Fix typos in string and comments of python and C++ code in models

dongjoon-hyun · dongjoon-hyun · commit dc9616b8af01 · 2016-01-14T10:10:01.000-08:00
diff --git a/tensorflow/models/embedding/word2vec_kernels.cc b/tensorflow/models/embedding/word2vec_kernels.cc
@@ -117,7 +117,7 @@ class SkipgramOp : public OpKernel {
   int32 label_limit_ GUARDED_BY(mu_);
 
   // {example_pos_, label_pos_} is the cursor for the next example.
-  // example_pos_ wrapps around at the end of corpus_. For each
+  // example_pos_ wraps around at the end of corpus_. For each
   // example, we randomly generate [label_pos_, label_limit) for
   // labels.
   void NextExample(int32* example, int32* label) EXCLUSIVE_LOCKS_REQUIRED(mu_) {
diff --git a/tensorflow/models/embedding/word2vec_ops.cc b/tensorflow/models/embedding/word2vec_ops.cc
@@ -65,7 +65,7 @@ w_out: output word embedding.
 examples: A vector of word ids.
 labels: A vector of word ids.
 vocab_count: Count of words in the vocabulary.
-num_negative_samples: Number of negative samples per exaple.
+num_negative_samples: Number of negative samples per example.
 )doc");
 
 }  // end namespace tensorflow
diff --git a/tensorflow/models/image/alexnet/alexnet_benchmark.py b/tensorflow/models/image/alexnet/alexnet_benchmark.py
@@ -164,7 +164,7 @@ def time_tensorflow_run(session, target, info_string):
 
   Args:
     session: the TensorFlow session to run the computation under.
-    target: the targe Tensor that is passed to the session's run() function.
+    target: the target Tensor that is passed to the session's run() function.
     info_string: a string summarizing this run, to be printed with the stats.
 
   Returns:
diff --git a/tensorflow/models/image/cifar10/cifar10.py b/tensorflow/models/image/cifar10/cifar10.py
@@ -301,7 +301,7 @@ def _add_loss_summaries(total_loss):
   losses = tf.get_collection('losses')
   loss_averages_op = loss_averages.apply(losses + [total_loss])
 
-  # Attach a scalar summmary to all individual losses and the total loss; do the
+  # Attach a scalar summary to all individual losses and the total loss; do the
   # same for the averaged version of the losses.
   for l in losses + [total_loss]:
     # Name each loss as '(raw)' and name the moving average version of the loss
@@ -384,5 +384,5 @@ def _progress(count, block_size, total_size):
                                              reporthook=_progress)
     print()
     statinfo = os.stat(filepath)
-    print('Succesfully downloaded', filename, statinfo.st_size, 'bytes.')
+    print('Successfully downloaded', filename, statinfo.st_size, 'bytes.')
     tarfile.open(filepath, 'r:gz').extractall(dest_directory)
diff --git a/tensorflow/models/image/cifar10/cifar10_multi_gpu_train.py b/tensorflow/models/image/cifar10/cifar10_multi_gpu_train.py
@@ -95,7 +95,7 @@ def tower_loss(scope):
   loss_averages = tf.train.ExponentialMovingAverage(0.9, name='avg')
   loss_averages_op = loss_averages.apply(losses + [total_loss])
 
-  # Attach a scalar summmary to all individual losses and the total loss; do the
+  # Attach a scalar summary to all individual losses and the total loss; do the
   # same for the averaged version of the losses.
   for l in losses + [total_loss]:
     # Remove 'tower_[0-9]/' from the name in case this is a multi-GPU training
diff --git a/tensorflow/models/rnn/translate/data_utils.py b/tensorflow/models/rnn/translate/data_utils.py
@@ -255,7 +255,7 @@ def prepare_wmt_data(data_dir, en_vocabulary_size, fr_vocabulary_size):
       (3) path to the token-ids for English development data-set,
       (4) path to the token-ids for French development data-set,
       (5) path to the English vocabulary file,
-      (6) path to the French vocabluary file.
+      (6) path to the French vocabulary file.
   """
   # Get wmt data to the specified directory.
   train_path = get_wmt_enfr_train_set(data_dir)
diff --git a/tensorflow/models/rnn/translate/seq2seq_model.py b/tensorflow/models/rnn/translate/seq2seq_model.py
@@ -184,7 +184,7 @@ def step(self, session, encoder_inputs, decoder_inputs, target_weights,
       average perplexity, and the outputs.
 
     Raises:
-      ValueError: if length of enconder_inputs, decoder_inputs, or
+      ValueError: if length of encoder_inputs, decoder_inputs, or
         target_weights disagrees with bucket size for the specified bucket_id.
     """
     # Check if the sizes match.
