 @@ stash_type pkg.torch.onnx.class_hierarchyÈ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'xx.training.lib.layers.ResBlock', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J… pkg.torch.onnx.fx_nodek%relu_8 : [num_users=5] = call_function[target=torch.ops.aten.relu.default](args = (%add_15,), kwargs = {})JÐ pkg.torch.onnx.name_scopes±['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.resblock', 'vision_model.point_policy.hydra.resblock.final_relu', 'relu_8']JÀ -pkg.torch.onnx.stack_trace¡File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace¡File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 109, in forward x = self.resblock(in_feats) @@ -3475,9 +3475,9 @@ stash_type pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']Jû pkg.torch.onnx.fx_nodeà%linear_9 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_25, %p_vision_model_point_policy_hydra_in_layer_meta_weight, %p_vision_model_point_policy_hydra_in_layer_meta_bias), kwargs = {})J  pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.meta', 'linear_9']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3489,9 +3489,9 @@ stash_type pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‡ pkg.torch.onnx.fx_nodem%relu_9 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_9,), kwargs = {})J” pkg.torch.onnx.name_scopesv['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_9']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3509,9 +3509,9 @@ stash_type pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']JŠ pkg.torch.onnx.fx_nodeï%linear_10 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_26, %p_vision_model_point_policy_hydra_in_layer_desire_pred_weight, %p_vision_model_point_policy_hydra_in_layer_desire_pred_bias), kwargs = {})J¨ pkg.torch.onnx.name_scopes‰['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.desire_pred', 'linear_10']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3523,9 +3523,9 @@ stash_type pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_10 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_10,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_10']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3543,9 +3543,9 @@ stash_type pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeõ%linear_11 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_27, %p_vision_model_point_policy_hydra_in_layer_road_transform_weight, %p_vision_model_point_policy_hydra_in_layer_road_transform_bias), kwargs = {})J« pkg.torch.onnx.name_scopesŒ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.road_transform', 'linear_11']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3557,9 +3557,9 @@ stash_type pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_11 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_11,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_11']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3577,9 +3577,9 @@ stash_type pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']Jü pkg.torch.onnx.fx_nodeá%linear_12 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_28, %p_vision_model_point_policy_hydra_in_layer_pose_weight, %p_vision_model_point_policy_hydra_in_layer_pose_bias), kwargs = {})J¡ pkg.torch.onnx.name_scopes‚['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.pose', 'linear_12']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3591,9 +3591,9 @@ stash_type pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_12 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_12,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_12']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3611,9 +3611,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J  pkg.torch.onnx.fx_node…%linear_13 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%clone_29, %p_vision_model_point_policy_hydra_in_layer_wide_from_device_euler_weight, %p_vision_model_point_policy_hydra_in_layer_wide_from_device_euler_bias), kwargs = {})J³ pkg.torch.onnx.name_scopes”['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.in_layer.wide_from_device_euler', 'linear_13']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3625,9 +3625,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_13 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%linear_13,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_13']Jƒ -pkg.torch.onnx.stack_traceäFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceäFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 113, in forward in_layer = {k: self.relu(v(in_dropouts[k])) for k,v in self.in_layer.items()} @@ -3645,9 +3645,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J€ pkg.torch.onnx.fx_nodeå%linear_14 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_9, %p_vision_model_point_policy_hydra_res_layer_meta_0_weight, %p_vision_model_point_policy_hydra_res_layer_meta_0_bias), kwargs = {})JÖ pkg.torch.onnx.name_scopes·['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.meta', 'vision_model.point_policy.hydra.res_layer.meta.0', 'linear_14']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3661,9 +3661,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_14 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_14,), kwargs = {})JÔ pkg.torch.onnx.name_scopesµ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.meta', 'vision_model.point_policy.hydra.res_layer.meta.1', 'relu_14']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3683,9 +3683,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeæ%linear_15 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_14, %p_vision_model_point_policy_hydra_res_layer_meta_2_weight, %p_vision_model_point_policy_hydra_res_layer_meta_2_bias), kwargs = {})JÖ pkg.torch.onnx.name_scopes·['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.meta', 'vision_model.point_policy.hydra.res_layer.meta.2', 'linear_15']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3700,9 +3700,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']JŽ pkg.torch.onnx.fx_nodet%add_16 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_9, %linear_15), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_16']Jð -pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3712,9 +3712,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J† pkg.torch.onnx.fx_nodel%relu_15 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_16,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_15']J -pkg.torch.onnx.stack_traceñFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceñFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3732,9 +3732,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeô%linear_16 