.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "usage_examples/graph/plot_show_arrows.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_graph_plot_show_arrows.py>`
        to download the full example code.

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

.. _sphx_glr_usage_examples_graph_plot_show_arrows.py:

Connector Arrowheads
=======================================

When a graph has skip connections (e.g. a residual block), plain connector lines can
cross each other with no visual cue about data-flow direction. Setting
``show_arrows=True`` draws a small arrowhead at each connector's downstream endpoint.

The model here is a compact residual block: a main path through two hidden layers plus
a skip connection from the stem output into the merge point before the final layer.

.. GENERATED FROM PYTHON SOURCE LINES 11-47



.. image-sg:: /usage_examples/graph/images/sphx_glr_plot_show_arrows_001.png
   :alt: plot show arrows
   :srcset: /usage_examples/graph/images/sphx_glr_plot_show_arrows_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


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


    class ResidualBlock(nn.Module):
        """A dense residual block with a skip connection around fc1/fc2."""

        def __init__(self) -> None:
            super().__init__()
            self.stem = nn.Linear(4, 4)
            self.fc1 = nn.Linear(4, 4)
            self.fc2 = nn.Linear(4, 4)
            self.out = nn.Linear(4, 2)

        def forward(self, x: torch.Tensor) -> torch.Tensor:
            """Forward pass with a skip connection around fc1/fc2."""
            stem_out = self.stem(x)
            branch = self.fc2(self.fc1(stem_out))
            merged = branch + stem_out
            return self.out(merged)


    model = ResidualBlock()
    input_shape = (1, 4)

    img = visualtorch.render(model, input_shape, style="graph", show_neurons=False, show_arrows=True, layer_spacing=80)

    dpi = 150  # rendered at 2x this in the final doc build (savefig.dpi=300 in conf.py)
    plt.figure(figsize=(img.width / dpi, img.height / dpi), dpi=dpi)
    plt.imshow(img)
    plt.axis("off")
    plt.tight_layout()
    plt.show()


.. _sphx_glr_download_usage_examples_graph_plot_show_arrows.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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