.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "usage_examples/flow/plot_level_gap_flow.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_usage_examples_flow_plot_level_gap_flow.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_usage_examples_flow_plot_level_gap_flow.py:

Skip-Connection Level Spacing
=======================================

``level_gap`` controls the vertical distance in pixels between overlapping skip-connection routes. This
nested residual model creates two detour levels: an inner shortcut around one convolution and an
outer shortcut around the whole block. Compare a compact setting with a more widely spaced one.
The additional rendering options separate the boxes and make the routed lines easier to see.

.. GENERATED FROM PYTHON SOURCE LINES 9-64



.. image-sg:: /usage_examples/flow/images/sphx_glr_plot_level_gap_flow_001.png
   :alt: level_gap=20, level_gap=80
   :srcset: /usage_examples/flow/images/sphx_glr_plot_level_gap_flow_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import matplotlib.pyplot as plt
    import torch
    import visualtorch
    from torch import nn


    class NestedResidualBlock(nn.Module):
        """A residual block with one shortcut nested inside another."""

        def __init__(self, channels: int) -> None:
            super().__init__()
            self.conv1 = nn.Conv2d(channels, channels, kernel_size=3, padding=1)
            self.conv2 = nn.Conv2d(channels, channels, kernel_size=3, padding=1)
            self.inner_relu = nn.ReLU()
            self.conv3 = nn.Conv2d(channels, channels, kernel_size=3, padding=1)
            self.outer_relu = nn.ReLU()

        def forward(self, x: torch.Tensor) -> torch.Tensor:
            """Run the block with overlapping inner and outer shortcuts."""
            outer_identity = x
            x = self.conv1(x)
            inner_identity = x
            x = self.inner_relu(self.conv2(x) + inner_identity)
            x = self.conv3(x)
            return self.outer_relu(x + outer_identity)


    model = NestedResidualBlock(channels=4)
    input_shape = (1, 4, 16, 16)

    level_gaps = (20, 80)
    images = [
        visualtorch.render(
            model,
            input_shape,
            style="flow",
            level_gap=level_gap,
            spacing=25,
            connector_width=2,
        )
        for level_gap in level_gaps
    ]

    dpi = 150  # rendered at 2x this in the final doc build (savefig.dpi=300 in conf.py)
    figure_width = min(12, max(8, sum(img.width for img in images) / dpi))
    figure_height = min(4, max(3, max(img.height for img in images) / dpi))
    _, axes = plt.subplots(1, 2, figsize=(figure_width, figure_height), dpi=dpi)
    for ax, img, level_gap in zip(axes, images, level_gaps, strict=True):
        ax.imshow(img)
        ax.set_title(f"level_gap={level_gap}")
        ax.axis("off")

    plt.tight_layout()
    plt.show()


.. _sphx_glr_download_usage_examples_flow_plot_level_gap_flow.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_level_gap_flow.ipynb <plot_level_gap_flow.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_level_gap_flow.py <plot_level_gap_flow.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_level_gap_flow.zip <plot_level_gap_flow.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_