learning_test.py 文件源码

def testIndexedSlicesGradIsMultiplied(self):
    values = tf.constant(self._grad_vec, dtype=tf.float32)
    indices = tf.constant([0, 1, 2], dtype=tf.int32)
    dense_shape = tf.constant([self._grad_vec.size], dtype=tf.int32)

    gradient = tf.IndexedSlices(values, indices, dense_shape)
    variable = tf.Variable(tf.zeros((1, 3)))
    grad_to_var = (gradient, variable)
    gradient_multipliers = {variable: self._multiplier}

    [grad_to_var] = slim.learning.multiply_gradients(
        [grad_to_var],
        gradient_multipliers)

    # Ensure the built IndexedSlice has the right form.
    self.assertEqual(grad_to_var[1], variable)
    self.assertEqual(grad_to_var[0].indices, indices)
    self.assertEqual(grad_to_var[0].dense_shape, dense_shape)

    with self.test_session() as sess:
      actual_gradient = sess.run(grad_to_var[0].values)
    np_testing.assert_almost_equal(actual_gradient,
                                   self._multiplied_grad_vec, 5)