experiments/STT-tensorflow
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Add named arguments to all uses of tf.split and reverse the order of arguments

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so as to conform to the order that will be standard once the split_v -> split
rename happens.
Change: 141326568
This commit is contained in:
A. Unique TensorFlower 2016-12-07 10:37:17 -08:00 committed by TensorFlower Gardener
parent 878f5fcb81
commit c8cab5483f
1 changed files with 6 additions and 6 deletions
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12
tensorflow/contrib/metrics/python/ops/metric_ops_test.py
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@ -1929,10 +1929,10 @@ class StreamingPrecisionRecallThresholdsTest(tf.test.TestCase):
rec, rec_op = metrics.streaming_recall_at_thresholds(
predictions, labels, thresholds, weights=weights)
[prec_low, prec_high] = tf.split(0, 2, prec)
[prec_low, prec_high] = tf.split(value=prec, num_or_size_splits=2, axis=0)
prec_low = tf.reshape(prec_low, shape=())
prec_high = tf.reshape(prec_high, shape=())
[rec_low, rec_high] = tf.split(0, 2, rec)
[rec_low, rec_high] = tf.split(value=rec, num_or_size_splits=2, axis=0)
rec_low = tf.reshape(rec_low, shape=())
rec_high = tf.reshape(rec_high, shape=())
@ -1956,10 +1956,10 @@ class StreamingPrecisionRecallThresholdsTest(tf.test.TestCase):
rec, rec_op = metrics.streaming_recall_at_thresholds(
predictions, labels, thresholds, weights=weights)
[prec_low, prec_high] = tf.split(0, 2, prec)
[prec_low, prec_high] = tf.split(value=prec, num_or_size_splits=2, axis=0)
prec_low = tf.reshape(prec_low, shape=())
prec_high = tf.reshape(prec_high, shape=())
[rec_low, rec_high] = tf.split(0, 2, rec)
[rec_low, rec_high] = tf.split(value=rec, num_or_size_splits=2, axis=0)
rec_low = tf.reshape(rec_low, shape=())
rec_high = tf.reshape(rec_high, shape=())
@ -1981,8 +1981,8 @@ class StreamingPrecisionRecallThresholdsTest(tf.test.TestCase):
rec, rec_op = metrics.streaming_recall_at_thresholds(
predictions, labels, thresholds)
[prec_low, prec_high] = tf.split(0, 2, prec)
[rec_low, rec_high] = tf.split(0, 2, rec)
[prec_low, prec_high] = tf.split(value=prec, num_or_size_splits=2, axis=0)
[rec_low, rec_high] = tf.split(value=rec, num_or_size_splits=2, axis=0)
sess.run(tf.local_variables_initializer())
sess.run([prec_op, rec_op])