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# Copyright 2016 The TensorFlow Authors. 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.
# ==============================================================================
"""Tests for 2D LSTMs."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.contrib.ndlstm.python import lstm2d as lstm2d_lib
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import test_util
from tensorflow.python.ops import variables
from tensorflow.python.platform import test
lstm2d = lstm2d_lib
def _rand(*size):
return np.random.uniform(size=size).astype("f")
class Lstm2DTest(test_util.TensorFlowTestCase):
def testImagesToSequenceDims(self):
with self.test_session():
inputs = constant_op.constant(_rand(2, 7, 11, 5))
outputs = lstm2d.images_to_sequence(inputs)
variables.global_variables_initializer().run()
result = outputs.eval()
self.assertEqual(tuple(result.shape), (11, 14, 5))
def testSequenceToImagesDims(self):
with self.test_session():
inputs = constant_op.constant(_rand(11, 14, 5))
outputs = lstm2d.sequence_to_images(inputs, 2)
variables.global_variables_initializer().run()
result = outputs.eval()
self.assertEqual(tuple(result.shape), (2, 7, 11, 5))
def testImagesAndSequenceDims(self):
with self.test_session():
size = (2, 7, 11, 5)
inputs = constant_op.constant(_rand(*size))
sequence = lstm2d.images_to_sequence(inputs)
outputs = lstm2d.sequence_to_images(sequence, size[0])
variables.global_variables_initializer().run()
result = outputs.eval()
self.assertEqual(tuple(result.shape), size)
def testSeparableLstmDims(self):
with self.test_session():
inputs = constant_op.constant(_rand(2, 7, 11, 5))
outputs = lstm2d.separable_lstm(inputs, 8)
variables.global_variables_initializer().run()
result = outputs.eval()
self.assertEqual(tuple(result.shape), (2, 7, 11, 8))
def testReduceToSequenceDims(self):
with self.test_session():
inputs = constant_op.constant(_rand(2, 7, 11, 5))
outputs = lstm2d.reduce_to_sequence(inputs, 8)
variables.global_variables_initializer().run()
result = outputs.eval()
self.assertEqual(tuple(result.shape), (2, 11, 8))
def testReduceToFinalDims(self):
with self.test_session():
inputs = constant_op.constant(_rand(2, 7, 11, 5))
outputs = lstm2d.reduce_to_final(inputs, 8, 12)
variables.global_variables_initializer().run()
result = outputs.eval()
self.assertEqual(tuple(result.shape), (2, 8))
if __name__ == "__main__":
test.main()
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