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"""Tests for SparseReorder."""
import tensorflow.python.platform
import numpy as np
import tensorflow as tf
class SparseReorderTest(tf.test.TestCase):
def _SparseTensorPlaceholder(self):
return tf.SparseTensor(
tf.placeholder(tf.int64),
tf.placeholder(tf.int32),
tf.placeholder(tf.int64))
def _SparseTensorValue_5x6(self, permutation):
ind = np.array([
[0, 0],
[1, 0], [1, 3], [1, 4],
[3, 2], [3, 3]]).astype(np.int64)
val = np.array([0, 10, 13, 14, 32, 33]).astype(np.int32)
ind = ind[permutation]
val = val[permutation]
shape = np.array([5, 6]).astype(np.int64)
return tf.SparseTensorValue(ind, val, shape)
def testAlreadyInOrder(self):
with self.test_session(use_gpu=False) as sess:
sp_input = self._SparseTensorPlaceholder()
input_val = self._SparseTensorValue_5x6(np.arange(6))
sp_output = tf.sparse_reorder(sp_input)
output_val = sess.run(sp_output, {sp_input: input_val})
self.assertAllEqual(output_val.indices, input_val.indices)
self.assertAllEqual(output_val.values, input_val.values)
self.assertAllEqual(output_val.shape, input_val.shape)
def testOutOfOrder(self):
expected_output_val = self._SparseTensorValue_5x6(np.arange(6))
with self.test_session(use_gpu=False) as sess:
for _ in range(5): # To test various random permutations
sp_input = self._SparseTensorPlaceholder()
input_val = self._SparseTensorValue_5x6(np.random.permutation(6))
sp_output = tf.sparse_reorder(sp_input)
output_val = sess.run(sp_output, {sp_input: input_val})
self.assertAllEqual(output_val.indices, expected_output_val.indices)
self.assertAllEqual(output_val.values, expected_output_val.values)
self.assertAllEqual(output_val.shape, expected_output_val.shape)
if __name__ == "__main__":
tf.test.main()
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