aboutsummaryrefslogtreecommitdiffhomepage
diff options
context:
space:
mode:
authorGravatar Taehoon Lee <taehoonlee@snu.ac.kr>2017-06-11 14:23:54 +0900
committerGravatar Taehoon Lee <taehoonlee@snu.ac.kr>2017-06-11 14:23:54 +0900
commitcc2b908fa6f2acf06ffccf341ad2af8cd24aa12f (patch)
tree02580d97f45e7edaa3cf9e0d3278bb687107d6d1
parent504965336d1432ee96b4f0e9b78f65ee201e9be5 (diff)
Fix typos
-rw-r--r--tensorflow/contrib/keras/python/keras/backend.py6
-rw-r--r--tensorflow/contrib/keras/python/keras/models_test.py2
-rw-r--r--tensorflow/contrib/learn/python/learn/estimators/linear_test.py20
-rw-r--r--tensorflow/contrib/learn/python/learn/estimators/model_fn_test.py10
-rw-r--r--tensorflow/core/kernels/priority_queue.cc2
-rw-r--r--tensorflow/core/kernels/typed_conditional_accumulator_base.h2
-rw-r--r--tensorflow/python/debug/wrappers/framework_test.py2
-rw-r--r--tensorflow/python/estimator/canned/dnn_linear_combined.py2
-rw-r--r--tensorflow/tensorboard/components/tf_graph_common/graph.ts2
-rw-r--r--tensorflow/tools/tfprof/g3doc/command_line.md2
10 files changed, 25 insertions, 25 deletions
diff --git a/tensorflow/contrib/keras/python/keras/backend.py b/tensorflow/contrib/keras/python/keras/backend.py
index b7adf9461a..7a00560308 100644
--- a/tensorflow/contrib/keras/python/keras/backend.py
+++ b/tensorflow/contrib/keras/python/keras/backend.py
@@ -3260,7 +3260,7 @@ def conv2d(x,
padding: string, `"same"` or `"valid"`.
data_format: `"channels_last"` or `"channels_first"`.
Whether to use Theano or TensorFlow data format
- for inputs/kernels/ouputs.
+ for inputs/kernels/outputs.
dilation_rate: tuple of 2 integers.
Returns:
@@ -3308,7 +3308,7 @@ def conv2d_transpose(x,
padding: string, `"same"` or `"valid"`.
data_format: `"channels_last"` or `"channels_first"`.
Whether to use Theano or TensorFlow data format
- for inputs/kernels/ouputs.
+ for inputs/kernels/outputs.
Returns:
A tensor, result of transposed 2D convolution.
@@ -3394,7 +3394,7 @@ def conv3d(x,
padding: string, `"same"` or `"valid"`.
data_format: `"channels_last"` or `"channels_first"`.
Whether to use Theano or TensorFlow data format
- for inputs/kernels/ouputs.
+ for inputs/kernels/outputs.
dilation_rate: tuple of 3 integers.
Returns:
diff --git a/tensorflow/contrib/keras/python/keras/models_test.py b/tensorflow/contrib/keras/python/keras/models_test.py
index 50aba43c24..99fd6e1cbe 100644
--- a/tensorflow/contrib/keras/python/keras/models_test.py
+++ b/tensorflow/contrib/keras/python/keras/models_test.py
@@ -105,7 +105,7 @@ class TestModelSaving(test.TestCase):
out2 = model.predict(x)
self.assertAllClose(out, out2, atol=1e-05)
- def test_fuctional_model_saving(self):
+ def test_functional_model_saving(self):
if h5py is None:
return # Skip test if models cannot be saved.
diff --git a/tensorflow/contrib/learn/python/learn/estimators/linear_test.py b/tensorflow/contrib/learn/python/learn/estimators/linear_test.py
index 145d5c40fa..d3bb0fda57 100644
--- a/tensorflow/contrib/learn/python/learn/estimators/linear_test.py
+++ b/tensorflow/contrib/learn/python/learn/estimators/linear_test.py
@@ -729,7 +729,7 @@ class LinearClassifierTest(test.TestCase):
self.assertLess(loss, 0.07)
def testSdcaOptimizerRealValuedFeatures(self):
- """Tests LinearClasssifier with SDCAOptimizer and real valued features."""
+ """Tests LinearClassifier with SDCAOptimizer and real valued features."""
def input_fn():
return {
@@ -776,7 +776,7 @@ class LinearClassifierTest(test.TestCase):
self.assertLess(loss, 0.05)
def testSdcaOptimizerBucketizedFeatures(self):
- """Tests LinearClasssifier with SDCAOptimizer and bucketized features."""
+ """Tests LinearClassifier with SDCAOptimizer and bucketized features."""
def input_fn():
return {
@@ -802,7 +802,7 @@ class LinearClassifierTest(test.TestCase):
self.assertGreater(scores['accuracy'], 0.9)
def testSdcaOptimizerSparseFeatures(self):
- """Tests LinearClasssifier with SDCAOptimizer and sparse features."""
