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Refactor model input shaping and indexing logic.

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Introduce dynamic reshaping for 'desire' inputs and improve indexing for 'features_buffer' to enhance maintainability and clarity. These changes reduce hardcoding and make the code more adaptable to varying input dimensions.
This commit is contained in:
DevTekVE
2025-01-06 10:42:52 +01:00
parent 2be0e84e9f
commit bd3117f5d1
1 changed files with 10 additions and 3 deletions
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sunnypilot/modeld/modeld.py
+10 -3
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@@ -69,6 +69,14 @@ class ModelState:
for k,v in self.inputs.items():
self.model.addInput(k, v)
num_elements = model_metadata['input_shapes']['features_buffer'][1]
step_size = int(-100 / num_elements)
self.feature_buffer_idxs = np.arange(step_size, step_size * (num_elements + 1), step_size)[::-1]
desired_shape = self.inputs['desire'].shape[1]
middle_dim = int(self.desire_20Hz.shape[0] / desired_shape)
self.desire_reshape_dims = (desired_shape, middle_dim, -1)
def slice_outputs(self, model_outputs: np.ndarray) -> dict[str, np.ndarray]:
parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in self.output_slices.items()}
if SEND_RAW_PRED:
@@ -84,7 +92,7 @@ class ModelState:
self.desire_20Hz[:-1] = self.desire_20Hz[1:]
self.desire_20Hz[-1] = new_desire
self.inputs['desire'][:] = self.desire_20Hz.reshape((25,4,-1)).max(axis=1).flatten()
self.inputs['desire'][:] = self.desire_20Hz.reshape(self.desire_reshape_dims).max(axis=1).flatten()
self.inputs['traffic_convention'][:] = inputs['traffic_convention']
@@ -100,8 +108,7 @@ class ModelState:
self.full_features_20Hz[:-1] = self.full_features_20Hz[1:]
self.full_features_20Hz[-1] = outputs['hidden_state'][0, :]
idxs = np.arange(-4,-100,-4)[::-1]
self.inputs['features_buffer'][:] = self.full_features_20Hz[idxs].flatten()
self.inputs['features_buffer'][:] = self.full_features_20Hz[self.feature_buffer_idxs].flatten()
return outputs