.. _sphx_glr_auto_examples_06_torch:

Custom parallelproj pytorch layer examples
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How to wrap a parallelproj operator as a differentiable PyTorch layer, with an
autograd-compatible forward and adjoint, so that projectors can be embedded in
deep-learning reconstruction pipelines (e.g. unrolled / model-based networks).


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    <div class="sphx-glr-thumbcontainer" tooltip="In this example, we show how to define a custom pytorch layer that can be used to define a feed forward neural network that includes a parallelproj forward and back backward projections (or any .LinearOperator) that can be used with pytorch&#x27;s autograd engine.">

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  :doc:`/auto_examples/06_torch/01_run_projection_layer`

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   /auto_examples/06_torch/01_run_projection_layer