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author | Manjunath Kudlur <keveman@gmail.com> | 2015-11-06 16:27:58 -0800 |
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committer | Manjunath Kudlur <keveman@gmail.com> | 2015-11-06 16:27:58 -0800 |
commit | f41959ccb2d9d4c722fe8fc3351401d53bcf4900 (patch) | |
tree | ef0ca22cb2a5ac4bdec9d080d8e0788a53ed496d /tensorflow/python/kernel_tests/reverse_sequence_op_test.py |
TensorFlow: Initial commit of TensorFlow library.
TensorFlow is an open source software library for numerical computation
using data flow graphs.
Base CL: 107276108
Diffstat (limited to 'tensorflow/python/kernel_tests/reverse_sequence_op_test.py')
-rw-r--r-- | tensorflow/python/kernel_tests/reverse_sequence_op_test.py | 109 |
1 files changed, 109 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/reverse_sequence_op_test.py b/tensorflow/python/kernel_tests/reverse_sequence_op_test.py new file mode 100644 index 0000000000..7cfbcd7946 --- /dev/null +++ b/tensorflow/python/kernel_tests/reverse_sequence_op_test.py @@ -0,0 +1,109 @@ +"""Tests for tensorflow.ops.reverse_sequence_op.""" +import tensorflow.python.platform + +import numpy as np +import tensorflow as tf + +from tensorflow.python.kernel_tests import gradient_checker as gc + + +class ReverseSequenceTest(tf.test.TestCase): + + def _testReverseSequence(self, x, seq_dim, seq_lengths, + truth, use_gpu=False, expected_err_re=None): + with self.test_session(use_gpu=use_gpu): + ans = tf.reverse_sequence(x, + seq_dim=seq_dim, + seq_lengths=seq_lengths) + if expected_err_re is None: + tf_ans = ans.eval() + self.assertAllClose(tf_ans, truth, atol=1e-10) + self.assertShapeEqual(truth, ans) + else: + with self.assertRaisesOpError(expected_err_re): + ans.eval() + + def _testBothReverseSequence(self, x, seq_dim, seq_lengths, + truth, expected_err_re=None): + self._testReverseSequence(x, seq_dim, seq_lengths, + truth, True, expected_err_re) + self._testReverseSequence(x, seq_dim, seq_lengths, + truth, False, expected_err_re) + + def _testBasic(self, dtype): + x = np.asarray([ + [[1, 2, 3, 4], [5, 6, 7, 8]], + [[9, 10, 11, 12], [13, 14, 15, 16]], + [[17, 18, 19, 20], [21, 22, 23, 24]]], dtype=dtype) + x = x.reshape(3, 2, 4, 1, 1) + + # reverse dim 2 up to (0:3, none, 0:4) along dim=0 + seq_dim = 2 + seq_lengths = np.asarray([3, 0, 4], dtype=np.int64) + + truth = np.asarray( + [[[3, 2, 1, 4], [7, 6, 5, 8]], # reverse 0:3 + [[9, 10, 11, 12], [13, 14, 15, 16]], # reverse none + [[20, 19, 18, 17], [24, 23, 22, 21]]], # reverse 0:4 (all) + dtype=dtype) + truth = truth.reshape(3, 2, 4, 1, 1) + self._testBothReverseSequence(x, seq_dim, seq_lengths, truth) + + def testFloatBasic(self): + self._testBasic(np.float32) + + def testDoubleBasic(self): + self._testBasic(np.float64) + + def testInt32Basic(self): + self._testBasic(np.int32) + + def testInt64Basic(self): + self._testBasic(np.int64) + + def testSComplexBasic(self): + self._testBasic(np.complex64) + + def testFloatReverseSequenceGrad(self): + x = np.asarray([ + [[1, 2, 3, 4], [5, 6, 7, 8]], + [[9, 10, 11, 12], [13, 14, 15, 16]], + [[17, 18, 19, 20], [21, 22, 23, 24]]], dtype=np.float) + x = x.reshape(3, 2, 4, 1, 1) + + # reverse dim 2 up to (0:3, none, 0:4) along dim=0 + seq_dim = 2 + seq_lengths = np.asarray([3, 0, 4], dtype=np.int64) + + with self.test_session(): + input_t = tf.constant(x, shape=x.shape) + seq_lengths_t = tf.constant(seq_lengths, shape=seq_lengths.shape) + reverse_sequence_out = tf.reverse_sequence(input_t, + seq_dim=seq_dim, + seq_lengths=seq_lengths_t) + err = gc.ComputeGradientError(input_t, + x.shape, + reverse_sequence_out, + x.shape, + x_init_value=x) + print "ReverseSequence gradient error = %g" % err + self.assertLess(err, 1e-8) + + def testShapeFunctionEdgeCases(self): + # Batch size mismatched between input and seq_lengths. + with self.assertRaises(ValueError): + tf.reverse_sequence( + tf.placeholder(tf.float32, shape=(32, 2, 3)), + seq_lengths=tf.placeholder(tf.int64, shape=(33,)), + seq_dim=3) + + # seq_dim out of bounds. + with self.assertRaisesRegexp(ValueError, "seq_dim must be < input.dims()"): + tf.reverse_sequence( + tf.placeholder(tf.float32, shape=(32, 2, 3)), + seq_lengths=tf.placeholder(tf.int64, shape=(32,)), + seq_dim=3) + + +if __name__ == "__main__": + tf.test.main() |