class_docstr: A light object representing the same color of light everywhere.
  By default, this is white, which effectively means lighting is
  not used in rendering.
  
  Unlike other lights this supports an arbitrary number of channels, not just 3 for RGB.
  The ambient_color input determines the number of channels.
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docstr: If ambient_color is provided, it should be a sequence of
  triples of floats.
  
  Args:
      ambient_color: RGB color
      device: Device (as str or torch.device) on which the tensors should be located
  
  The ambient_color if provided, should be
      - tuple/list of C-element tuples of floats
      - torch tensor of shape (1, C)
      - torch tensor of shape (N, C)
  where C is the number of channels and N is batch size.
  For RGB, C is 3.
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code: def __init__(
      self, *, ambient_color=None, device: Device = "cpu"
  ) -> None:
      """
      If ambient_color is provided, it should be a sequence of
      triples of floats.
  
      Args:
          ambient_color: RGB color
          device: Device (as str or torch.device) on which the tensors should be located
  
      The ambient_color if provided, should be
          - tuple/list of C-element tuples of floats
          - torch tensor of shape (1, C)
          - torch tensor of shape (N, C)
      where C is the number of channels and N is batch size.
      For RGB, C is 3.
      """
      if ambient_color is None:
          ambient_color = ((1.0, 1.0, 1.0),)
      super().__init__(ambient_color=ambient_color, device=device)
  
imports: import torch
  import torch.nn.functional
  from ..common.datatypes import Device
  from .utils import convert_to_tensors_and_broadcast, TensorProperties
label_desc: Use image node_id 1 to create a new AmbientLights object from inherited base classes: TensorProperties with example: obj = AmbientLights()