def testMultipleGradientsWithVariables(self):
gradient = tf.constant(self._grad_vec, dtype=tf.float32)
variable = tf.Variable(tf.zeros_like(gradient))
grad_to_var = (gradient, variable)
gradient_multipliers = {variable: self._multiplier}
[grad_to_var] = slim.learning.multiply_gradients(
[grad_to_var],
gradient_multipliers)
# Ensure the variable passed through.
self.assertEqual(grad_to_var[1], variable)
with self.test_session() as sess:
actual_gradient = sess.run(grad_to_var[0])
np_testing.assert_almost_equal(actual_gradient,
self._multiplied_grad_vec, 5)
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