code: def create_rasterizer_inputs(batch_shape):
      """Creates random inputs for rasterization tests with given batch shape."""
      image_height = random.randint(3, 5)
      image_width = random.randint(6, 9)
      num_attributes1 = 4
      num_attributes2 = 11
  
      # Create vertices.
      vertices = np.array(
          ((0.0, -4.0, 1.0), (-4.0, 0.0, 1.0), (0.0, 4, 1.0)),
          np.float32,
      )
      vertices = set_batch_shape(vertices, batch_shape)
  
      # Create attributes dictionary.
      attributes1 = np.random.uniform(
          -1.0, 1.0, (3, num_attributes1)
      ).astype(np.float32)
      attributes1 = set_batch_shape(attributes1, batch_shape)
      attributes2 = np.random.uniform(
          -1.0, 1.0, (3, num_attributes2)
      ).astype(np.float32)
      attributes2 = set_batch_shape(attributes2, batch_shape)
  
      attributes_dictionary = {}
      attributes_dictionary["attribute1"] = attributes1
      attributes_dictionary["attribute2"] = attributes2
      triangles = np.array(((0, 1, 2),), np.int32)
  
      # Construct the view projection matrix.
      model_to_eye_matrix = make_look_at_matrix(
          look_at_point=(0.0, 0.0, 1.0)
      )
      model_to_eye_matrix = set_batch_shape(
          model_to_eye_matrix, batch_shape
      )
      perspective_matrix = make_perspective_matrix(
          image_width, image_height
      )
      perspective_matrix = set_batch_shape(
          perspective_matrix, batch_shape
      )
      view_projection_matrix = tf.linalg.matmul(
          perspective_matrix, model_to_eye_matrix
      )
  
      return (
          vertices,
          triangles,
          attributes_dictionary,
          model_to_eye_matrix,
          perspective_matrix,
          view_projection_matrix,
          image_height,
          image_width,
      )
  
file_path: graphics/tensorflow_graphics/rendering/tests/rasterization_test_utils.py
imports: import os
  import random
  import numpy
  import tensorflow
  from tensorflow_graphics.geometry.transformation import look_at
  from tensorflow_graphics.rendering.camera import perspective
  from tensorflow_graphics.util import shape
label_desc: Use image node_id 7 for calling a global function with example usage: create_rasterizer_inputs(batch_shape) and returns: vertices,  triangles,  attributes_dictionary,  model_to_eye_matrix,  perspective_matrix,  view_projection_matrix,  image_height,  image_width