Merge pull request tensorflow#9844 from chris-chris/patch/170511-misspell

benoitsteiner · web-flow · commit 33cd434e24e8 · 2017-05-11T22:08:17.000-07:00
Fix misspells on c++ codes.
diff --git a/tensorflow/cc/framework/gradients_test.cc b/tensorflow/cc/framework/gradients_test.cc
@@ -260,7 +260,7 @@ TEST_F(GradientsTest, StackUnstack_StopBackprop) {
 }
 
 TEST_F(GradientsTest, DependentGradOutputs) {
-  // Tests that dependant gradients (in this case the gradients w.r.t to the
+  // Tests that dependent gradients (in this case the gradients w.r.t to the
   // output and one input of MatMul) are computed properly.
 
   // Create two chained MatMul ops.
diff --git a/tensorflow/cc/saved_model/loader.cc b/tensorflow/cc/saved_model/loader.cc
@@ -36,7 +36,7 @@ auto* load_attempt_count = monitoring::Counter<2>::New(
     "status");
 auto* load_latency = monitoring::Counter<1>::New(
     "/tensorflow/cc/saved_model/load_latency",
-    "Latency in microseconds for SavedModels that were succesfully loaded.",
+    "Latency in microseconds for SavedModels that were successfully loaded.",
     "model_path");
 constexpr char kLoadAttemptFail[] = "fail";
 constexpr char kLoadAttemptSuccess[] = "success";
diff --git a/tensorflow/compiler/xla/service/gpu/elemental_ir_emitter.cc b/tensorflow/compiler/xla/service/gpu/elemental_ir_emitter.cc
@@ -113,7 +113,7 @@ StatusOr<llvm::Value*> GpuElementalIrEmitter::EmitMathCall(
     tensorflow::gtl::ArraySlice<llvm::Value*> operands,
     tensorflow::gtl::ArraySlice<PrimitiveType> input_types,
     PrimitiveType output_type) const {
-  // Binary math functions tranform are of type [T] -> T.
+  // Binary math functions transform are of type [T] -> T.
   for (PrimitiveType input_type : input_types) {
     if (output_type != input_type) {
       return Unimplemented("Input type ≠ output type: %s ≠ %s",
diff --git a/tensorflow/compiler/xla/service/gpu/ir_emitter.cc b/tensorflow/compiler/xla/service/gpu/ir_emitter.cc
@@ -399,7 +399,7 @@ Status IrEmitter::HandleDot(HloInstruction* dot,
   llvm::Type* accum_type = target_array.GetElementLlvmType();
   llvm::Value* accum_address = llvm_ir::EmitAllocaAtFunctionEntry(
       accum_type,       // The pointee type of the alloca instruction.
-      "accum_address",  // The name of the alloca instuction.
+      "accum_address",  // The name of the alloca instruction.
       &ir_builder_);
 
   // Initialize the accumulator in the preheader to zero.
diff --git a/tensorflow/compiler/xla/service/gpu/llvm_gpu_backend/gpu_backend_lib.cc b/tensorflow/compiler/xla/service/gpu/llvm_gpu_backend/gpu_backend_lib.cc
@@ -396,7 +396,7 @@ StatusOr<string> CompileModuleToPtx(llvm::Module* module,
 
   // The LLVM IR verifier performs sanity checking on the IR. This helps
   // discover problems and report them in a meaningful manner, rather than let
-  // later passes report obscure assertions becasue of unfulfilled invariants.
+  // later passes report obscure assertions because of unfulfilled invariants.
   module_passes.add(llvm::createVerifierPass());
 
   // Create the function-level pass manager. It needs data layout information
diff --git a/tensorflow/compiler/xla/service/gpu/while_transformer.cc b/tensorflow/compiler/xla/service/gpu/while_transformer.cc
@@ -168,7 +168,7 @@ class MatcherBase {
   virtual ~MatcherBase() {}
 
   // Attempts to match each ExprTree in 'expr_trees_'.
-  // Returns OK on the first succesful match, error status otherwise.
+  // Returns OK on the first successful match, error status otherwise.
   virtual tensorflow::Status Run() {
     Status status;
     for (const ExprTree& expr_tree : expr_trees_) {
diff --git a/tensorflow/compiler/xla/service/layout_assignment.cc b/tensorflow/compiler/xla/service/layout_assignment.cc
@@ -1041,7 +1041,7 @@ StatusOr<Layout> InferArrayLayout(
                                   *first_buffer_layout)) {
       // The points-to set is ambiguous for this index and the different source
       // buffers have different layouts. This case is possible in valid XLA
-      // computations because we do not propagate BufferLayoutConstaints to all
+      // computations because we do not propagate BufferLayoutConstraints to all
       // LogicalBuffers which may alias the constrained LogicalBuffer at some
       // point in the computation.
       return FailedPrecondition(
@@ -1254,7 +1254,7 @@ Status LayoutAssignment::RunOnComputation(
   TF_ASSIGN_OR_RETURN(auto points_to_analysis,
                       TuplePointsToAnalysis::Run(computation->parent()));
 
