Fix typos

tensorflow/contrib/autograph/operators/control_flow.py

@@ -141,7 +141,7 @@ def while_cond(epoch_number, iterate, *state):
         while_body,
         init_state=(epoch_number, iterate) + init_state,
         extra_deps=())
-  # Dropping the epoch number and iterate because they are not not syntactically
+  # Dropping the epoch number and iterate because they are not syntactically
   # visible.
   results = results[2:]
 

tensorflow/contrib/autograph/pyct/static_analysis/reaching_definitions.py

@@ -39,7 +39,7 @@
 class Definition(object):
   """Definition objects describe a unique definition of a variable.
 
-  Subclasses of this may be used by passing an appropriate factory fuction to
+  Subclasses of this may be used by passing an appropriate factory function to
   resolve.
 
   Attributes:

tensorflow/contrib/bigtable/python/ops/bigtable_api.py

@@ -331,7 +331,7 @@ def parallel_scan_prefix(self,
     """Retrieves row (including values) from the Bigtable service at high speed.
 
     Rows with row-key prefixed by `prefix` will be retrieved. This method is
-    similar to `scan_prefix`, but by constrast performs multiple sub-scans in
+    similar to `scan_prefix`, but by contrast performs multiple sub-scans in
     parallel in order to achieve higher performance.
 
     Note: The dataset produced by this method is not deterministic!
@@ -390,7 +390,7 @@ def parallel_scan_range(self,
     """Retrieves rows (including values) from the Bigtable service.
 
     Rows with row-keys between `start` and `end` will be retrieved. This method
-    is similar to `scan_range`, but by constrast performs multiple sub-scans in
+    is similar to `scan_range`, but by contrast performs multiple sub-scans in
     parallel in order to achieve higher performance.
 
     Note: The dataset produced by this method is not deterministic!

tensorflow/contrib/constrained_optimization/python/swap_regret_optimizer.py

@@ -150,7 +150,7 @@ def _project_stochastic_matrix_wrt_euclidean_norm(matrix):
         "matrix must be two dimensional (instead is %d-dimensional)" %
         matrix_shape.ndims)
   if matrix_shape[0] != matrix_shape[1]:
-    raise ValueError("matrix must be be square (instead has shape (%d,%d))" %
+    raise ValueError("matrix must be square (instead has shape (%d,%d))" %
                      (matrix_shape[0], matrix_shape[1]))
   dimension = matrix_shape[0].value
   if dimension is None:

tensorflow/contrib/distributions/python/ops/sample_stats.py

@@ -134,7 +134,7 @@ def auto_correlation(
     x_len = util.prefer_static_shape(x_rotated)[-1]
 
     # TODO(langmore) Investigate whether this zero padding helps or hurts.  At
-    # the moment is is necessary so that all FFT implementations work.
+    # the moment is necessary so that all FFT implementations work.
     # Zero pad to the next power of 2 greater than 2 * x_len, which equals
     # 2**(ceil(Log_2(2 * x_len))).  Note: Log_2(X) = Log_e(X) / Log_e(2).
     x_len_float64 = math_ops.cast(x_len, np.float64)
@@ -198,7 +198,7 @@ def auto_correlation(
     # Recall R[m] is a sum of N / 2 - m nonzero terms x[n] Conj(x[n - m]).  The
     # other terms were zeros arising only due to zero padding.
     # `denominator = (N / 2 - m)` (defined below) is the proper term to
-    # divide by by to make this an unbiased estimate of the expectation
+    # divide by to make this an unbiased estimate of the expectation
     # E[X[n] Conj(X[n - m])].
     x_len = math_ops.cast(x_len, dtype.real_dtype)
     max_lags = math_ops.cast(max_lags, dtype.real_dtype)

tensorflow/contrib/lite/toco/model.h

@@ -2009,7 +2009,7 @@ class Model {
   std::size_t transient_data_size = 0;
   // For code-generation only: required alignment of the transient_data buffer
   std::size_t transient_data_alignment = 0;
-  // Arithmatic operations performed in the model.
+  // Arithmetic operations performed in the model.
   int64 ops_count = 0;
 
