docstr: Check if the convolution parameters and output have correct shapes.
docstr_tok: ["Check","if","the","convolution","parameters","and","output","have","correct","shapes","."]
code: def test_dynamic_graph_convolution_keras_layer_exception_not_raised_shapes(
      self,
      batch_size,
      num_vertices,
      in_channels,
      out_channels,
      reduction,
  ):
      """Check if the convolution parameters and output have correct shapes."""
      if not tf.executing_eagerly():
          return
      data, neighbors = _dummy_data(
          batch_size, num_vertices, in_channels
      )
      layer = gc_layer.DynamicGraphConvolutionKerasLayer(
          num_output_channels=out_channels, reduction=reduction
      )
  
      try:
          output = layer(inputs=[data, neighbors], sizes=None)
      except Exception as e:  # pylint: disable=broad-except
          self.fail("Exception raised: %s" % str(e))
  
      self.assertAllEqual(
          (batch_size, num_vertices, out_channels), output.shape
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  from six.moves import range
  from six.moves import zip
  import tensorflow
  import tensorflow_graphics.nn.layer.graph_convolution
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 1 for calling the GraphConvolutionTestDynamicGraphConvolutionKerasLayerTests obj's underlying member method code with example usage: obj.test_dynamic_graph_convolution_keras_layer_exception_not_raised_shapes(batch_size, num_vertices, in_channels, out_channels, reduction) without return types