+ """Tests LinearClassifier with SDCAOptimizer and sparse features."""
def input_fn():
return {
@@ -833,7 +833,7 @@ class LinearClassifierTest(test.TestCase):
self.assertGreater(scores['accuracy'], 0.9)
def testSdcaOptimizerWeightedSparseFeatures(self):
- """LinearClasssifier with SDCAOptimizer and weighted sparse features."""
+ """LinearClassifier with SDCAOptimizer and weighted sparse features."""
def input_fn():
return {
@@ -864,7 +864,7 @@ class LinearClassifierTest(test.TestCase):
self.assertGreater(scores['accuracy'], 0.9)
def testSdcaOptimizerCrossedFeatures(self):
- """Tests LinearClasssifier with SDCAOptimizer and crossed features."""
+ """Tests LinearClassifier with SDCAOptimizer and crossed features."""
def input_fn():
return {
@@ -897,7 +897,7 @@ class LinearClassifierTest(test.TestCase):
self.assertGreater(scores['accuracy'], 0.9)
def testSdcaOptimizerMixedFeatures(self):
- """Tests LinearClasssifier with SDCAOptimizer and a mix of features."""
+ """Tests LinearClassifier with SDCAOptimizer and a mix of features."""
def input_fn():
return {
@@ -1509,7 +1509,7 @@ class LinearRegressorTest(test.TestCase):
self.assertLess(loss, 0.05)
def testSdcaOptimizerSparseFeaturesWithL1Reg(self):
- """Tests LinearClasssifier with SDCAOptimizer and sparse features."""
+ """Tests LinearClassifier with SDCAOptimizer and sparse features."""
def input_fn():
return {
@@ -1581,7 +1581,7 @@ class LinearRegressorTest(test.TestCase):
self.assertLess(l1_reg_weights_norm, no_l1_reg_weights_norm)
def testSdcaOptimizerBiasOnly(self):
- """Tests LinearClasssifier with SDCAOptimizer and validates bias weight."""
+ """Tests LinearClassifier with SDCAOptimizer and validates bias weight."""
def input_fn():
"""Testing the bias weight when it's the only feature present.
@@ -1614,7 +1614,7 @@ class LinearRegressorTest(test.TestCase):
regressor.get_variable_value('linear/bias_weight')[0], 0.25, err=0.1)
def testSdcaOptimizerBiasAndOtherColumns(self):
- """Tests LinearClasssifier with SDCAOptimizer and validates bias weight."""
+ """Tests LinearClassifier with SDCAOptimizer and validates bias weight."""
def input_fn():
"""Testing the bias weight when there are other features present.
@@ -1676,7 +1676,7 @@ class LinearRegressorTest(test.TestCase):
regressor.get_variable_value('linear/b/weight')[0], 0.0, err=0.05)
def testSdcaOptimizerBiasAndOtherColumnsFabricatedCentered(self):
- """Tests LinearClasssifier with SDCAOptimizer and validates bias weight."""
+ """Tests LinearClassifier with SDCAOptimizer and validates bias weight."""
def input_fn():
"""Testing the bias weight when there are other features present.
diff --git a/tensorflow/contrib/learn/python/learn/estimators/model_fn_test.py b/tensorflow/contrib/learn/python/learn/estimators/model_fn_test.py
index 6ebfeb0f16..284e2cfd7a 100644
--- a/tensorflow/contrib/learn/python/learn/estimators/model_fn_test.py
+++ b/tensorflow/contrib/learn/python/learn/estimators/model_fn_test.py
@@ -123,7 +123,7 @@ class ModelFnopsTest(test.TestCase):
self.assertAllEqual(predictions["probabilities"].eval(),
regression_output.value.eval())
- def testEstimatorSpec_export_classsification(self):
+ def testEstimatorSpec_export_classification(self):
predictions = self.create_predictions()
output_alternatives = {"classification_head": (
constants.ProblemType.CLASSIFICATION, predictions)}
@@ -143,7 +143,7 @@ class ModelFnopsTest(test.TestCase):
self.assertAllEqual(predictions["classes"].eval(),
classification_output.classes.eval())
- def testEstimatorSpec_export_classsification_with_missing_scores(self):
+ def testEstimatorSpec_export_classification_with_missing_scores(self):
predictions = self.create_predictions()
output_alternatives_predictions = predictions.copy()
del output_alternatives_predictions["scores"]
@@ -165,7 +165,7 @@ class ModelFnopsTest(test.TestCase):
self.assertAllEqual(predictions["classes"].eval(),
classification_output.classes.eval())
- def testEstimatorSpec_export_classsification_with_missing_scores_proba(self):
+ def testEstimatorSpec_export_classification_with_missing_scores_proba(self):
predictions = self.create_predictions()
output_alternatives_predictions = predictions.copy()
del output_alternatives_predictions["scores"]
@@ -187,7 +187,7 @@ class ModelFnopsTest(test.TestCase):
self.assertAllEqual(predictions["classes"].eval(),
classification_output.classes.eval())
- def testEstimatorSpec_export_classsification_with_missing_classes(self):
+ def testEstimatorSpec_export_classification_with_missing_classes(self):
predictions = self.create_predictions()
output_alternatives_predictions = predictions.copy()
del output_alternatives_predictions["classes"]
@@ -208,7 +208,7 @@ class ModelFnopsTest(test.TestCase):
classification_output.scores.eval())
self.assertIsNone(classification_output.classes)
- def testEstimatorSpec_export_classsification_with_nonstring_classes(self):
+ def testEstimatorSpec_export_classification_with_nonstring_classes(self):
predictions = self.create_predictions()
output_alternatives_predictions = predictions.copy()
output_alternatives_predictions["classes"] = constant_op.constant(
diff --git a/tensorflow/core/kernels/priority_queue.cc b/tensorflow/core/kernels/priority_queue.cc
index 8884c0c4a0..9cbd832957 100644
--- a/tensorflow/core/kernels/priority_queue.cc
+++ b/tensorflow/core/kernels/priority_queue.cc
@@ -338,7 +338,7 @@ void PriorityQueue::TryDequeueMany(int num_elements, OpKernelContext* ctx,
for (; s > 0; --s) {
if (attempt->tuple.empty()) {
// Only allocate tuple when we have something to dequeue
- // so we don't use exceessive memory when there are many
+ // so we don't use excessive memory when there are many
// blocked dequeue attempts waiting.
