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TensorFlow provides a convenience class inheriting from unittest.TestCase which adds methods relevant to TensorFlow tests. Here is an example:

    import tensorflow as tf


    class SquareTest(tf.test.TestCase):

      def testSquare(self):
        with self.test_session():
          x = tf.square([2, 3])
          self.assertAllEqual(x.eval(), [4, 9])


    if __name__ == '__main__':
      tf.test.main()

tf.test.TestCase inherits from unittest.TestCase but adds a few additional methods. See @{tf.test.TestCase} for details.

• @{tf.test.main}
• @{tf.test.TestCase}
• @{tf.test.test_src_dir_path}

Note: tf.test.mock is an alias to the python mock or unittest.mock depending on the python version.

• @{tf.test.assert_equal_graph_def}
• @{tf.test.get_temp_dir}
• @{tf.test.is_built_with_cuda}
• @{tf.test.is_gpu_available}
• @{tf.test.gpu_device_name}

@{tf.test.compute_gradient} and @{tf.test.compute_gradient_error} perform numerical differentiation of graphs for comparison against registered analytic gradients.