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Fix Codacy Warnings (#477)

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Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
Filippo Olivo
2025-03-10 15:38:45 +01:00
committed by Nicola Demo
parent e3790e049a
commit 4177bfbb50
157 changed files with 3473 additions and 3839 deletions
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39
pina/model/block/spectral.py
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@@ -1,7 +1,10 @@
"""
TODO: Add title.
"""
import torch
import torch.nn as nn
from torch import nn
from ...utils import check_consistency
import warnings
######## 1D Spectral Convolution ###########
@@ -13,7 +16,8 @@ class SpectralConvBlock1D(nn.Module):
def __init__(self, input_numb_fields, output_numb_fields, n_modes):
"""
The module computes the spectral convolution of the input with a linear kernel in the
The module computes the spectral convolution of the input with a linear
kernel in the
fourier space, and then it maps the input back to the physical
space.
@@ -106,17 +110,20 @@ class SpectralConvBlock2D(nn.Module):
def __init__(self, input_numb_fields, output_numb_fields, n_modes):
"""
The module computes the spectral convolution of the input with a linear kernel in the
The module computes the spectral convolution of the input with a linear
kernel in the
fourier space, and then it maps the input back to the physical
space.
The block expects an input of size ``[batch, input_numb_fields, Nx, Ny]``
The block expects an input of size
``[batch, input_numb_fields, Nx, Ny]``
and returns an output of size ``[batch, output_numb_fields, Nx, Ny]``.
:param int input_numb_fields: The number of channels for the input.
:param int output_numb_fields: The number of channels for the output.
:param list | tuple n_modes: Number of modes to select for each dimension.
It must be at most equal to the ``floor(Nx/2)+1`` and ``floor(Ny/2)+1``.
:param list | tuple n_modes: Number of modes to select for each
dimension. It must be at most equal to the ``floor(Nx/2)+1`` and
``floor(Ny/2)+1``.
"""
super().__init__()
@@ -234,18 +241,21 @@ class SpectralConvBlock3D(nn.Module):
def __init__(self, input_numb_fields, output_numb_fields, n_modes):
"""
The module computes the spectral convolution of the input with a linear kernel in the
The module computes the spectral convolution of the input with a
linear kernel in the
fourier space, and then it maps the input back to the physical
space.
The block expects an input of size ``[batch, input_numb_fields, Nx, Ny, Nz]``
and returns an output of size ``[batch, output_numb_fields, Nx, Ny, Nz]``.
The block expects an input of size
``[batch, input_numb_fields, Nx, Ny, Nz]``
and returns an output of size
``[batch, output_numb_fields, Nx, Ny, Nz]``.
:param int input_numb_fields: The number of channels for the input.
:param int output_numb_fields: The number of channels for the output.
:param list | tuple n_modes: Number of modes to select for each dimension.
It must be at most equal to the ``floor(Nx/2)+1``, ``floor(Ny/2)+1``
and ``floor(Nz/2)+1``.
:param list | tuple n_modes: Number of modes to select for each
dimension. It must be at most equal to the ``floor(Nx/2)+1``,
``floor(Ny/2)+1`` and ``floor(Nz/2)+1``.
"""
super().__init__()
@@ -347,7 +357,8 @@ class SpectralConvBlock3D(nn.Module):
``[batch, input_numb_fields, x, y, z]``.
:type x: torch.Tensor
:return: The output tensor obtained from the
spectral convolution of size ``[batch, output_numb_fields, x, y, z]``.
spectral convolution of size
``[batch, output_numb_fields, x, y, z]``.
:rtype: torch.Tensor
"""