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update doc

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This commit is contained in:
Dario Coscia
2025-03-17 12:23:26 +01:00
committed by FilippoOlivo
parent ae1fd2680f
commit 480140dd31
33 changed files with 265 additions and 196 deletions
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32
pina/model/fourier_neural_operator.py
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@@ -274,7 +274,7 @@ class FNO(KernelNeuralOperator):
layers=None,
):
"""
param torch.nn.Module lifting_net: The lifting neural network mapping
:param torch.nn.Module lifting_net: The lifting neural network mapping
the input to its hidden dimension.
:param torch.nn.Module projecting_net: The projection neural network
mapping the hidden representation to the output function.
@@ -318,22 +318,24 @@ class FNO(KernelNeuralOperator):
def forward(self, x):
"""
Forward pass for the :class:`FourierNeuralOperator` model.
Forward pass for the :class:`FourierNeuralOperator` model.
The ``lifting_net`` maps the input to the hidden dimension.
Then, several layers of Fourier blocks are applied. Finally, the
``projection_net`` maps the hidden representation to the output
function.
The ``lifting_net`` maps the input to the hidden dimension.
Then, several layers of Fourier blocks are applied. Finally, the
``projection_net`` maps the hidden representation to the output
function.
: param x: The input tensor for performing the computation. Depending
on the ``dimensions`` in the initialization, it expects a tensor
with the following shapes:
* 1D tensors: ``[batch, X, channels]``
* 2D tensors: ``[batch, X, Y, channels]``
* 3D tensors: ``[batch, X, Y, Z, channels]``
:type x: torch.Tensor | LabelTensor
:return: The output tensor.
:rtype: torch.Tensor
:param x: The input tensor for performing the computation. Depending
on the ``dimensions`` in the initialization, it expects a tensor
with the following shapes:
* 1D tensors: ``[batch, X, channels]``
* 2D tensors: ``[batch, X, Y, channels]``
* 3D tensors: ``[batch, X, Y, Z, channels]``
:type x: torch.Tensor | LabelTensor
:return: The output tensor.
:rtype: torch.Tensor
"""
if isinstance(x, LabelTensor):