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_10, %p_vision_model_point_policy_hydra_res_layer_desire_pred_0_weight, %p_vision_model_point_policy_hydra_res_layer_desire_pred_0_bias), kwargs = {})Jä pkg.torch.onnx.name_scopesÅ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.desire_pred', 'vision_model.point_policy.hydra.res_layer.desire_pred.0', 'linear_16']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3748,9 +3748,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_16 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_16,), kwargs = {})Jâ pkg.torch.onnx.name_scopesÃ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.desire_pred', 'vision_model.point_policy.hydra.res_layer.desire_pred.1', 'relu_16']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3770,9 +3770,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeô%linear_17 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_16, %p_vision_model_point_policy_hydra_res_layer_desire_pred_2_weight, %p_vision_model_point_policy_hydra_res_layer_desire_pred_2_bias), kwargs = {})Jä pkg.torch.onnx.name_scopesÅ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.desire_pred', 'vision_model.point_policy.hydra.res_layer.desire_pred.2', 'linear_17']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3787,9 +3787,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeu%add_17 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_10, %linear_17), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_17']Jð -pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3799,9 +3799,9 @@ Dvision_model.point_policy.hydra.in_layer.wide_from_device_euler.bias linear_13 pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J† pkg.torch.onnx.fx_nodel%relu_17 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_17,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_17']J -pkg.torch.onnx.stack_traceñFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceñFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3819,9 +3819,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.0.weight pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J• pkg.torch.onnx.fx_nodeú%linear_18 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_11, %p_vision_model_point_policy_hydra_res_layer_road_transform_0_weight, %p_vision_model_point_policy_hydra_res_layer_road_transform_0_bias), kwargs = {})Jê pkg.torch.onnx.name_scopesË['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.road_transform', 'vision_model.point_policy.hydra.res_layer.road_transform.0', 'linear_18']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3835,9 +3835,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.0.weight pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_18 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_18,), kwargs = {})Jè pkg.torch.onnx.name_scopesÉ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.road_transform', 'vision_model.point_policy.hydra.res_layer.road_transform.1', 'relu_18']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3857,9 +3857,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J• pkg.torch.onnx.fx_nodeú%linear_19 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_18, %p_vision_model_point_policy_hydra_res_layer_road_transform_2_weight, %p_vision_model_point_policy_hydra_res_layer_road_transform_2_bias), kwargs = {})Jê pkg.torch.onnx.name_scopesË['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.road_transform', 'vision_model.point_policy.hydra.res_layer.road_transform.2', 'linear_19']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3874,9 +3874,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeu%add_18 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_11, %linear_19), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_18']Jð -pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3886,9 +3886,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J† pkg.torch.onnx.fx_nodel%relu_19 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_18,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_19']J -pkg.torch.onnx.stack_traceñFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceñFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3906,9 +3906,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeæ%linear_20 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_12, %p_vision_model_point_policy_hydra_res_layer_pose_0_weight, %p_vision_model_point_policy_hydra_res_layer_pose_0_bias), kwargs = {})JÖ pkg.torch.onnx.name_scopes·['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.pose', 'vision_model.point_policy.hydra.res_layer.pose.0', 'linear_20']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3922,9 +3922,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_20 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_20,), kwargs = {})JÔ pkg.torch.onnx.name_scopesµ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.pose', 'vision_model.point_policy.hydra.res_layer.pose.1', 'relu_20']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3944,9 +3944,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeæ%linear_21 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_20, %p_vision_model_point_policy_hydra_res_layer_pose_2_weight, %p_vision_model_point_policy_hydra_res_layer_pose_2_bias), kwargs = {})JÖ pkg.torch.onnx.name_scopes·['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.pose', 'vision_model.point_policy.hydra.res_layer.pose.2', 'linear_21']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3961,9 +3961,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeu%add_19 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_12, %linear_21), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_19']Jð -pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3973,9 +3973,9 @@ Avision_model.point_policy.hydra.res_layer.road_transform.2.weight pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J† pkg.torch.onnx.fx_nodel%relu_21 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_19,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_21']J -pkg.torch.onnx.stack_traceñFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceñFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -3993,9 +3993,9 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.0.bias linear pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J¥ pkg.torch.onnx.fx_nodeŠ%linear_22 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_13, %p_vision_model_point_policy_hydra_res_layer_wide_from_device_euler_0_weight, %p_vision_model_point_policy_hydra_res_layer_wide_from_device_euler_0_bias), kwargs = {})Jú