From 6142a52de7a5749ca3797c4bda794ef7223e065f Mon Sep 17 00:00:00 2001 From: DevTekVE Date: Sat, 10 May 2025 09:46:54 +0200 Subject: [PATCH] models: aligning naming on modeld_v2 with upstream naming (#903) Refactor variable names for clarity in 20Hz model logic. Renamed `full_features_20Hz` to `full_features_buffer` and `desire_20Hz` to `full_desire` for better readability and consistency. This improves code maintainability and aligns variable names with their intended purpose. --- sunnypilot/modeld_v2/modeld.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/sunnypilot/modeld_v2/modeld.py b/sunnypilot/modeld_v2/modeld.py index e0f38c59ac..a52d844aeb 100755 --- a/sunnypilot/modeld_v2/modeld.py +++ b/sunnypilot/modeld_v2/modeld.py @@ -53,8 +53,8 @@ class ModelState: self.frames = {'input_imgs': DrivingModelFrame(context, buffer_length), 'big_input_imgs': DrivingModelFrame(context, buffer_length)} self.prev_desire = np.zeros(ModelConstants.DESIRE_LEN, dtype=np.float32) if self.model_runner.is_20hz: - self.full_features_20Hz = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.FEATURE_LEN), dtype=np.float32) - self.desire_20Hz = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN + 1, ModelConstants.DESIRE_LEN), dtype=np.float32) + self.full_features_buffer = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN, ModelConstants.FEATURE_LEN), dtype=np.float32) + self.full_desire = np.zeros((ModelConstants.FULL_HISTORY_BUFFER_LEN + 1, ModelConstants.DESIRE_LEN), dtype=np.float32) # img buffers are managed in openCL transform code self.numpy_inputs = {} @@ -66,7 +66,7 @@ class ModelState: if self.model_runner.is_20hz: num_elements = self.numpy_inputs['features_buffer'].shape[1] step_size = int(-100 / num_elements) - self.full_features_20Hz_idxs = np.arange(step_size, step_size * (num_elements + 1), step_size)[::-1] + self.full_features_buffer_idxs = np.arange(step_size, step_size * (num_elements + 1), step_size)[::-1] self.desire_reshape_dims = (self.numpy_inputs['desire'].shape[0], self.numpy_inputs['desire'].shape[1], -1, self.numpy_inputs['desire'].shape[2]) def run(self, buf: VisionBuf, wbuf: VisionBuf, transform: np.ndarray, transform_wide: np.ndarray, @@ -77,9 +77,9 @@ class ModelState: self.prev_desire[:] = inputs['desire'] if self.model_runner.is_20hz: - self.desire_20Hz[:-1] = self.desire_20Hz[1:] - self.desire_20Hz[-1] = new_desire - self.numpy_inputs['desire'][:] = self.desire_20Hz.reshape(self.desire_reshape_dims).max(axis=2) + self.full_desire[:-1] = self.full_desire[1:] + self.full_desire[-1] = new_desire + self.numpy_inputs['desire'][:] = self.full_desire.reshape(self.desire_reshape_dims).max(axis=2) else: length = inputs['desire'].shape[0] self.numpy_inputs['desire'][0, :-1] = self.numpy_inputs['desire'][0, 1:] @@ -102,9 +102,9 @@ class ModelState: outputs = self.model_runner.run_model() if self.model_runner.is_20hz: - self.full_features_20Hz[:-1] = self.full_features_20Hz[1:] - self.full_features_20Hz[-1] = outputs['hidden_state'][0, :] - self.numpy_inputs['features_buffer'][:] = self.full_features_20Hz[self.full_features_20Hz_idxs] + self.full_features_buffer[:-1] = self.full_features_buffer[1:] + self.full_features_buffer[-1] = outputs['hidden_state'][0, :] + self.numpy_inputs['features_buffer'][:] = self.full_features_buffer[self.full_features_buffer_idxs] else: feature_len = outputs['hidden_state'].shape[1] self.numpy_inputs['features_buffer'][0, :-1] = self.numpy_inputs['features_buffer'][0, 1:]