  private:

tensorflow/contrib/model_pruning/python/layers/layers.py

@@ -139,7 +139,7 @@ def masked_convolution(inputs,
       with "NC".
     num_outputs: Integer, the number of output filters.
     kernel_size: A sequence of N positive integers specifying the spatial
-      dimensions of of the filters.  Can be a single integer to specify the same
+      dimensions of the filters.  Can be a single integer to specify the same
       value for all spatial dimensions.
     stride: A sequence of N positive integers specifying the stride at which to
       compute output.  Can be a single integer to specify the same value for all

tensorflow/contrib/quantize/python/quant_ops_test.py

@@ -75,7 +75,7 @@ def testMovingAvgQuantizeTrainingAssign(self):
       self.assertGreater(max_value, 0.0)
       self.assertLess(max_value, 1.0)
 
-  def testVariablesNotParitioned_LastValue(self):
+  def testVariablesNotPartitioned_LastValue(self):
     # Variables added should not use a default partiioner since they are
     # scalar. There would be a tensorflow error thrown if the partitioner was
     # respected by the rewrite.
@@ -90,7 +90,7 @@ def testVariablesNotParitioned_LastValue(self):
             is_training=True,
             vars_collection=_MIN_MAX_VARS)
 
-  def testVariablesNotParitioned_MovingAvg(self):
+  def testVariablesNotPartitioned_MovingAvg(self):
     # Variables added should not use a default partiioner since they are
     # scalar. There would be a tensorflow error thrown if the partitioner was
     # respected by the rewrite.

tensorflow/core/framework/function.h

@@ -456,7 +456,7 @@ class FunctionLibraryRuntime {
 
     // This interface is EXPERIMENTAL and subject to change.
     //
-    // Instatiates the function using an executor of the given type. If empty,
+    // Instantiates the function using an executor of the given type. If empty,
     // the default TensorFlow executor will be used.
     string executor_type;
   };

tensorflow/python/ops/image_ops_test.py

@@ -1956,7 +1956,7 @@ def testZeroLengthInput(self):
           "all dims of 'image.shape' must be > 0",
           use_tensor_inputs_options=[False])
 
-      # The orignal error message does not contain back slashes. However, they
+      # The original error message does not contain back slashes. However, they
       # are added by either the assert op or the runtime. If this behavior
       # changes in the future, the match string will also needs to be changed.
       self._assertRaises(
@@ -2985,7 +2985,7 @@ def testZeroLengthInput(self):
           "all dims of 'image.shape' must be > 0",
           use_tensor_inputs_options=[False])
 
-      # The orignal error message does not contain back slashes. However, they
+      # The original error message does not contain back slashes. However, they
       # are added by either the assert op or the runtime. If this behavior
       # changes in the future, the match string will also needs to be changed.
       self._assertRaises(

tensorflow/python/ops/parallel_for/pfor.py

@@ -2117,7 +2117,7 @@ def _convert_print(pfor_input):
 # 2a Elements written to the array are "stacked"
 # To simulate multiple TensorArrays, we may increase the dimension of each
 # element of the array. i.e. the i_th row of the j_th entry of the converted
-# TensorArray corresponds to to the j_th entry of the TensorArray in the i_th
+# TensorArray corresponds to the j_th entry of the TensorArray in the i_th
 # pfor iteration.
 #
 # 2b Elements written to the array are "unstacked"

tensorflow/python/training/ftrl.py

@@ -86,7 +86,7 @@ def __init__(self,
 
     if initial_accumulator_value < 0.0:
       raise ValueError(
-          "initial_accumulator_value %f needs to be be positive or zero" %
+          "initial_accumulator_value %f needs to be positive or zero" %
           initial_accumulator_value)
     if learning_rate_power > 0.0:
       raise ValueError("learning_rate_power %f needs to be negative or zero" %