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Fix small dtype inference error in ctc loss op test.

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Change: 115706184
This commit is contained in:
Eugene Brevdo 2016-02-26 13:59:10 -08:00 committed by TensorFlower Gardener
parent 8d7f58d44d
commit 6390a06d80
1 changed files with 2 additions and 2 deletions

4
tensorflow/contrib/ctc/ctc_loss_op_test.py
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@ -181,7 +181,7 @@ class CTCLossTest(tf.test.TestCase):
for t in range(5)] + 2 * [np.nan*np.ones((2, depth), np.float32)]
# convert inputs into [max_time x batch_size x depth tensor] Tensor
inputs = np.asarray(inputs)
inputs = np.asarray(inputs, dtype=np.float32)
# len batch_size array of label vectors
labels = SimpleSparseTensorFrom([targets_0, targets_1])
@ -198,7 +198,7 @@ class CTCLossTest(tf.test.TestCase):
for t in range(5)] + 2 * [np.zeros((2, depth), np.float32)]
# convert grad_truth into [max_time x batch_size x depth] Tensor
grad_truth = np.asarray(grad_truth)
grad_truth = np.asarray(grad_truth, dtype=np.float32)
self._testCTCLoss(inputs, seq_lens, labels, loss_truth, grad_truth)