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@ -145,6 +145,8 @@ class AutoPlacementPolicy(PlacementPolicy):
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self._warmup_non_model_data_ratio = warmup_non_model_data_ratio
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self._warmup_non_model_data_ratio = warmup_non_model_data_ratio
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self._steady_cuda_cap_ratio = steady_cuda_cap_ratio
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self._steady_cuda_cap_ratio = steady_cuda_cap_ratio
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self.__avail_cuda_model_data_for_prefetch = None
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def evict_tensors(
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def evict_tensors(
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self,
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self,
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can_evict_chunks: List[Chunk],
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can_evict_chunks: List[Chunk],
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@ -204,6 +206,7 @@ class AutoPlacementPolicy(PlacementPolicy):
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f"Adjust layout failed! No enough CUDA memory! "
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f"Adjust layout failed! No enough CUDA memory! "
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f"Need {to_free_cuda_model_data}, freed {freed_cuda_model_data}"
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f"Need {to_free_cuda_model_data}, freed {freed_cuda_model_data}"
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)
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)
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self.__avail_cuda_model_data_for_prefetch = avail_cuda_model_data - freed_cuda_model_data
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return freed_cuda_model_data, time() - start
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return freed_cuda_model_data, time() - start
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@staticmethod
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@staticmethod
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@ -234,14 +237,9 @@ class AutoPlacementPolicy(PlacementPolicy):
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) -> List[Chunk]:
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) -> List[Chunk]:
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if is_warmup: # no prefetch during warmup since we need compute_list
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if is_warmup: # no prefetch during warmup since we need compute_list
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return []
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return []
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# modified from self.evict_tensors
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cuda_capacity = self._steady_cuda_cap_ratio * colo_device_memory_capacity(
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avail_cuda_model_data = self.__avail_cuda_model_data_for_prefetch
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get_accelerator().get_current_device()
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self.__avail_cuda_model_data_for_prefetch = None # incase of double use
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)
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max_cuda_non_model_data_per_period = self.mem_stats_collector.next_period_non_model_data_usage("cuda")
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used_cuda_model_data = self.chunk_manager.total_mem["cuda"]
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total_cuda_model_data = cuda_capacity - max_cuda_non_model_data_per_period
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avail_cuda_model_data = total_cuda_model_data - used_cuda_model_data
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prefetch_chunk_memory = 0
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prefetch_chunk_memory = 0
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can_prefetch = self.max_prefetch - len(async_works)
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can_prefetch = self.max_prefetch - len(async_works)
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