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change expected features
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@@ -83,11 +83,9 @@ class SARMConfig(PreTrainedConfig):
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encode_on_the_fly: bool = True # Encode images/text during training
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use_dataset_task: bool = True # Use task descriptions from dataset
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use_subtask_annotations: bool = True # Use subtask annotations for stage-aware training if available
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# Features (required by PreTrainedPolicy)
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# Video_features and text_features are generated by the processor from raw images/text, we don't declare them as VISUAL/LANGUAGE here to avoid validation errors
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input_features: dict = field(default_factory=lambda: {
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"video_features": PolicyFeature(shape=(9, 512), type=FeatureType.VISUAL),
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"text_features": PolicyFeature(shape=(384,), type=FeatureType.LANGUAGE),
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"state_features": PolicyFeature(shape=(9, 14), type=FeatureType.STATE) # Example: 7 DOF × 2 arms
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})
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output_features: dict = field(default_factory=lambda: {
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