fix lfs pointers and model handling

openpilot/selfdrive/modeld/compile_modeld.py

@@ -163,7 +163,7 @@ def get_policy_npy_shapes(input_shapes):
 def make_input_queues(vision_input_shapes, policy_input_shapes, frame_skip, device):
   input_queues, npy = make_warp_input_queues(vision_input_shapes, frame_skip, device)
 
-  fb = policy_input_shapes['features_buffer']  # (1, 24, 512), past features only; the model appends the current frame's feature
+  fb = policy_input_shapes['features_buffer']  # (1, 25, 512)
   dp = policy_input_shapes['desire_pulse']  # (1, 25, 8)
 
   shapes, sizes = get_policy_npy_shapes(policy_input_shapes)
@@ -171,7 +171,7 @@ def make_input_queues(vision_input_shapes, policy_input_shapes, frame_skip, devi
   # views into the packed inputs, to be refilled at runtime
   npy.update({k: v.reshape(s) for (k, s), v in zip(shapes.items(), np.split(packed_npy_inputs, np.cumsum(sizes[:-1])), strict=True)})
   input_queues.update({
-    'feat_q': Tensor(np.zeros((frame_skip * fb[1], fb[0], fb[2]), dtype=np.float32), device=device).contiguous().realize(),
+    'feat_q': Tensor(np.zeros((frame_skip * (fb[1] - 1) + 1, fb[0], fb[2]), dtype=np.float32), device=device).contiguous().realize(),
     'desire_q': Tensor(np.zeros((frame_skip * dp[1], dp[0], dp[2]), dtype=np.float32), device=device).contiguous().realize(),
     'packed_npy_inputs': Tensor(packed_npy_inputs, device='NPY').realize(),
   })

openpilot/selfdrive/modeld/models/big_driving_off_policy.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e8508048b37e66d0e786961d2cde9a55c924f197e81e313a972d656c023b2227
-size 288
+oid sha256:8a26866121d1d3a1152bfce024ed7584b8569507d120d4bc8917320093dcd31a
+size 41191256

openpilot/selfdrive/modeld/models/big_driving_on_policy.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b947312f8d56767c0b1913ff092a1a79098ab1af8eebf30fd8b0b418371602bb
-size 288
+oid sha256:94b07ef7a0f65d5c41ac696b4ae7bdc59e2d4c5f504460e2b0d720620892c2e8
+size 33679037

openpilot/selfdrive/modeld/models/big_driving_vision.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:343778b145dafee6e06b35fc8d76121c0192d602a45825f7df8375ee32a86bda
-size 289
+oid sha256:eda005282417ffa825092ece5c16b5584142044cdbcf15b6d0246136ac6db601
+size 120584466

openpilot/selfdrive/modeld/models/driving_off_policy.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:af489cd1dbf01cc1c2339e51c0fa579bcbf92b2b76a64776acaf8b57ceb84910
-size 288
+oid sha256:6173be8a69b1d9633a09969c80b2a8bd990bfe7d3e76e192a0e537f6fd72222b
+size 41192485

openpilot/selfdrive/modeld/models/driving_on_policy.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fd7420975d5a03874e25c852fd1e4e5de1ef5c58ce8c871cca85afe129765225
-size 288
+oid sha256:6b66ef783af3fa86190e85a6b4f729cd1443b20be41134aa258f9c376825a45c
+size 33680163

openpilot/selfdrive/modeld/models/driving_vision.onnx

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ff9d05212c02e837d4903aeafe7141cd9e5742751560f3fa96759d75fd738844
-size 288
+oid sha256:bbd0761201b3b161587d097f173c66bf82cd02966e5f0d1edd888c970d6f6d87
+size 21735970

openpilot/selfdrive/modeld/parse_model_outputs.py

@@ -117,7 +117,6 @@ class Parser:
 
   def parse_policy_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]:
     self.parse_mdn('action', outs, in_N=0, out_N=0, out_shape=(ModelConstants.ACTION_WIDTH,))
-    self.parse_categorical_crossentropy('desire_state', outs, out_shape=(ModelConstants.DESIRE_PRED_WIDTH,))
     return outs
 
   def parse_outputs(self, outs: dict[str, np.ndarray]) -> dict[str, np.ndarray]: