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https://github.com/hpcaitech/ColossalAI.git
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[fix] rm unused comments
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@@ -49,7 +49,6 @@ class ZeroBubbleVPipeScheduler(PipelineSchedule):
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overlap_p2p: bool = True,
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):
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super().__init__(stage_manager)
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# Not support overlap_p2p so far
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# batch info
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self.num_microbatch = num_microbatch
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self.microbatch_size = microbatch_size
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@@ -543,8 +542,6 @@ class ZeroBubbleVPipeScheduler(PipelineSchedule):
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output_obj_grad_ = []
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# For chunk 0 stage 0, use micro_batch as input_obj_; and we don't have to cal microbatch dx.
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# if model_chunk_id == 0 and self.stage_manager.is_first_stage(ignore_chunk=True):
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# return None
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# For loss backward; output_obj is loss; output_obj_grad should be None
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if model_chunk_id == 1 and self.stage_manager.is_first_stage(ignore_chunk=True):
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@@ -718,10 +715,8 @@ class ZeroBubbleVPipeScheduler(PipelineSchedule):
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# Do not release_tensor_data loss, release_tensor_data other output_obj;
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if model_chunk_id == 1 and self.stage_manager.is_first_stage(ignore_chunk=True):
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self.output_tensors[model_chunk_id].append(output_obj)
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# self.output_tensors_dw[model_chunk_id].append(output_obj)
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else:
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self.output_tensors[model_chunk_id].append(output_obj)
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# self.output_tensors_dw[model_chunk_id].append(output_obj)
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# add output to send_fwd_buffer
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if model_chunk_id == 0: # chunk 0
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