"the the" -> "the"

tensorflower-gardener · tensorflower-gardener · commit b619ca9750ee · 2017-02-21T17:24:32.000-08:00
Change: 148163782
diff --git a/tensorflow/compiler/xla/literal_util.h b/tensorflow/compiler/xla/literal_util.h
@@ -127,7 +127,7 @@ class LiteralUtil {
   static std::unique_ptr<Literal> Transpose(
       const Literal& literal, tensorflow::gtl::ArraySlice<int64> permutation);
 
-  // Creates a sub-array from the the given literal by extracting the indices
+  // Creates a sub-array from the given literal by extracting the indices
   // [start_index, limit_index) of each dimension. The result literal has the
   // same rank and layout as for the given literal. The number of indices in
   // start_indices and limit_indices must be the rank of the literal, and the
diff --git a/tensorflow/compiler/xla/shape_util.h b/tensorflow/compiler/xla/shape_util.h
@@ -227,7 +227,7 @@ class ShapeUtil {
   // Validates that the provided shape satisfies invariants.
   static Status ValidateShape(const Shape& shape);
 
-  // Validates the the provided shape satisfies invariants, except those that
+  // Validates the provided shape satisfies invariants, except those that
   // pertain to layout.
   //
   // Layout is optional for client-provided shapes, so that the compiler may
diff --git a/tensorflow/contrib/linalg/python/ops/linear_operator_addition.py b/tensorflow/contrib/linalg/python/ops/linear_operator_addition.py
@@ -138,7 +138,7 @@ def add_operators(operators,
 
 
 def _pop_a_match_at_tier(op1, operator_list, tier):
-  # Search from the back of list the the front in order to create nice default
+  # Search from the back of list to the front in order to create nice default
   # order of operations.
   for i in range(1, len(operator_list) + 1):
     op2 = operator_list[-i]
diff --git a/tensorflow/core/kernels/meta_support.cc b/tensorflow/core/kernels/meta_support.cc
@@ -332,7 +332,7 @@ void Quantize(OpKernelContext* tf_context, const float* input, int count,
   // The float to int/uint cast in NEON uses round toward 0. To keep the
   // rounding consistent with Eigen, which uses round toward closest, we can
   // add 0.5f and exploit the fact that we only operate on non negative values.
-  // TODO(maciekc): fix the the actual kernel in gemmlowp/meta
+  // TODO(maciekc): fix the actual kernel in gemmlowp/meta
   params.kernel.range_offset =
       static_cast<float>(std::numeric_limits<uint8_t>::lowest()) + 0.5f;
 
diff --git a/tensorflow/examples/android/jni/object_tracking/image-inl.h b/tensorflow/examples/android/jni/object_tracking/image-inl.h
@@ -452,7 +452,7 @@ void Image<T>::DownsampleSmoothed5x5(const Image<T>& original) {
                                        4, 16, 24, 16, 4,   // 64 +
                                        1,  4,  6,  4, 1};  // 16 = 256
 
-  // We'll multiply and sum with the the whole numbers first, then divide by
+  // We'll multiply and sum with the whole numbers first, then divide by
   // the total weight to normalize at the last moment.
   for (int y = 0; y < height_; ++y) {
     for (int x = 0; x < width_; ++x) {
diff --git a/tensorflow/python/debug/cli/cli_shared.py b/tensorflow/python/debug/cli/cli_shared.py
@@ -203,7 +203,7 @@ def _recommend_command(command, description, indent=2, create_link=False):
 
   Args:
     command: (str) The command to recommend.
-    description: (str) A description of what the the command does.
+    description: (str) A description of what the command does.
     indent: (int) How many spaces to indent in the beginning.
     create_link: (bool) Whether a command link is to be applied to the command
       string.
diff --git a/tensorflow/python/ops/linalg_ops.py b/tensorflow/python/ops/linalg_ops.py
@@ -333,7 +333,7 @@ def norm(tensor, ord='euclidean', axis=None, keep_dims=False, name=None):
   Mostly equivalent to numpy.linalg.norm.
   Not supported: ord <= 0, 2-norm for matrices, nuclear norm.
   Other differences:
-    a) If axis is `None`, treats the the flattened `tensor` as a vector
+    a) If axis is `None`, treats the flattened `tensor` as a vector
      regardless of rank.
     b) Explicitly supports 'euclidean' norm as the default, including for
      higher order tensors.
diff --git a/tensorflow/tensorboard/components/tf_graph_common/lib/scene/node.ts b/tensorflow/tensorboard/components/tf_graph_common/lib/scene/node.ts
@@ -1039,7 +1039,7 @@ function _markParentsOfNodes(visibleNodes: {[nodeName: string]: Node}) {
 /**
  * Find the parent of the passed in op node which is expanded. This is done
  * by going through all parents until the parent's parent is expanded, thus
- * finding the the first unexpanded parent which is rendered on the screen.
+ * finding the first unexpanded parent which is rendered on the screen.
  * @param renderGraphInfo The graph info object used to gain access to the
  * render info of the parents.
  * @param currentNode The node whose parent is to be found.
diff --git a/tensorflow/tensorboard/dist/tf-tensorboard.html b/tensorflow/tensorboard/dist/tf-tensorboard.html
@@ -11660,7 +11660,7 @@ <h3 id="tooltip-help" class="tooltip-container">
                 /**
                  * Find the parent of the passed in op node which is expanded. This is done
                  * by going through all parents until the parent's parent is expanded, thus
-                 * finding the the first unexpanded parent which is rendered on the screen.
+                 * finding the first unexpanded parent which is rendered on the screen.
                  * @param renderGraphInfo The graph info object used to gain access to the
                  * render info of the parents.
                  * @param currentNode The node whose parent is to be found.
@@ -24937,4 +24937,4 @@ <h2>Settings</h2>
 },{"dup":8}]},{},[35,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34]);
 </script>
 </dom-module>
-</body></html>
+</body></html>
diff --git a/third_party/eigen3/unsupported/Eigen/CXX11/src/NeuralNetworks/Activations.h b/third_party/eigen3/unsupported/Eigen/CXX11/src/NeuralNetworks/Activations.h
@@ -80,11 +80,11 @@ struct functor_traits<scalar_tanh_fast_derivative_op<T> > {
 }  // namespace internal
 
 /**
-  * \ingroup CXX11_NeuralNetworks_Module
-  * \brief Template functor to clip the the magnitude of the first scalar.
-  *
-  * \sa class CwiseBinaryOp, MatrixBase::Clip
-  */
+ * \ingroup CXX11_NeuralNetworks_Module
+ * \brief Template functor to clip the magnitude of the first scalar.
+ *
+ * \sa class CwiseBinaryOp, MatrixBase::Clip
+ */
 template <typename Scalar>
 struct scalar_clip_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_clip_op)
