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pack_op_test.py
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66 lines (56 loc) · 2.3 KB
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# Copyright 2015 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Functional tests for Pack Op."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow.python.platform
import numpy as np
import tensorflow as tf
class PackOpTest(tf.test.TestCase):
def testSimple(self):
np.random.seed(7)
for use_gpu in False, True:
with self.test_session(use_gpu=use_gpu):
for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
data = np.random.randn(*shape)
# Convert [data[0], data[1], ...] separately to tensorflow
# TODO(irving): Remove list() once we handle maps correctly
xs = list(map(tf.constant, data))
# Pack back into a single tensorflow tensor
c = tf.pack(xs)
self.assertAllEqual(c.eval(), data)
def testGradients(self):
np.random.seed(7)
for use_gpu in False, True:
for shape in (2,), (3,), (2, 3), (3, 2), (4, 3, 2):
data = np.random.randn(*shape)
shapes = [shape[1:]] * shape[0]
with self.test_session(use_gpu=use_gpu):
# TODO(irving): Remove list() once we handle maps correctly
xs = list(map(tf.constant, data))
c = tf.pack(xs)
err = tf.test.compute_gradient_error(xs, shapes, c, shape)
self.assertLess(err, 1e-6)
def testZeroSize(self):
# Verify that pack doesn't crash for zero size inputs
for use_gpu in False, True:
with self.test_session(use_gpu=use_gpu):
for shape in (0,), (3,0), (0, 3):
x = np.zeros((2,) + shape)
p = tf.pack(list(x)).eval()
self.assertAllEqual(p, x)
if __name__ == "__main__":
tf.test.main()