class_docstr: A simple single-scene dataset based on PyTorch3D renders of a mesh.
  Provides `num_views` renders of the mesh as train, with no val
  and test. The renders are generated from viewpoints sampled at uniformly
  distributed azimuth intervals. The elevation is kept constant so that the
  camera's vertical position coincides with the equator.
  
  By default, uses Keenan Crane's cow model, and the camera locations are
  set to make sense for that.
  
  Although the rendering used to generate this dataset will use a GPU
  if one is available, the data it produces is on the CPU just like
  the data returned by implicitron's other dataset map providers.
  This is because both datasets and models can be large, so implicitron's
  training loop expects data on the CPU and only moves
  what it needs to the device.
  
  For a more detailed explanation of this code, please refer to the
  docs/tutorials/fit_textured_mesh.ipynb notebook.
  
  Members:
      num_views: The number of generated renders.
      data_file: The folder that contains the mesh file. By default, finds
          the cow mesh in the same repo as this code.
      azimuth_range: number of degrees on each side of the start position to
          take samples
      distance: distance from camera centres to the origin.
      resolution: the common height and width of the output images.
      use_point_light: whether to use a particular point light as opposed
          to ambient white.
      gpu_idx: which gpu to use for rendering the mesh.
      path_manager_factory: (Optional) An object that generates an instance of
          PathManager that can translate provided file paths.
      path_manager_factory_class_type: The class type of `path_manager_factory`.
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code: def get_dataset_map(self) -> DatasetMap:
      # pyre-ignore[16]
      return DatasetMap(train=self.train_dataset, val=None, test=None)
  
file_path: pytorch3d/pytorch3d/implicitron/dataset/rendered_mesh_dataset_map_provider.py
imports: from os.path import dirname, join, realpath
  from typing import Optional, Tuple
  import torch
  from pytorch3d.implicitron.tools.config import registry, run_auto_creation
  from pytorch3d.io import IO
  from pytorch3d.renderer import AmbientLights, BlendParams, CamerasBase, FoVPerspectiveCameras, HardPhongShader, look_at_view_transform, MeshRasterizer, MeshRendererWithFragments, PointLights, RasterizationSettings
  from pytorch3d.structures.meshes import Meshes
  from .dataset_map_provider import DatasetMap, DatasetMapProviderBase, PathManagerFactory
  from .single_sequence_dataset import SingleSceneDataset
  from .utils import DATASET_TYPE_KNOWN
label_desc: Use image node_id 1 for calling the RenderedMeshDatasetMapProvider obj's underlying member method code with example usage: obj.get_dataset_map() and returns: DatasetMap