Fix typos

tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary.h

@@ -36,7 +36,7 @@ class WeightedQuantilesSummary {
   struct SummaryEntry {
     SummaryEntry(const ValueType& v, const WeightType& w, const WeightType& min,
                  const WeightType& max) {
-      // Explicitely initialize all of memory (including padding from memory
+      // Explicitly initialize all of memory (including padding from memory
       // alignment) to allow the struct to be msan-resistant "plain old data".
       //
       // POD = http://en.cppreference.com/w/cpp/concept/PODType

tensorflow/contrib/framework/python/framework/tensor_util.py

@@ -79,7 +79,7 @@ def reduce_sum_n(tensors, name=None):
 
 @deprecated(None,
     "Please switch to tf.confusion_matrix.remove_squeezable_dimensions. Note "
-    "that order of the inputs and ouputs of labels and predictions have also "
+    "that order of the inputs and outputs of labels and predictions have also "
     "been switched.")
 def remove_squeezable_dimensions(predictions, labels, name=None):
   """Squeeze last dim if ranks of `predictions` and `labels` differ by 1.

tensorflow/contrib/rnn/python/ops/rnn_cell.py

@@ -2058,7 +2058,7 @@ def _conv(args,
     if len(shape) not in [3,4,5]:
       raise ValueError("Conv Linear expects 3D, 4D or 5D arguments: %s" % str(shapes))
     if len(shape) != len(shapes[0]):
-      raise ValueError("Conv Linear expects all args to be of same Dimensiton: %s" % str(shapes))
+      raise ValueError("Conv Linear expects all args to be of same Dimension: %s" % str(shapes))
     else:
       total_arg_size_depth += shape[-1]
   dtype = [a.dtype for a in args][0]

tensorflow/core/kernels/mkl_cwise_ops_common.cc

@@ -48,7 +48,7 @@ class MklBinaryOp : public BinaryOp<Device, Functor> {
     auto out = context->mutable_output(0);
     VLOG(1) << "Shapes (output): " << out->shape().DebugString();
 
-    // Pass input shape through to ouput shape
+    // Pass input shape through to output shape
     ForwardMklMetaDataInToOut(context, 0, 0);
 
     out = context->mutable_output(0);

tensorflow/examples/tutorials/word2vec/word2vec_basic.py

@@ -89,7 +89,7 @@ def build_dataset(words, n_words):
 # Filling 4 global variables:
 # data - list of codes (integers from 0 to vocabulary_size-1).
 #   This is the original text but words are replaced by their codes
-# count - map of words(strings) to count of occurences
+# count - map of words(strings) to count of occurrences
 # dictionary - map of words(strings) to their codes(integers)
 # reverse_dictionary - maps codes(integers) to words(strings)
 data, count, dictionary, reverse_dictionary = build_dataset(vocabulary,

tensorflow/python/debug/lib/debug_graphs.py

@@ -231,7 +231,7 @@ def _infer_device_name(graph_def):
       break
   if device_name is None:
     logging.warn(
-        "Failed to infer device name from partiton GraphDef: none of the nodes "
+        "Failed to infer device name from partition GraphDef: none of the nodes "
         "of the GraphDef has a non-empty device name.")
   return device_name
 

tensorflow/python/keras/_impl/keras/engine/topology_test.py

@@ -200,7 +200,7 @@ def test_node_construction(self):
     with self.assertRaises(ValueError):
       _ = keras.layers.Input(shape=(32,), batch_shape=(10, 32))
     with self.assertRaises(ValueError):
-      _ = keras.layers.Input(shape=(32,), unknwon_kwarg=None)
+      _ = keras.layers.Input(shape=(32,), unknown_kwarg=None)
 
     self.assertListEqual(a.get_shape().as_list(), [None, 32])
     a_layer, a_node_index, a_tensor_index = a._keras_history

tensorflow/python/kernel_tests/summary_tensor_op_test.py

@@ -154,7 +154,7 @@ def get_description(summary_op):
       self.assertEqual(descr.display_name, "my name")
       self.assertEqual(descr.summary_description, "my description")
 
-      # If both SummmaryMetadata and explicit args are provided, the args win
+      # If both SummaryMetadata and explicit args are provided, the args win
       overwrite = summary_ops.tensor_summary(
           "simple",
           const,