-  // Construct LayoutConstaints with all layout constraints of the computation.
+  // Construct LayoutConstraints with all layout constraints of the computation.
   LayoutConstraints constraints(*points_to_analysis, computation);
 
   // Add constraints required for correctness on all backends (eg, entry
diff --git a/tensorflow/compiler/xla/tests/deallocation_test.cc b/tensorflow/compiler/xla/tests/deallocation_test.cc
@@ -52,7 +52,7 @@ TEST_F(DeallocationTest, DeallocateScalar) {
   builder.ConstantR0<float>(42.0);
   auto global_data = ExecuteAndCheckTransfer(&builder, {});
 
-  // A result can be transfered an arbitrary number of times.  Add an extra
+  // A result can be transferred an arbitrary number of times.  Add an extra
   // transfer here so we're not just testing that a second call to Transfer
   // fails.
   ASSERT_IS_OK(client_->Transfer(*global_data).status());
diff --git a/tensorflow/compiler/xla/tests/literal_test_util.cc b/tensorflow/compiler/xla/tests/literal_test_util.cc
@@ -314,7 +314,7 @@ class NearComparator {
 
  private:
   // EXPECTs that the two given scalar values are within the error bound. Keeps
-  // track of how many mismatches have occured to keep the size of the output
+  // track of how many mismatches have occurred to keep the size of the output
   // manageable.
   template <typename NativeT>
   bool ExpectValuesNear(NativeT expected, NativeT actual) {
diff --git a/tensorflow/compiler/xla/tests/reduce_test.cc b/tensorflow/compiler/xla/tests/reduce_test.cc
@@ -61,7 +61,7 @@ namespace {
 class ReduceTest : public ClientLibraryTestBase {
  protected:
   ReduceTest() {
-    // Implementation note: layed out z >> y >> x by default.
+    // Implementation note: laid out z >> y >> x by default.
     // clang-format off
     literal_2d_ = LiteralUtil::CreateR2<float>({
       // x0   x1   x2
diff --git a/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary_test.cc b/tensorflow/contrib/boosted_trees/lib/quantiles/weighted_quantiles_summary_test.cc
@@ -75,7 +75,7 @@ TEST_F(WeightedQuantilesSummaryTest, BuildFromBuffer) {
   Summary summary;
   summary.BuildFromBufferEntries(buffer1_->GenerateEntryList());
 
-  // We expect no approximation error because no compress operation occured.
+  // We expect no approximation error because no compress operation occurred.
   EXPECT_EQ(summary.ApproximationError(), 0);
 
   // Check first and last elements in the summary.
diff --git a/tensorflow/contrib/opt/python/training/drop_stale_gradient_optimizer_test.py b/tensorflow/contrib/opt/python/training/drop_stale_gradient_optimizer_test.py
@@ -184,7 +184,7 @@ def test2WorkersStaleness0(self):
     thread_0.join()
     thread_1.join()
 
-    # With 2 workers and max staleness set to 0, only cheif worker will update
+    # With 2 workers and max staleness set to 0, only chief worker will update
     # var_0 and var_1.
     self.assertAllEqual(1, sessions[0].run(global_step))
     self.assertAllEqual(1.0, sessions[0].run(stale_counter))
@@ -250,7 +250,7 @@ def test3WorkersStaleness0(self):
     thread_1.join()
     thread_2.join()
 
-    # With 3 workers and max staleness set to 0, only cheif worker will update
+    # With 3 workers and max staleness set to 0, only chief worker will update
     # var_0 and var_1.
     self.assertAllEqual(1, sessions[0].run(global_step))
     self.assertAllEqual(2.0, sessions[0].run(stale_counter))
diff --git a/tensorflow/core/common_runtime/gpu/gpu_util.cc b/tensorflow/core/common_runtime/gpu/gpu_util.cc
@@ -227,7 +227,7 @@ void GPUUtil::DeviceToDeviceCopy(DeviceContext* send_dev_context,
     }
     // Since we want to use the memory from recv_stream in the
     // send_device_to_device_stream, add a dependency to make sure the memory is
-    // truely free.
+    // truly free.
     // TODO(zhengxq): remove this dependency when we switch to a better way
     // to make sure the memory is free.
     send_device_to_device_stream->ThenWaitFor(recv_stream);
@@ -322,7 +322,7 @@ void GPUUtil::CopyCPUTensorToGPU(const Tensor* cpu_tensor,
     done(errors::Internal("No send gpu copy-out-stream is available."));
     return;
   }
-  // Wait for the recv-stream to make sure the buffer is truely available.
+  // Wait for the recv-stream to make sure the buffer is truly available.
   recv_host_to_device_stream->ThenWaitFor(recv_stream);
 
