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Add torch jit ignore decorator to Lightning properties #3295

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Add torch jit ignore decorator to Lightning properties #3295

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4 changes: 4 additions & 0 deletions pytorch_lightning/core/lightning.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,7 @@ def __init__(self, *args, **kwargs):
self._example_input_array = None
self._datamodule = None

@torch.jit.ignore
@property
def example_input_array(self) -> Any:
return self._example_input_array
Expand All @@ -84,6 +85,7 @@ def example_input_array(self) -> Any:
def example_input_array(self, example: Any) -> None:
self._example_input_array = example

@torch.jit.ignore
@property
def datamodule(self) -> Any:
return self._datamodule
Expand All @@ -92,6 +94,7 @@ def datamodule(self) -> Any:
def datamodule(self, datamodule: Any) -> None:
self._datamodule = datamodule

@torch.jit.ignore
@property
def on_gpu(self):
"""
Expand Down Expand Up @@ -1720,6 +1723,7 @@ def to_onnx(self, file_path: str, input_sample: Optional[Tensor] = None, **kwarg

torch.onnx.export(self, input_data, file_path, **kwargs)

@torch.jit.ignore
@property
def hparams(self) -> Union[AttributeDict, str]:
if not hasattr(self, '_hparams'):
Expand Down
2 changes: 2 additions & 0 deletions pytorch_lightning/utilities/device_dtype_mixin.py
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Expand Up @@ -11,6 +11,7 @@ def __init__(self):
self._dtype = torch.get_default_dtype()
self._device = torch.device('cpu')

@torch.jit.ignore
@property
def dtype(self) -> Union[str, torch.dtype]:
return self._dtype
Expand All @@ -20,6 +21,7 @@ def dtype(self, new_dtype: Union[str, torch.dtype]):
# necessary to avoid infinite recursion
raise RuntimeError('Cannot set the dtype explicitly. Please use module.to(new_dtype).')

@torch.jit.ignore
@property
def device(self) -> Union[str, torch.device]:
return self._device
Expand Down