class_docstr: Tests correctness of the Y = g(X) = exp(X) / sum(exp(X)) transformation.
class_docstr_tok: ["Tests","correctness","of","the","Y","=","g","(","X",")","=","exp","(","X",")","\/","sum","(","exp","(","X",")",")","transformation","."]
code: def testShapeGettersWithDynamicShape(self):
      x = tf1.placeholder_with_default([2, 4], shape=None)
      y = tf1.placeholder_with_default([2, 5], shape=None)
      bijector = softmax_centered.SoftmaxCentered(validate_args=True)
      self.assertAllEqual(
          [2, 5], self.evaluate(bijector.forward_event_shape_tensor(x))
      )
      self.assertAllEqual(
          [2, 4], self.evaluate(bijector.inverse_event_shape_tensor(y))
      )
  
file_path: probability/tensorflow_probability/python/bijectors/softmax_centered_test.py
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import softmax_centered
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 5 for calling the SoftmaxCenteredBijectorTest obj's underlying member method code with example usage: obj.testShapeGettersWithDynamicShape() without return types