conform to line length limit

Author: LarsKue

bayesflow/adapters/__init__.py

@@ -1,5 +1,6 @@
 """
-A collection of :py:class:`~bayesflow.adapters.Adapter` transforms, which tell BayesFlow how to interpret your :py:class:`~bayesflow.simulators.Simulator` output and plug it into neural networks for training and inference.
+A collection of :py:class:`~bayesflow.adapters.Adapter` transforms, which tell BayesFlow how to interpret your
+:py:class:`~bayesflow.simulators.Simulator` output and plug it into neural networks for training and inference.
 """
 
 from . import transforms

bayesflow/approximators/__init__.py

@@ -1,5 +1,6 @@
 """
-A collection of :py:class:`~bayesflow.approximators.Approximator`\ s, which embody the inference task and the neural network components used to perform it.
+A collection of :py:class:`~bayesflow.approximators.Approximator`\ s, which embody the inference task and the
+neural network components used to perform it.
 """
 
 from .approximator import Approximator

bayesflow/datasets/__init__.py

@@ -1,5 +1,6 @@
 """
-A collection of `keras.utils.PyDataset <https://keras.io/api/utils/python_utils/#pydataset-class>`__\ s, which wrap your data-generating process (i.e., your :py:class:`~bayesflow.simulators.Simulator`).
+A collection of `keras.utils.PyDataset <https://keras.io/api/utils/python_utils/#pydataset-class>`__\ s, which
+wrap your data-generating process (i.e., your :py:class:`~bayesflow.simulators.Simulator`).
 What type of Dataset you use determines the effective training strategy (e.g., online or offline).
 """
 

bayesflow/metrics/__init__.py

@@ -1,5 +1,6 @@
 """
-A collection of `keras.Metric <https://keras.io/api/metrics/base_metric/#metric-class>`__\ s for evaluating the performance of models.
+A collection of `keras.Metric <https://keras.io/api/metrics/base_metric/#metric-class>`__\ s for evaluating the
+performance of models.
 """
 
 from . import functional

bayesflow/simulators/__init__.py

@@ -1,7 +1,9 @@
 """
-This module provides the :py:class:`~bayesflow.simulators.Simulator`, which is the base implementation of a generative mathematical model, data generating process.
+This module provides the :py:class:`~bayesflow.simulators.Simulator`, which is the base implementation of a
+generative mathematical model, or data generating process.
 Its primary function is to sample data with the :py:meth:`~bayesflow.simulators.Simulator.sample` method.
-The module also contains several other kinds of Simulators, as well as the function :py:func:`~bayesflow.simulators.make_simulator` to facilitate easy implementation.
+The module also contains several other kinds of Simulators, as well as the function
+:py:func:`~bayesflow.simulators.make_simulator` to facilitate easy implementation.
 """
 
 from .sequential_simulator import SequentialSimulator

bayesflow/workflows/__init__.py

@@ -1,5 +1,6 @@
 """
-Provides :py:class:`~bayesflow.workflows.BasicWorkflow`, a high-level interface for working on typical BayesFlow applications without having to worry about the internals.
+Provides :py:class:`~bayesflow.workflows.BasicWorkflow`, a high-level interface for working on typical BayesFlow
+applications without having to worry about the internals.
 """
 
 from .basic_workflow import BasicWorkflow