docstr: Tests the upsampling with a zero kernel.
docstr_tok: ["Tests","the","upsampling","with","a","zero","kernel","."]
code: def test_upsample_transposed_convolution_zero_kernel(
      self, num_vertices, num_features, kernel_size, data_type
  ):
      """Tests the upsampling with a zero kernel."""
      data = np.random.uniform(
          size=(num_vertices, num_features)
      ).astype(data_type)
      pool_map = np.zeros(
          shape=(num_vertices, num_vertices * kernel_size),
          dtype=data_type,
      )
      for i in range(num_vertices):
          pool_map[
              i, np.arange(kernel_size * i, kernel_size * (i + 1))
          ] = (1.0 / kernel_size)
      pool_map = _dense_to_sparse(pool_map)
  
      # Transposed convolution op with a zero kernel.
      transposed_convolution_op = tf.keras.layers.Conv2DTranspose(
          filters=num_features,
          kernel_size=(1, kernel_size),
          strides=(1, kernel_size),
          padding="valid",
          use_bias=False,
          kernel_initializer="zeros",
      )
  
      upsampled = gp.upsample_transposed_convolution(
          data,
          pool_map,
          sizes=None,
          kernel_size=kernel_size,
          transposed_convolution_op=transposed_convolution_op,
      )
  
      # Initializes variables of the transpose conv layer.
      self.evaluate(tf.compat.v1.global_variables_initializer())
  
      self.assertAllEqual(
          tf.shape(input=upsampled),
          (num_vertices * kernel_size, num_features),
      )
      self.assertAllEqual(upsampled, tf.zeros_like(upsampled))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  from absl.testing import parameterized
  import numpy
  from six.moves import range
  import tensorflow
  import tensorflow_graphics.geometry.convolution.graph_pooling
  from tensorflow_graphics.geometry.convolution.tests import utils_test
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 4 for calling the GraphPoolingUpsampleTransposeConvolutionTests obj's underlying member method code with example usage: obj.test_upsample_transposed_convolution_zero_kernel(num_vertices, num_features, kernel_size, data_type) without return types