docstr: Checks if the is_broadcast_compatible function works as expected.
docstr_tok: ["Checks","if","the","is_broadcast_compatible","function","works","as","expected","."]
code: def test_is_broadcast_compatible(
      self, shape_x, shape_y, broadcastable
  ):
      """Checks if the is_broadcast_compatible function works as expected."""
      if tf.executing_eagerly():
          if (
              shape_x is None
              or shape_y is None
              or None in shape_x
              or None in shape_y
          ):
              return
          shape_x = tf.compat.v1.placeholder_with_default(
              tf.zeros(shape_x, dtype=tf.float32), shape=shape_x
          ).shape
          shape_y = tf.compat.v1.placeholder_with_default(
              tf.zeros(shape_y, dtype=tf.float32), shape=shape_y
          ).shape
      else:
          shape_x = tf.compat.v1.placeholder(
              shape=shape_x, dtype=tf.float32
          ).shape
          shape_y = tf.compat.v1.placeholder(
              shape=shape_y, dtype=tf.float32
          ).shape
  
      self.assertEqual(
          shape.is_broadcast_compatible(shape_x, shape_y), broadcastable
      )
  
file_path: graphics/tensorflow_graphics/util/tests/shape_test.py
imports: from absl.testing import parameterized
  import tensorflow
  from tensorflow_graphics.util import shape
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 1 for calling the ShapeTest obj's underlying member method code with example usage: obj.test_is_broadcast_compatible(shape_x, shape_y, broadcastable) without return types