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Is your feature request related to a problem? Please describe
To clearly define the expected inputs/outputs for a given nn.Module, it would be convenient to create a wrapper class for torch.Tensor that encapsulates shape schema and allows for comparisons
Describe the solution you'd like
Create a class called torcharch.types.TensorShape which is initialized with the tensor dimensionality as well any restrictions on the valid range of values each dimension can take on. This can be useful for several cases
Custom modules should define a valid input/output @property
End users can use this interface to check their work
Schema can also be used to conduct dynamic unit tests
Describe alternatives you've considered
The main alternative would be using the built-in tensor class to define a dummy example. However, this is limiting in that the object can't contain schema information about the acceptable range of values in each dimension
It does not appear that PyTorch includes a class like this currently, although that would be preferable
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe
To clearly define the expected inputs/outputs for a given
nn.Module
, it would be convenient to create a wrapper class fortorch.Tensor
that encapsulates shape schema and allows for comparisonsDescribe the solution you'd like
Create a class called
torcharch.types.TensorShape
which is initialized with the tensor dimensionality as well any restrictions on the valid range of values each dimension can take on. This can be useful for several cases@property
Describe alternatives you've considered
The text was updated successfully, but these errors were encountered: