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Replace deprecated tf.contrib.metrics.streaming_accuracy with tf.metrics.accuracy #18154

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Apr 2, 2018
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Replace deprecated tf.contrib.metrics.streaming_accuracy with tf.metrics.accuracy #18154

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117d464
Replace deprecated tf.contrib.metrics.streaming_accuracy with tf.metr…
yongtang Apr 1, 2018
510946d
Replace streaming_accuracy with tf.metrics.accuracy in tests
yongtang Apr 1, 2018
5f1cdc4
Fix additional WARNING in evaluation_test.py
yongtang Apr 1, 2018
60bc416
Fix pylint issue
yongtang Apr 1, 2018
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10 changes: 4 additions & 6 deletions tensorflow/contrib/training/python/training/evaluation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,9 +36,8 @@

# Choose the metrics to compute:
names_to_values, names_to_updates = tf.contrib.metrics.aggregate_metric_map({
"accuracy": tf.contrib.metrics.streaming_accuracy(predictions, labels),
"mse": tf.contrib.metrics.streaming_mean_squared_error(
predictions, labels),
"accuracy": tf.metrics.accuracy(labels, predictions),
"mse": tf.metrics.mean_squared_error(labels, predictions),
})

# Define the summaries to write:
Expand Down Expand Up @@ -81,9 +80,8 @@

# Choose the metrics to compute:
names_to_values, names_to_updates = tf.contrib.metrics.aggregate_metric_map({
"accuracy": tf.contrib.metrics.streaming_accuracy(predictions, labels),
"mse": tf.contrib.metrics.streaming_mean_squared_error(
predictions, labels),
"accuracy": tf.metrics.accuracy(labels, predictions),
"mse": tf.metrics.mean_squared_error(labels, predictions),
})

# Define the summaries to write:
Expand Down
16 changes: 9 additions & 7 deletions tensorflow/contrib/training/python/training/evaluation_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,6 @@
from tensorflow.contrib.framework.python.ops import variables
from tensorflow.contrib.layers.python.layers import layers
from tensorflow.contrib.losses.python.losses import loss_ops
from tensorflow.contrib.metrics.python.ops import metric_ops
from tensorflow.contrib.training.python.training import evaluation
from tensorflow.contrib.training.python.training import training
from tensorflow.core.protobuf import config_pb2
Expand All @@ -38,6 +37,7 @@
from tensorflow.python.framework import random_seed
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import metrics
from tensorflow.python.ops import state_ops
from tensorflow.python.ops import variables as variables_lib
from tensorflow.python.platform import gfile
Expand Down Expand Up @@ -196,7 +196,8 @@ def testEvaluatePerfectModel(self):
logits = logistic_classifier(inputs)
predictions = math_ops.round(logits)

accuracy, update_op = metric_ops.streaming_accuracy(predictions, labels)
accuracy, update_op = metrics.accuracy(
predictions=predictions, labels=labels)

checkpoint_path = evaluation.wait_for_new_checkpoint(checkpoint_dir)

Expand Down Expand Up @@ -311,7 +312,8 @@ def testEvaluatePerfectModel(self):
logits = logistic_classifier(inputs)
predictions = math_ops.round(logits)

accuracy, update_op = metric_ops.streaming_accuracy(predictions, labels)
accuracy, update_op = metrics.accuracy(
predictions=predictions, labels=labels)

final_values = evaluation.evaluate_repeatedly(
checkpoint_dir=checkpoint_dir,
Expand Down Expand Up @@ -365,7 +367,8 @@ def testEvaluationLoopTimeoutWithTimeoutFn(self):
logits = logistic_classifier(inputs)
predictions = math_ops.round(logits)

accuracy, update_op = metric_ops.streaming_accuracy(predictions, labels)
accuracy, update_op = metrics.accuracy(
predictions=predictions, labels=labels)

timeout_fn_calls = [0]
def timeout_fn():
Expand Down Expand Up @@ -417,9 +420,8 @@ def testEvaluateWithEvalFeedDict(self):
self.assertEqual(final_values['my_var'], expected_value)

def _create_names_to_metrics(self, predictions, labels):
accuracy0, update_op0 = metric_ops.streaming_accuracy(predictions, labels)
accuracy1, update_op1 = metric_ops.streaming_accuracy(
predictions + 1, labels)
accuracy0, update_op0 = metrics.accuracy(labels, predictions)
accuracy1, update_op1 = metrics.accuracy(labels, predictions + 1)

names_to_values = {'Accuracy': accuracy0, 'Another_accuracy': accuracy1}
names_to_updates = {'Accuracy': update_op0, 'Another_accuracy': update_op1}
Expand Down