'Verify dense feature extraction with atrous convolution.'

def testAtrousFullyConvolutionalValues(self):

    nominal_stride = 32
    for output_stride in [4, 8, 16, 32, None]:
        with slim.arg_scope(resnet_utils.resnet_arg_scope()):
            with tf.Graph().as_default():
                with self.test_session() as sess:
                    tf.set_random_seed(0)
                    inputs = create_test_input(2, 81, 81, 3)
                    (output, _) = self._resnet_small(inputs, None, is_training=False, global_pool=False, output_stride=output_stride)
                    if (output_stride is None):
                        factor = 1
                    else:
                        factor = (nominal_stride // output_stride)
                    output = resnet_utils.subsample(output, factor)
                    tf.get_variable_scope().reuse_variables()
                    (expected, _) = self._resnet_small(inputs, None, is_training=False, global_pool=False)
                    sess.run(tf.global_variables_initializer())
                    self.assertAllClose(output.eval(), expected.eval(), atol=0.0001, rtol=0.0001)
