Fix rendering and codacy

This commit is contained in:
FilippoOlivo
2025-03-14 15:05:16 +01:00
committed by Nicola Demo
parent 05105dd517
commit 001d1fc9cf
8 changed files with 98 additions and 96 deletions

View File

@@ -244,7 +244,7 @@ class PinaSampler:
class PinaDataModule(LightningDataModule):
"""
This class extends :class:`lightning.pytorch.LightningDataModule`,
This class extends :class:`~lightning.pytorch.core.LightningDataModule`,
allowing proper creation and management of different types of datasets
defined in PINA.
"""
@@ -268,24 +268,24 @@ class PinaDataModule(LightningDataModule):
:param AbstractProblem problem: The problem containing the data on which
to create the datasets and dataloaders.
:param float train_size: Fraction of elements in the training split. It
must be in the range [0, 1].
must be in the range [0, 1].
:param float test_size: Fraction of elements in the test split. It must
be in the range [0, 1].
be in the range [0, 1].
:param float val_size: Fraction of elements in the validation split. It
must be in the range [0, 1].
must be in the range [0, 1].
:param batch_size: The batch size used for training. If ``None``, the
entire dataset is returned in a single batch.
:type batch_size: int | None
entire dataset is returned in a single batch. Default is ``None``.
:type batch_size: int
:param bool shuffle: Whether to shuffle the dataset before splitting.
Default True.
Default ``Tru``e.
:param bool repeat: Whether to repeat the dataset indefinitely.
Default False.
Default ``False``.
:param automatic_batching: Whether to enable automatic batching.
Default False.
Default ``False``.
:param int num_workers: Number of worker threads for data loading.
Default 0 (serial loading).
Default ``0`` (serial loading).
:param bool pin_memory: Whether to use pinned memory for faster data
transfer to GPU. Default False.
transfer to GPU. Default ``False``.
:raises ValueError: If at least one of the splits is negative.
:raises ValueError: If the sum of the splits is different from 1.
@@ -643,7 +643,7 @@ class PinaDataModule(LightningDataModule):
Return all the input points coming from all the datasets.
:return: The input points for training.
:rtype dict
:rtype: dict
"""
to_return = {}