   const int64 total_bytes = cpu_tensor->TotalBytes();
diff --git a/tensorflow/core/grappler/costs/measuring_cost_estimator.cc b/tensorflow/core/grappler/costs/measuring_cost_estimator.cc
@@ -73,7 +73,7 @@ Status MeasuringCostEstimator::PredictCosts(const GraphDef& optimized_graph,
       return;
     }
     if (!local_status.ok()) {
-      // Discard the data if the run wasn't sucessful.
+      // Discard the data if the run wasn't successful.
       barrier.DecrementCount();
       return;
     }
diff --git a/tensorflow/core/grappler/costs/robust_stats.cc b/tensorflow/core/grappler/costs/robust_stats.cc
@@ -47,7 +47,7 @@ static double Median(std::vector<double> &&values) {
   // nth_element.
   const auto lower_middle = std::max_element(values.begin(), middle);
   // Preventing overflow. We know that '*lower_middle <= *middle'.
-  // If both are on oposite sides of zero, the sum won't overflow, otherwise
+  // If both are on opposite sides of zero, the sum won't overflow, otherwise
   // the difference won't overflow.
   if (*lower_middle <= 0 && *middle >= 0) {
     return (*lower_middle + *middle) / 2;
diff --git a/tensorflow/core/kernels/basic_ops_benchmark_test.cc b/tensorflow/core/kernels/basic_ops_benchmark_test.cc
@@ -22,7 +22,7 @@ limitations under the License.
 
 namespace tensorflow {
 
-// We focus on the single thread performance of runing ops.
+// We focus on the single thread performance of running ops.
 static SessionOptions InitOptions() {
   SessionOptions opts;
   opts.config.set_intra_op_parallelism_threads(1);
diff --git a/tensorflow/core/kernels/deep_conv2d.cc b/tensorflow/core/kernels/deep_conv2d.cc
@@ -1069,7 +1069,7 @@ struct DeepConv2D<CPUDevice, T> {
       // Allocate temporary buffer 'buffer2', which is first used for
       // transformed input tiles, then re-used for transformed output tiles.
       // Calculate required buffer size for 'buffer2' as max required buffer
-      // between input and output tranform buffer sizes.
+      // between input and output transform buffer sizes.
       const int64 buffer2_tile_transform_size =
           tile_spatial_size * num_tiles * in_depth;
       const int64 buffer2_out_transform_size =
diff --git a/tensorflow/core/lib/gtl/inlined_vector_test.cc b/tensorflow/core/lib/gtl/inlined_vector_test.cc
@@ -816,7 +816,7 @@ static void BM_StdVectorFillString(int iters, int len) {
   }
   testing::ItemsProcessed(int64{iters} * len);
   // The purpose of the benchmark is to verify that inlined vector is
-  // efficient when moving is more efficent than copying. To do so, we
+  // efficient when moving is more efficient than copying. To do so, we
   // use strings that are larger than the small string optimization.
   CHECK(!StringRepresentedInline(strings[0]));
 }
diff --git a/tensorflow/core/ops/sdca_ops.cc b/tensorflow/core/ops/sdca_ops.cc
@@ -105,7 +105,7 @@ example_weights: a vector which contains the weight associated with each
 example_labels: a vector which contains the label/target associated with each
   example.
 sparse_indices: a list of vectors where each value is the indices which has
-  corresponding weights in sparse_weights. This field maybe ommitted for the
+  corresponding weights in sparse_weights. This field maybe omitted for the
   dense approach.
 sparse_weights: a list of vectors where each value is the weight associated with
   a sparse feature group.
diff --git a/tensorflow/core/platform/cloud/google_auth_provider.cc b/tensorflow/core/platform/cloud/google_auth_provider.cc
@@ -67,7 +67,7 @@ constexpr char kGceTokenUrl[] =
 // The authentication token scope to request.
 constexpr char kOAuthScope[] = "https://www.googleapis.com/auth/cloud-platform";
 
-// The default intial delay between retries with exponential backoff.
+// The default initial delay between retries with exponential backoff.
 constexpr int kInitialRetryDelayUsec = 500000;  // 0.5 sec
 
 /// Returns whether the given path points to a readable file.

Original file line number	Diff line number	Diff line change
`@@ -260,7 +260,7 @@ TEST_F(GradientsTest, StackUnstack_StopBackprop) {`
`260`	`260`	`}`
`261`	`261`
`262`	`262`	`TEST_F(GradientsTest, DependentGradOutputs) {`
`263`		`- // Tests that dependant gradients (in this case the gradients w.r.t to the`
	`263`	`+ // Tests that dependent gradients (in this case the gradients w.r.t to the`
`264`	`264`	`// output and one input of MatMul) are computed properly.`
`265`	`265`
`266`	`266`	`// Create two chained MatMul ops.`