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fix: torch.Tensor.to frontend failing with certain arg/kwarg combinations #28477

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merged 1 commit into from
Mar 5, 2024
Merged

fix: torch.Tensor.to frontend failing with certain arg/kwarg combinations #28477

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85 changes: 37 additions & 48 deletions ivy/functional/frontends/torch/tensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -563,36 +563,27 @@ def new_zeros(
)

def to(self, *args, **kwargs):
if len(args) > 0:
if hasattr(args[0], "ivy_array") or ivy.is_array(args[0]):
if self.dtype == ivy.dtype(args[0]) and self.device == ivy.dev(args[0]):
return self
else:
cast_tensor = self.clone()
cast_tensor.ivy_array = ivy.asarray(
self.ivy_array,
dtype=ivy.dtype(args[0]),
device=ivy.dev(args[0]),
)
return cast_tensor
if (
isinstance(args[0], ivy.NativeDtype)
or isinstance(args[0], ivy.Dtype)
and hasattr(args[0], "as_native_dtype")
or args[0] in ivy._all_ivy_dtypes_str
device = None
dtype = None

# look for device and dtype in the args
for arg in args:
if hasattr(arg, "ivy_array") or ivy.is_array(arg):
device = ivy.dev(arg)
dtype = ivy.dtype(arg)
elif (
isinstance(arg, ivy.NativeDtype)
or isinstance(arg, ivy.Dtype)
and hasattr(arg, "as_native_dtype")
or arg in ivy._all_ivy_dtypes_str
):
if self.dtype == ivy.as_ivy_dtype(args[0]):
return self
else:
cast_tensor = self.clone()
cast_tensor.ivy_array = ivy.asarray(self.ivy_array, dtype=args[0])
return cast_tensor
if isinstance(args[0], (ivy.Device, ivy.NativeDevice, str)):
if isinstance(args[0], str) and not isinstance(
args[0], (ivy.Device, ivy.NativeDevice)
dtype = arg
elif isinstance(arg, (ivy.Device, ivy.NativeDevice, str)):
if isinstance(arg, str) and not isinstance(
arg, (ivy.Device, ivy.NativeDevice)
):
ivy.utils.assertions.check_elem_in_list(
args[0],
arg,
[
"cpu",
"cuda",
Expand All @@ -613,28 +604,26 @@ def to(self, *args, **kwargs):
"hpu",
],
)
if self.device == ivy.as_ivy_dev(args[0]):
return self
else:
cast_tensor = self.clone()
cast_tensor.ivy_array = ivy.asarray(self.ivy_array, device=args[0])
return cast_tensor
device = arg

# look for device and dtype in the kwargs
if "device" in kwargs:
device = kwargs["device"]
if "dtype" in kwargs:
dtype = kwargs["dtype"]

if (dtype is None or self.dtype == dtype) and (
device is None or self.device == ivy.as_ivy_dev(device)
):
return self
else:
if (
"dtype" in kwargs
and "device" in kwargs
and self.dtype == kwargs["dtype"]
and self.device == kwargs["device"]
):
return self
else:
cast_tensor = self.clone()
cast_tensor.ivy_array = ivy.asarray(
self.ivy_array,
device=kwargs["device"] if "device" in kwargs else self.device,
dtype=kwargs["dtype"] if "dtype" in kwargs else self.dtype,
)
return cast_tensor
cast_tensor = self.clone()
cast_tensor.ivy_array = ivy.asarray(
self.ivy_array,
dtype=dtype,
device=device,
)
return cast_tensor

@with_unsupported_dtypes({"2.2 and below": ("float16",)}, "torch")
def acos(self):
Expand Down
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