:param: color (bn, 3, h, w) :param: wi (*, *, 3, h, w), supposed to be normalized :param: wo (*, *, 3, h, w), supposed to be normalized

:param: roughness/metallic (bn, 1, h, w) :param: wi (*, *, 3, h, w), supposed to be normalized :param: wo (*, *, 3, h, w), supposed to be

:param: color (bn, 3, h, w) :param: roughness/metallic (bn, 1, h, w) :param: wi (*, *, 3, h, w), supposed to be normalized :param: wo

Generate Albedo, Rough, Metallic and Normal properties from a given text prompt.

r""" Function invoked when calling the pipeline for generation. Args: prompt (`str` or `List[str]`, *optional*):

Transforms the elements of a dictionary according to the transform table. :param x_dict: The input dictionary :return: The tr

Flips the normals accordingly

Transforms the range of tensor. :param x: The input tensor :return: The transformed tensor

Render according to material, normal and lighting conditions Params: model: NeRF model to predict lights im,

Inverse transforms the elements of a dictionary according to the transform table. :param x_dict: The transformed dictionary :

Checks whether the stage referes to a training stage or not :return: True if the stage is Training or Validation

:param: sample (bn, spp, 3, h, w) :param: roughness (bn, 1, 1, h, w) :param: wi (*, *, 3, h, w), supposed to be normalized :return: w

:param: sample (bn, spp, 3, h, w) :param: roughness (bn, 1, h, w) :param: wi (*, *, 3, h, w), supposed to be normalized :return: wo (

:param: sample (bn, spp, 2, h, w) :param: roughness (bn, 1, h, w) :param: wi (*, *, 3, h, w), supposed to be normalized :return: wo (