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Add compatibility with skip_memory_metrics for mps device (#29264)
* Add compatibility with mps device * fix * typo and style
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@ -526,6 +526,8 @@ class TrainerMemoryTracker:
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elif is_torch_npu_available():
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self.torch.npu.reset_peak_memory_stats()
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self.torch.npu.empty_cache()
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elif is_torch_mps_available():
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self.torch.mps.empty_cache()
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# gpu
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if self.torch is not None:
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@ -535,6 +537,8 @@ class TrainerMemoryTracker:
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self.gpu_mem_used_at_start = self.torch.xpu.memory_allocated()
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elif is_torch_npu_available():
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self.gpu_mem_used_at_start = self.torch.npu.memory_allocated()
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elif is_torch_mps_available():
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self.gpu_mem_used_at_start = self.torch.mps.current_allocated_memory()
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# cpu
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self.cpu_mem_used_at_start = self.cpu_mem_used()
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@ -564,6 +568,8 @@ class TrainerMemoryTracker:
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self.torch.xpu.empty_cache()
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elif is_torch_npu_available():
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self.torch.npu.empty_cache()
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elif is_torch_mps_available():
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self.torch.mps.empty_cache()
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# concepts:
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# - alloc_delta: the difference of allocated memory between the end and the start
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@ -581,6 +587,11 @@ class TrainerMemoryTracker:
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elif is_torch_npu_available():
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self.gpu_mem_used_now = self.torch.npu.memory_allocated()
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self.gpu_mem_used_peak = self.torch.npu.max_memory_allocated()
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elif is_torch_mps_available():
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self.gpu_mem_used_now = self.torch.mps.current_allocated_memory()
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# self.torch.mps.max_memory_allocated() does not exist yet
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self.gpu_mem_used_peak = None
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else:
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raise ValueError("No available GPU device found!")
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@ -588,8 +599,11 @@ class TrainerMemoryTracker:
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"begin": self.gpu_mem_used_at_start,
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"end": self.gpu_mem_used_now,
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"alloc": (self.gpu_mem_used_now - self.gpu_mem_used_at_start),
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"peaked": max(0, self.gpu_mem_used_peak - self.gpu_mem_used_now),
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}
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if self.gpu_mem_used_peak is not None:
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self.gpu[self.cur_stage]["peaked"] = max(0, self.gpu_mem_used_peak - self.gpu_mem_used_now)
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else:
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self.gpu[self.cur_stage]["peaked"] = "Not available"
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# cpu
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self.cpu_mem_used_now = self.cpu_mem_used()
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