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 testShapeGetersWithBatchShape(self):
      x = tf.TensorShape([2, 4])
      y = tf.TensorShape([2, 5])
      bijector = softmax_centered.SoftmaxCentered(validate_args=True)
      self.assertAllEqual(y, bijector.forward_event_shape(x))
      self.assertAllEqual(
          tensorshape_util.as_list(y),
          self.evaluate(
              bijector.forward_event_shape_tensor(
                  tensorshape_util.as_list(x)
              )
          ),
      )
      self.assertAllEqual(x, bijector.inverse_event_shape(y))
      self.assertAllEqual(
          tensorshape_util.as_list(x),
          self.evaluate(
              bijector.inverse_event_shape_tensor(
                  tensorshape_util.as_list(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 4 for calling the SoftmaxCenteredBijectorTest obj's underlying member method code with example usage: obj.testShapeGetersWithBatchShape() without return types