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Fix: drop reconstructed conditioning frame in action-conditioned autoregressive concat #151

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Fix: drop reconstructed conditioning frame in action-conditioned autoregressive concat #151

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4 changes: 3 additions & 1 deletion cosmos_predict2/_src/predict2/action/inference/inference.py
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Original file line number Diff line number Diff line change
Expand Up @@ -360,7 +360,9 @@ def main():
if args.single_chunk:
break

chunk_list = [chunk_video[0]] + [chunk_video[i][: args.chunk_size] for i in range(1, len(chunk_video))]
# Drop the first frame of each subsequent chunk: it is the reconstructed
# conditioning frame (~ previous chunk's last frame) and would otherwise duplicate.
chunk_list = [chunk_video[0]] + [chunk_video[i][1:] for i in range(1, len(chunk_video))]
chunk_video = np.concatenate(chunk_list, axis=0)
if args.single_chunk:
chunk_video_name = f"{args.save_root}/{img_name + '_single_chunk.mp4'}"
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4 changes: 3 additions & 1 deletion cosmos_predict2/_src/predict2/action/inference/inference_gr00t.py
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Original file line number Diff line number Diff line change
Expand Up @@ -337,7 +337,9 @@ def main():
if args.single_chunk:
break

chunk_list = [chunk_video[0]] + [chunk_video[i][: args.chunk_size] for i in range(1, len(chunk_video))]
# Drop the first frame of each subsequent chunk: it is the reconstructed
# conditioning frame (~ previous chunk's last frame) and would otherwise duplicate.
chunk_list = [chunk_video[0]] + [chunk_video[i][1:] for i in range(1, len(chunk_video))]
chunk_video = np.concatenate(chunk_list, axis=0)
if args.single_chunk:
chunk_video_name = f"{args.save_root}/{img_name + '_single_chunk.mp4'}"
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6 changes: 3 additions & 3 deletions cosmos_predict2/action_conditioned.py
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Original file line number Diff line number Diff line change
Expand Up @@ -358,9 +358,9 @@ def inference(
if inference_args.single_chunk:
break

chunk_list = [chunk_video[0]] + [
chunk_video[i][: inference_args.chunk_size] for i in range(1, len(chunk_video))
]
# Drop the first frame of each subsequent chunk: it is the reconstructed
# conditioning frame (~ previous chunk's last frame) and would otherwise duplicate.
chunk_list = [chunk_video[0]] + [chunk_video[i][1:] for i in range(1, len(chunk_video))]
chunk_video = np.concatenate(chunk_list, axis=0)
if inference_args.single_chunk:
chunk_video_name = str(inference_args.save_root / f"{img_name}_single_chunk.mp4")
Expand Down