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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 tensorflow.contrib.layers.python.ops.sparse_ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
from tensorflow.contrib.layers.python.ops import sparse_ops
class SparseOpsTest(tf.test.TestCase):
def test_dense_to_sparse_tensor_1d(self):
with self.test_session() as sess:
st = sparse_ops.dense_to_sparse_tensor([1, 0, 2, 0])
result = sess.run(st)
self.assertEqual(result.indices.dtype, np.int64)
self.assertEqual(result.values.dtype, np.int32)
self.assertEqual(result.dense_shape.dtype, np.int64)
self.assertAllEqual([[0], [2]], result.indices)
self.assertAllEqual([1, 2], result.values)
self.assertAllEqual([4], result.dense_shape)
def test_dense_to_sparse_tensor_1d_float(self):
with self.test_session() as sess:
st = sparse_ops.dense_to_sparse_tensor([1.5, 0.0, 2.3, 0.0])
result = sess.run(st)
self.assertEqual(result.indices.dtype, np.int64)
self.assertEqual(result.values.dtype, np.float32)
self.assertEqual(result.dense_shape.dtype, np.int64)
self.assertAllEqual([[0], [2]], result.indices)
self.assertAllClose([1.5, 2.3], result.values)
self.assertAllEqual([4], result.dense_shape)
def test_dense_to_sparse_tensor_1d_bool(self):
with self.test_session() as sess:
st = sparse_ops.dense_to_sparse_tensor([True, False, True, False])
result = sess.run(st)
self.assertEqual(result.indices.dtype, np.int64)
self.assertEqual(result.values.dtype, np.bool)
self.assertEqual(result.dense_shape.dtype, np.int64)
self.assertAllEqual([[0], [2]], result.indices)
self.assertAllEqual([True, True], result.values)
self.assertAllEqual([4], result.dense_shape)
def test_dense_to_sparse_tensor_1d_str(self):
with self.test_session() as sess:
st = sparse_ops.dense_to_sparse_tensor([b'qwe', b'', b'ewq', b''])
result = sess.run(st)
self.assertEqual(result.indices.dtype, np.int64)
self.assertEqual(result.values.dtype, np.object)
self.assertEqual(result.dense_shape.dtype, np.int64)
self.assertAllEqual([[0], [2]], result.indices)
self.assertAllEqual([b'qwe', b'ewq'], result.values)
self.assertAllEqual([4], result.dense_shape)
def test_dense_to_sparse_tensor_1d_str_special_ignore(self):
with self.test_session() as sess:
st = sparse_ops.dense_to_sparse_tensor(
[b'qwe', b'', b'ewq', b''], ignore_value=b'qwe')
result = sess.run(st)
self.assertEqual(result.indices.dtype, np.int64)
self.assertEqual(result.values.dtype, np.object)
self.assertEqual(result.dense_shape.dtype, np.int64)
self.assertAllEqual([[1], [2], [3]], result.indices)
self.assertAllEqual([b'', b'ewq', b''], result.values)
self.assertAllEqual([4], result.dense_shape)
def test_dense_to_sparse_tensor_2d(self):
with self.test_session() as sess:
st = sparse_ops.dense_to_sparse_tensor([[1, 2, 0, 0], [3, 4, 5, 0]])
result = sess.run(st)
self.assertAllEqual([[0, 0], [0, 1], [1, 0], [1, 1], [1, 2]],
result.indices)
self.assertAllEqual([1, 2, 3, 4, 5], result.values)
self.assertAllEqual([2, 4], result.dense_shape)
def test_dense_to_sparse_tensor_3d(self):
with self.test_session() as sess:
st = sparse_ops.dense_to_sparse_tensor([[[1, 2, 0, 0], [3, 4, 5, 0]],
[[7, 8, 0, 0], [9, 0, 0, 0]]])
result = sess.run(st)
self.assertAllEqual([[0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 1, 1], [0, 1, 2],
[1, 0, 0], [1, 0, 1], [1, 1, 0]], result.indices)
self.assertAllEqual([1, 2, 3, 4, 5, 7, 8, 9], result.values)
self.assertAllEqual([2, 2, 4], result.dense_shape)
def test_dense_to_sparse_tensor_1d_no_shape(self):
with self.test_session() as sess:
tensor = tf.placeholder(shape=[None], dtype=tf.int32)
st = sparse_ops.dense_to_sparse_tensor(tensor)
result = sess.run(st, feed_dict={tensor: [0, 100, 0, 3]})
self.assertAllEqual([[1], [3]], result.indices)
self.assertAllEqual([100, 3], result.values)
self.assertAllEqual([4], result.dense_shape)
def test_dense_to_sparse_tensor_3d_no_shape(self):
with self.test_session() as sess:
tensor = tf.placeholder(shape=[None, None, None], dtype=tf.int32)
st = sparse_ops.dense_to_sparse_tensor(tensor)
result = sess.run(st,
feed_dict={
tensor: [[[1, 2, 0, 0], [3, 4, 5, 0]],
[[7, 8, 0, 0], [9, 0, 0, 0]]]
})
self.assertAllEqual([[0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 1, 1], [0, 1, 2],
[1, 0, 0], [1, 0, 1], [1, 1, 0]], result.indices)
self.assertAllEqual([1, 2, 3, 4, 5, 7, 8, 9], result.values)
self.assertAllEqual([2, 2, 4], result.dense_shape)
def test_convert_to_sparse_undef_shape(self):
with self.test_session():
with self.assertRaises(ValueError):
tensor = tf.placeholder(dtype=tf.int32)
sparse_ops.dense_to_sparse_tensor(tensor)
if __name__ == '__main__':
tf.test.main()
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