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  • Unifying integral kernel NO architectures with BaseNO (maybe rename better)
  • Implement FNO based on BaseNO

@dario-coscia dario-coscia added the pr-to-fix Label for PR that needs modification label Feb 9, 2024
@dario-coscia dario-coscia added pr-to-review Label for PR that are ready to been reviewed and removed pr-to-fix Label for PR that needs modification labels Feb 16, 2024
@dario-coscia dario-coscia requested a review from ndem0 February 16, 2024 12:43
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ndem0 commented Feb 16, 2024

Everything fine to me, please just fix the Codacy issues (https://app.codacy.com/gh/mathLab/PINA/pullRequest?prid=13602959)

Comment on lines 38 to 57
:param input_numb_fields: Number of input fields.
:type input_numb_fields: int
:param output_numb_fields: Number of output fields.
:type output_numb_fields: int
:param n_modes: Number of modes.
:type n_modes: int or list[int]
:param dimensions: Number of dimensions (1, 2, or 3).
:type dimensions: int
:param padding: Padding size, defaults to 8.
:type padding: int
:param padding_type: Type of padding, defaults to "constant".
:type padding_type: str
:param inner_size: Inner size, defaults to 20.
:type inner_size: int
:param n_layers: Number of layers, defaults to 2.
:type n_layers: int
:param func: Activation function, defaults to nn.Tanh.
:type func: torch.nn.Module
:param layers: List of layer sizes, defaults to None.
:type layers: list[int]
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for primitive type, use the compact form

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done!

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Everything fine to me, please just fix the Codacy issues (https://app.codacy.com/gh/mathLab/PINA/pullRequest?prid=13602959)

I tried to address as many as I could. The ones remaining are either not solvable (too many arguments in the input) or I do not know how to avoid triggering the codacy error (for example the forward pass one...). Also, I think the test failing on windows is due to the fact that some packages are not correctly installed when using windows...

@dario-coscia dario-coscia self-assigned this Feb 20, 2024
@dario-coscia dario-coscia added the enhancement New feature or request label Feb 20, 2024
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ndem0 commented Feb 21, 2024

Yes, just rebase conflicts after #243 and we're done!

Dario Coscia and others added 4 commits February 21, 2024 11:05
… it better)

* Implement FNO based on BaseNO
* modify doc for FNO and adding for FourierIntegralKernel, NeuralKernelOperator
* adding tests
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Yes, just rebase conflicts after #243 and we're done!

Should be done!

@ndem0 ndem0 merged commit e516e77 into master Feb 21, 2024
@dario-coscia dario-coscia deleted the no branch March 1, 2024 17:32
AleDinve pushed a commit to AleDinve/PINA that referenced this pull request Mar 4, 2024
* Unify integral kernel NO architectures with NeuralKernelOperator
* Implement FNO based on NeuralKernelOperator
* modify doc for FNO and add for FourierIntegralKernel, NeuralKernelOperator
* adding tests

---------

Co-authored-by: Dario Coscia <[email protected]>
Co-authored-by: Dario Coscia <[email protected]>
dario-coscia added a commit that referenced this pull request Mar 12, 2025
* Unify integral kernel NO architectures with NeuralKernelOperator
* Implement FNO based on NeuralKernelOperator
* modify doc for FNO and add for FourierIntegralKernel, NeuralKernelOperator
* adding tests

---------

Co-authored-by: Dario Coscia <[email protected]>
Co-authored-by: Dario Coscia <[email protected]>
dario-coscia added a commit that referenced this pull request Apr 17, 2025
* Unify integral kernel NO architectures with NeuralKernelOperator
* Implement FNO based on NeuralKernelOperator
* modify doc for FNO and add for FourierIntegralKernel, NeuralKernelOperator
* adding tests

---------

Co-authored-by: Dario Coscia <[email protected]>
Co-authored-by: Dario Coscia <[email protected]>
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3 participants