pkg.torch.onnx.name_scopesÛ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler.0', 'linear_22']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -4009,9 +4009,9 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.0.bias linear pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J‰ pkg.torch.onnx.fx_nodeo%relu_22 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%linear_22,), kwargs = {})Jø pkg.torch.onnx.name_scopesÙ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler.1', 'relu_22']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -4031,9 +4031,9 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchyÎ['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.container.Sequential', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J¥ pkg.torch.onnx.fx_nodeŠ%linear_23 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_22, %p_vision_model_point_policy_hydra_res_layer_wide_from_device_euler_2_weight, %p_vision_model_point_policy_hydra_res_layer_wide_from_device_euler_2_bias), kwargs = {})Jú pkg.torch.onnx.name_scopesÛ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler', 'vision_model.point_policy.hydra.res_layer.wide_from_device_euler.2', 'linear_23']Jš -pkg.torch.onnx.stack_traceûFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceûFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -4048,9 +4048,9 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'aten.add.Tensor']J pkg.torch.onnx.fx_nodeu%add_20 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%relu_13, %linear_23), kwargs = {})Jl pkg.torch.onnx.name_scopesN['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'add_20']Jð -pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÑFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -4060,9 +4060,9 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.activation.ReLU', 'aten.relu.default']J† pkg.torch.onnx.fx_nodel%relu_23 : [num_users=1] = call_function[target=torch.ops.aten.relu.default](args = (%add_20,), kwargs = {})J• pkg.torch.onnx.name_scopesw['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.relu', 'relu_23']J -pkg.torch.onnx.stack_traceñFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceñFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 114, in forward res_layer = {k: self.relu(in_layer[k] + v(in_layer[k])) for k,v in self.res_layer.items()} @@ -4080,9 +4080,9 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeæ%linear_24 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_15, %p_vision_model_point_policy_hydra_final_layer_meta_weight, %p_vision_model_point_policy_hydra_final_layer_meta_bias), kwargs = {})J¤ pkg.torch.onnx.name_scopes…['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.meta', 'linear_24']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 115, in forward ret = {k: v(res_layer[k]) for k,v in self.final_layer.items()} @@ -4100,9 +4100,9 @@ Gvision_model.point_policy.hydra.res_layer.wide_from_device_euler.2.bias linear pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeô%linear_25 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_17, %p_vision_model_point_policy_hydra_final_layer_desire_pred_weight, %p_vision_model_point_policy_hydra_final_layer_desire_pred_bias), kwargs = {})J« pkg.torch.onnx.name_scopesŒ['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.desire_pred', 'linear_25']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 115, in forward ret = {k: v(res_layer[k]) for k,v in self.final_layer.items()} @@ -4120,9 +4120,9 @@ Avision_model.point_policy.hydra.final_layer.road_transform.weight pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J• pkg.torch.onnx.fx_nodeú%linear_26 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_19, %p_vision_model_point_policy_hydra_final_layer_road_transform_weight, %p_vision_model_point_policy_hydra_final_layer_road_transform_bias), kwargs = {})J® pkg.torch.onnx.name_scopes['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.road_transform', 'linear_26']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 115, in forward ret = {k: v(res_layer[k]) for k,v in self.final_layer.items()} @@ -4140,9 +4140,9 @@ Avision_model.point_policy.hydra.final_layer.road_transform.weight pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J pkg.torch.onnx.fx_nodeæ%linear_27 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_21, %p_vision_model_point_policy_hydra_final_layer_pose_weight, %p_vision_model_point_policy_hydra_final_layer_pose_bias), kwargs = {})J¤ pkg.torch.onnx.name_scopes…['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.pose', 'linear_27']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 115, in forward ret = {k: v(res_layer[k]) for k,v in self.final_layer.items()} @@ -4160,9 +4160,9 @@ Gvision_model.point_policy.hydra.final_layer.wide_from_device_euler.bias linear pkg.torch.onnx.class_hierarchy¥['__main__.FlattenedVisionModel', 'xx.training.path.supercombo.Policy', 'xx.training.path.supercombo.Hydra', 'torch.nn.modules.linear.Linear', 'aten.linear.default']J¥ pkg.torch.onnx.fx_nodeŠ%linear_28 : [num_users=1] = call_function[target=torch.ops.aten.linear.default](args = (%relu_23, %p_vision_model_point_policy_hydra_final_layer_wide_from_device_euler_weight, %p_vision_model_point_policy_hydra_final_layer_wide_from_device_euler_bias), kwargs = {})J¶ pkg.torch.onnx.name_scopes—['', 'vision_model.point_policy', 'vision_model.point_policy.hydra', 'vision_model.point_policy.hydra.final_layer.wide_from_device_euler', 'linear_28']Jô -pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_traceÕFile "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) - File "/home/batman/xx/xx/training/path/supercombo.py", line 134, in forward + File "/home/batman/xx/xx/training/path/supercombo.py", line 132, in forward policy_outs = self.hydra(summary_outs) File "/home/batman/xx/xx/training/path/supercombo.py", line 115, in forward ret = {k: v(res_layer[k]) for k,v in self.final_layer.items()} @@ -4182,7 +4182,7 @@ node_cat_1"Concat* pkg.torch.onnx.class_hierarchy5['__main__.FlattenedVisionModel', 'aten.cat.default']JÌ pkg.torch.onnx.fx_node±%cat_1 : [num_users=1] = call_function[target=torch.ops.aten.cat.default](args = ([%linear_24, %linear_25, %linear_27, %linear_28, %linear_26, %detach, %p_pad], 1), kwargs = {})J+ pkg.torch.onnx.name_scopes ['', 'cat_1']JÊ -pkg.torch.onnx.stack_trace«File "/home/batman/xx/ml_tools/openpilot_compile/./compile_supercombo.py", line 91, in forward +pkg.torch.onnx.stack_trace«File "/home/batman/xx/./ml_tools/openpilot_compile/compile_supercombo.py", line 91, in forward return torch.cat([*self.forward_dict(inputs).values(), self.pad], dim=1) main_graph* BpadJ*ÂØ@