doc(condition): fix incorrect type hints for `torch.Tensor`
@@ -21,9 +21,9 @@ class BaseCondition:
f"""[ABSTRACT METHOD] Re-parameterize output(s) of a network.
:param output_tensor: Output of the neural network.
- :type output_tensor: `torch.nn.Tensor`
+ :type output_tensor: `torch.Tensor`
:param input_tensors: Inputs to the neural network; i.e., sampled coordinates; i.e., independent variables.
- :type input_tensors: tuple[`torch.nn.Tensor`]
+ :type input_tensors: tuple[`torch.Tensor`]
:return: the re-parameterized output of the network
:rtype: `torch.Tensor`
@@ -72,9 +72,9 @@ class EnsembleCondition:
This is useful when solving differential equations with a single, multi-output network.
:param output_tensor: Output of the neural network. Number of units (.shape[1]) must equal number of sub-conditions.
- :type output_tensor: `torch.nn.Tensor`
+ :type output_tensor: `torch.Tensor`
:param input_tensors: Inputs to the neural network; i.e., sampled coordinates; i.e., independent variables.
- :type input_tensors: tuple[`torch.nn.Tensor`]
+ :type input_tensors: tuple[`torch.Tensor`]
:return: The column-wise re-parameterized network output, concatenated across columns so that it's still one tensor.
:rtype: `torch.Tensor`
"""
