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

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

.. _sphx_glr_usage_examples_flow_plot_higher_resolution_flow.py:

Higher Resolution
=======================================

``flow_view``'s box size has two independent levers: ``scale_xy`` scales each box's spatial
(width/height) extent, and ``scale_z`` scales its depth (channel count). Both are clamped by
``min_xy``/``max_xy`` and ``min_z``/``max_z`` - if a box's computed size is already sitting at one
of those floors, raising the corresponding scale won't visibly change anything until it pushes
past that floor. With the defaults (``min_z=10``, ``scale_z=0.1``), any layer with fewer than 100
channels is already clamped to the same minimum depth - so bumping ``scale_z`` alone may look like
it did nothing unless you push it far enough to clear that floor.

Conv2d is orange, BatchNorm2d is green, and ReLU is sky blue.

.. GENERATED FROM PYTHON SOURCE LINES 14-54

.. code-block:: Python


    from collections import defaultdict

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


    class ResidualBlock(nn.Module):
        """A classic ResNet-style block with a plain identity shortcut."""

        def __init__(self, channels: int) -> None:
            super().__init__()
            self.conv1 = nn.Conv2d(channels, channels, kernel_size=3, padding=1)
            self.bn1 = nn.BatchNorm2d(channels)
            self.relu = nn.ReLU()
            self.conv2 = nn.Conv2d(channels, channels, kernel_size=3, padding=1)
            self.bn2 = nn.BatchNorm2d(channels)

        def forward(self, x: torch.Tensor) -> torch.Tensor:
            """Define the forward pass, with a skip connection around conv1/bn1/relu/conv2/bn2."""
            identity = x
            out = self.relu(self.bn1(self.conv1(x)))
            out = self.bn2(self.conv2(out))
            out = out + identity
            return self.relu(out)


    model = ResidualBlock(channels=8)

    input_shape = (1, 8, 16, 16)

    color_map: dict = defaultdict(dict)
    color_map[nn.Conv2d]["fill"] = "#E69F00"
    color_map[nn.BatchNorm2d]["fill"] = "#009E73"
    color_map[nn.ReLU]["fill"] = "#56B4E9"

    dpi = 150  # rendered at 2x this in the final doc build (savefig.dpi=300 in conf.py)








.. GENERATED FROM PYTHON SOURCE LINES 55-59

Default
-------
At the default ``scale_xy=1`` and ``scale_z=0.1``, this 8-channel model's boxes are already
clamped to the smallest allowed depth (``min_z=10``).

.. GENERATED FROM PYTHON SOURCE LINES 59-68

.. code-block:: Python


    img_default = visualtorch.render(model, input_shape, style="flow", color_map=color_map, legend=True)

    plt.figure(figsize=(img_default.width / dpi, img_default.height / dpi), dpi=dpi)
    plt.imshow(img_default)
    plt.axis("off")
    plt.tight_layout()
    plt.show()




.. image-sg:: /usage_examples/flow/images/sphx_glr_plot_higher_resolution_flow_001.png
   :alt: plot higher resolution flow
   :srcset: /usage_examples/flow/images/sphx_glr_plot_higher_resolution_flow_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 69-74

Higher Resolution
-----------------
``scale_xy=3`` grows the spatial extent immediately. ``scale_z=3`` needs to clear
``min_z / channels`` (here ``10 / 8``) before it visibly changes the depth at all - past that
point, both dimensions scale up together for a substantially bigger result.

.. GENERATED FROM PYTHON SOURCE LINES 74-90

.. code-block:: Python


    img_hires = visualtorch.render(
        model,
        input_shape,
        style="flow",
        color_map=color_map,
        legend=True,
        scale_xy=3,
        scale_z=3,
    )

    plt.figure(figsize=(img_hires.width / dpi, img_hires.height / dpi), dpi=dpi)
    plt.imshow(img_hires)
    plt.axis("off")
    plt.tight_layout()
    plt.show()



.. image-sg:: /usage_examples/flow/images/sphx_glr_plot_higher_resolution_flow_002.png
   :alt: plot higher resolution flow
   :srcset: /usage_examples/flow/images/sphx_glr_plot_higher_resolution_flow_002.png
   :class: sphx-glr-single-img






.. _sphx_glr_download_usage_examples_flow_plot_higher_resolution_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_higher_resolution_flow.ipynb <plot_higher_resolution_flow.ipynb>`

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

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

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

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


.. only:: html

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

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