torchdrivesim.rendering.nvdiffrast
==================================

.. py:module:: torchdrivesim.rendering.nvdiffrast

.. autoapi-nested-parse::

   Nvdiffrast-based renderers, equivalent to those based on PyTorch3D but sometimes faster.
   This module imports correctly if nvdiffrast is missing, but the renderer will raise the NvdiffrastNotFound exception.



Attributes
----------

.. autoapisummary::

   torchdrivesim.rendering.nvdiffrast.is_available
   torchdrivesim.rendering.nvdiffrast.logger
   torchdrivesim.rendering.nvdiffrast.glctx_sessions


Exceptions
----------

.. autoapisummary::

   torchdrivesim.rendering.nvdiffrast.NvdiffrastNotFound


Classes
-------

.. autoapisummary::

   torchdrivesim.rendering.nvdiffrast.NvdiffrastRendererConfig
   torchdrivesim.rendering.nvdiffrast.NvdiffrastRenderer


Functions
---------

.. autoapisummary::

   torchdrivesim.rendering.nvdiffrast.get_glctx_session


Module Contents
---------------

.. py:data:: is_available
   :value: True


.. py:data:: logger

.. py:data:: glctx_sessions

.. py:exception:: NvdiffrastNotFound

   Bases: :py:obj:`ImportError`


   Nvdiffrast is not installed.


.. py:function:: get_glctx_session(device, opengl=True)

.. py:class:: NvdiffrastRendererConfig

   Bases: :py:obj:`torchdrivesim.rendering.base.RendererConfig`


   Configuration of nvdiffrast-based renderer.


   .. py:attribute:: backend
      :type:  str
      :value: 'nvdiffrast'



   .. py:attribute:: antialias
      :type:  bool
      :value: False



   .. py:attribute:: opengl
      :type:  bool
      :value: False



   .. py:attribute:: max_minibatch_size
      :type:  Optional[int]
      :value: None



.. py:class:: NvdiffrastRenderer(cfg: NvdiffrastRendererConfig, *args, **kwargs)

   Bases: :py:obj:`torchdrivesim.rendering.base.BirdviewRenderer`


   Similar to PyTorch3DRenderer, and producing indistinguishable images, but sometimes faster.
   Note that nvdiffrast requires separate installation and is subject to its own license terms.


   .. py:method:: render_mesh(mesh: torchdrivesim.mesh.BirdviewMesh, res: torchdrivesim.utils.Resolution, cameras: torchdrivesim.rendering.base.Cameras) -> torch.Tensor

      Renders a given mesh, producing BxHxWxC tensor image of float RGB values in [0,255] range.