attempt->tuple.reserve(num_components());
for (int i = 0; i < num_components(); ++i) {
diff --git a/tensorflow/core/kernels/typed_conditional_accumulator_base.h b/tensorflow/core/kernels/typed_conditional_accumulator_base.h
index dbd7de7ce0..1980f758fc 100644
--- a/tensorflow/core/kernels/typed_conditional_accumulator_base.h
+++ b/tensorflow/core/kernels/typed_conditional_accumulator_base.h
@@ -22,7 +22,7 @@ namespace tensorflow {
/*
* TypedConditionalAccumulatorBase is a templated companion of
- * ConditionalAccumulatorBase which allows for subclassses to use different
+ * ConditionalAccumulatorBase which allows for subclasses to use different
* types for the input gradients. (See ConditionalAccumulator and
* SparseConditionalAccumulator.)
*
diff --git a/tensorflow/python/debug/wrappers/framework_test.py b/tensorflow/python/debug/wrappers/framework_test.py
index 536365b692..2b2289d6a8 100644
--- a/tensorflow/python/debug/wrappers/framework_test.py
+++ b/tensorflow/python/debug/wrappers/framework_test.py
@@ -215,7 +215,7 @@ class DebugWrapperSessionTest(test_util.TensorFlowTestCase):
wrapper_sess.partial_run_setup(self._p)
def testInteractiveSessionInit(self):
- """The wrapper should work also on other subclassses of session.Session."""
+ """The wrapper should work also on other subclasses of session.Session."""
TestDebugWrapperSession(
session.InteractiveSession(), self._dump_root, self._observer)
diff --git a/tensorflow/python/estimator/canned/dnn_linear_combined.py b/tensorflow/python/estimator/canned/dnn_linear_combined.py
index e991f6431c..30b64a32ff 100644
--- a/tensorflow/python/estimator/canned/dnn_linear_combined.py
+++ b/tensorflow/python/estimator/canned/dnn_linear_combined.py
@@ -374,7 +374,7 @@ class DNNLinearCombinedClassifier(estimator.Estimator):
class DNNLinearCombinedRegressor(estimator.Estimator):
- """An estimator for TensorFlow Linear and DNN joined models for regresssion.
+ """An estimator for TensorFlow Linear and DNN joined models for regression.
Note: This estimator is also known as wide-n-deep.
diff --git a/tensorflow/tensorboard/components/tf_graph_common/graph.ts b/tensorflow/tensorboard/components/tf_graph_common/graph.ts
index 1b0abcfd85..cbd7b14539 100644
--- a/tensorflow/tensorboard/components/tf_graph_common/graph.ts
+++ b/tensorflow/tensorboard/components/tf_graph_common/graph.ts
@@ -723,7 +723,7 @@ export class MetaedgeImpl implements Metaedge {
number {
let opNode = <OpNode> h.node(edge.v);
if (opNode.outputShapes == null) {
- // No shape information. Asssume a single number. This gives
+ // No shape information. Assume a single number. This gives
// a lower bound for the total size.
return 1;
}
diff --git a/tensorflow/tools/tfprof/g3doc/command_line.md b/tensorflow/tools/tfprof/g3doc/command_line.md
index 0d8d56809a..9f0de72e07 100644
--- a/tensorflow/tools/tfprof/g3doc/command_line.md
+++ b/tensorflow/tools/tfprof/g3doc/command_line.md
@@ -126,7 +126,7 @@ tfprof>
-show_name_regexes .*
-hide_name_regexes IsVariableInitialized_[0-9]+,save\/.*,^zeros[0-9_]*
-account_displayed_op_only false
-# supported select fileds. Availability depends on --[run_meta|checkpoint|op_log]_path.
+# supported select fields. Availability depends on --[run_meta|checkpoint|op_log]_path.
# [bytes|micros|params|float_ops|occurrence|tensor_value|device|op_types]
-select params
# format: output_type:key=value,key=value...