Fix cumsum for MPS in newer torch
The prior fix assumed that testing int16 was enough to determine if a fix is needed, but a recent fix for cumsum has int16 working but not bool.
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@ -139,8 +139,10 @@ orig_Tensor_cumsum = torch.Tensor.cumsum
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def cumsum_fix(input, cumsum_func, *args, **kwargs):
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if input.device.type == 'mps':
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output_dtype = kwargs.get('dtype', input.dtype)
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if any(output_dtype == broken_dtype for broken_dtype in [torch.bool, torch.int8, torch.int16, torch.int64]):
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if output_dtype == torch.int64:
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return cumsum_func(input.cpu(), *args, **kwargs).to(input.device)
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elif cumsum_needs_bool_fix and output_dtype == torch.bool or cumsum_needs_int_fix and (output_dtype == torch.int8 or output_dtype == torch.int16):
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return cumsum_func(input.to(torch.int32), *args, **kwargs).to(torch.int64)
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return cumsum_func(input, *args, **kwargs)
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@ -151,7 +153,8 @@ if has_mps():
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torch.nn.functional.layer_norm = layer_norm_fix
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torch.Tensor.numpy = numpy_fix
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elif version.parse(torch.__version__) > version.parse("1.13.1"):
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if not torch.Tensor([1,2]).to(torch.device("mps")).equal(torch.Tensor([1,1]).to(torch.device("mps")).cumsum(0, dtype=torch.int16)):
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cumsum_needs_int_fix = not torch.Tensor([1,2]).to(torch.device("mps")).equal(torch.ShortTensor([1,1]).to(torch.device("mps")).cumsum(0))
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cumsum_needs_bool_fix = not torch.BoolTensor([True,True]).to(device=torch.device("mps"), dtype=torch.int64).equal(torch.BoolTensor([True,False]).to(torch.device("mps")).cumsum(0))
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torch.cumsum = lambda input, *args, **kwargs: ( cumsum_fix(input, orig_cumsum, *args, **kwargs) )
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torch.Tensor.cumsum = lambda self, *args, **kwargs: ( cumsum_fix(self, orig_Tensor_cumsum, *args, **kwargs) )
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orig_narrow = torch.narrow
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