mirror of https://github.com/hpcaitech/ColossalAI
[chore] remove print
parent
f45f8a2aa7
commit
20701d4533
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@ -19,10 +19,6 @@ class TrainingPhase(Enum):
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logger = DistributedLogger("gemini_hook")
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import os
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rank = int(os.environ["RANK"])
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class GeminiZeROHook(ColoParamOpHook):
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def __init__(self, gemini_manager: GeminiManager) -> None:
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@ -56,23 +52,13 @@ class GeminiZeROHook(ColoParamOpHook):
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# get possible chunks to prefetch
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chunks_fetch_async = self._gemini_manager.placement_policy.get_prefetch_chunks()
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if rank == 0 and not self._gemini_manager.is_warmup():
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print(
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f"compute_id: {self._gemini_manager.compute_idx} self._gemini_manager.compute_list: {self._gemini_manager.compute_list}"
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)
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print(f"{all_chunks=}")
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print(f"accessed_chunks={self._chunk_manager.accessed_chunks}")
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print(f"{chunks_fetch_sync=}")
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print(f"{chunks_fetch_async=}")
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print(f"works={list(self._gemini_manager._async_works.keys())}")
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# prefetch
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for chunk in chunks_fetch_async:
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maybe_work = self._chunk_manager.access_chunk(chunk, async_access=True)
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if maybe_work is not None:
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self._gemini_manager.add_work(chunk, maybe_work)
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if rank == 0 and not self._gemini_manager.is_warmup():
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print(f"post accessed_chunks={self._chunk_manager.accessed_chunks}")
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# record cuda model data of the current OP, including memory for prefetched chunks
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self._gemini_manager.record_model_data_volume()
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