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loss_scaler.py: patching loss scaler for compatibility with current pytorch
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@@ -51,11 +51,10 @@ class DynamicLossScaler:
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# `x` is a torch.Tensor
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def _has_inf_or_nan(x):
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inf_count = torch.sum(x.abs() == float('inf'))
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if inf_count > 0:
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cpu_sum = float(x.float().sum())
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if cpu_sum == float('inf') or cpu_sum == -float('inf') or cpu_sum != cpu_sum:
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return True
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nan_count = torch.sum(x != x)
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return nan_count > 0
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return False
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# `overflow` is boolean indicating whether we overflowed in gradient
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def update_scale(self, overflow):
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