Wrap macro bodies in do{}while(0) to prevent capture of else-clauses.

PiperOrigin-RevId: 178202725

6 files changed, 34 insertions, 27 deletions

diff --git a/tensorflow/contrib/nearest_neighbor/kernels/hyperplane_lsh_probes.cc b/tensorflow/contrib/nearest_neighbor/kernels/hyperplane_lsh_probes.cc
index 62ee6630ac..2b412fac9a 100644
--- a/tensorflow/contrib/nearest_neighbor/kernels/hyperplane_lsh_probes.cc
+++ b/tensorflow/contrib/nearest_neighbor/kernels/hyperplane_lsh_probes.cc
@@ -45,16 +45,16 @@ class HyperplaneLSHProbesOp : public OpKernel {
     const Tensor& products_tensor = context->input(0);
     OP_REQUIRES(context, products_tensor.dims() == 2,
                 InvalidArgument("Need a two-dimensional products tensor, got ",
-                                products_tensor.dims(), " dimensions."))
+                                products_tensor.dims(), " dimensions."));
 
     const Tensor& num_tables_tensor = context->input(1);
     OP_REQUIRES(context, num_tables_tensor.dims() == 0,
                 InvalidArgument("Need a scalar num_tables tensor, got ",
-                                num_tables_tensor.dims(), " dimensions."))
+                                num_tables_tensor.dims(), " dimensions."));
     int num_tables = num_tables_tensor.scalar<int32>()();
     OP_REQUIRES(context, num_tables >= 1,
                 InvalidArgument("num_tables must be at least 1 but got ",
-                                num_tables, "."))
+                                num_tables, "."));
     OP_REQUIRES(context, num_tables <= 1000,
                 InvalidArgument("Need num_tables <= 1000, got ", num_tables,
                                 ". This is mostly to protect against incorrect "
@@ -66,12 +66,13 @@ class HyperplaneLSHProbesOp : public OpKernel {
                 InvalidArgument("Need a scalar num_hyperplanes_per_table "
                                 "tensor, got ",
                                 num_hyperplanes_per_table_tensor.dims(),
-                                " dimensions."))
+                                " dimensions."));
     int num_hyperplanes_per_table =
         num_hyperplanes_per_table_tensor.scalar<int32>()();
     OP_REQUIRES(context, num_hyperplanes_per_table >= 1,
                 InvalidArgument("num_hyperplanes_per_table must be at least 1 "
-                                "but got ", num_hyperplanes_per_table, "."))
+                                "but got ",
+                                num_hyperplanes_per_table, "."));
     OP_REQUIRES(context, num_hyperplanes_per_table <= 30,
                 InvalidArgument("Need num_hyperplanes_per_table <= 30, got ",
                                 num_hyperplanes_per_table, ". "
@@ -81,10 +82,10 @@ class HyperplaneLSHProbesOp : public OpKernel {
     const Tensor& num_probes_tensor = context->input(3);
     OP_REQUIRES(context, num_probes_tensor.dims() == 0,
                 InvalidArgument("Need a scalar num_probes tensor, got ",
-                                num_probes_tensor.dims(), " dimensions."))
+                                num_probes_tensor.dims(), " dimensions."));
     int num_probes = num_probes_tensor.scalar<int32>()();
     OP_REQUIRES(context, num_probes >= 1,
-                InvalidArgument("num_probes must be at least 1."))
+                InvalidArgument("num_probes must be at least 1."));
 
     int expected_num_hyperplanes = num_tables * num_hyperplanes_per_table;
     OP_REQUIRES(
diff --git a/tensorflow/contrib/resampler/kernels/resampler_ops.cc b/tensorflow/contrib/resampler/kernels/resampler_ops.cc
index 7d9ef14cef..e02c1b6a2b 100644
--- a/tensorflow/contrib/resampler/kernels/resampler_ops.cc
+++ b/tensorflow/contrib/resampler/kernels/resampler_ops.cc
@@ -406,10 +406,10 @@ class ResamplerGradOp : public ::tensorflow::OpKernel {
                                    data_channels);
     OP_REQUIRES(ctx, grad_output_shape == resampler_output_shape,
                 ::tensorflow::errors::InvalidArgument(
-                   "grad_output shape is not consistent with data and warp "
-                   "shapes; it should be ",
-                   resampler_output_shape.DebugString(), " but is ",
-                   grad_output_shape.DebugString()))
+                    "grad_output shape is not consistent with data and warp "
+                    "shapes; it should be ",
+                    resampler_output_shape.DebugString(), " but is ",
+                    grad_output_shape.DebugString()));
     const int num_sampling_points = warp.NumElements() / batch_size / 2;
     ::tensorflow::Tensor* grad_data = nullptr;
     ::tensorflow::Tensor* grad_warp = nullptr;
diff --git a/tensorflow/core/framework/op_kernel.h b/tensorflow/core/framework/op_kernel.h
index a7b9bb393d..3a9a6121c0 100644
--- a/tensorflow/core/framework/op_kernel.h
+++ b/tensorflow/core/framework/op_kernel.h
@@ -1492,10 +1492,12 @@ inline void OpOutputList::set_ref(int i, mutex* mu, Tensor* tensor_for_ref) {
 // }
 
 #define OP_REQUIRES(CTX, EXP, STATUS) \
-  if (!TF_PREDICT_TRUE(EXP)) {        \
-    (CTX)->CtxFailure((STATUS));      \
-    return;                           \
-  }
+  do {                                \
+    if (!TF_PREDICT_TRUE(EXP)) {      \
+      (CTX)->CtxFailure((STATUS));    \
+      return;                         \
+    }                                 \
+  } while (0)
 
 #define OP_REQUIRES_OK(CTX, ...)          \
   do {                                    \
@@ -1507,11 +1509,13 @@ inline void OpOutputList::set_ref(int i, mutex* mu, Tensor* tensor_for_ref) {
   } while (0)
 
 #define OP_REQUIRES_ASYNC(CTX, EXP, STATUS, CALLBACK) \
-  if (!TF_PREDICT_TRUE(EXP)) {                        \
-    (CTX)->CtxFailure((STATUS));                      \
-    (CALLBACK)();                                     \
-    return;                                           \
-  }
+  do {                                                \
+    if (!TF_PREDICT_TRUE(EXP)) {                      \
+      (CTX)->CtxFailure((STATUS));                    \
+      (CALLBACK)();                                   \
+      return;                                         \
+    }                                                 \
+  } while (0)
 
 #define OP_REQUIRES_OK_ASYNC(CTX, STATUS, CALLBACK) \
   do {                                              \
diff --git a/tensorflow/core/kernels/conditional_accumulator_base.h b/tensorflow/core/kernels/conditional_accumulator_base.h
index 05ee855dae..27db6ee785 100644
--- a/tensorflow/core/kernels/conditional_accumulator_base.h
+++ b/tensorflow/core/kernels/conditional_accumulator_base.h
@@ -162,10 +162,12 @@ class ConditionalAccumulatorBase : public ResourceBase {
  * function can get an indication that a failure has occurred.
 */
 #define OP_REQUIRES_BOOLEAN(CTX, EXP, STATUS) \
-  if (!TF_PREDICT_TRUE(EXP)) {                \
-    (CTX)->CtxFailure((STATUS));              \
-    return false;                             \
-  }
+  do {                                        \
+    if (!TF_PREDICT_TRUE(EXP)) {              \
+      (CTX)->CtxFailure((STATUS));            \
+      return false;                           \
+    }                                         \
+  } while (0)
 
 #define OP_REQUIRES_OK_BOOLEAN(CTX, STATUS) \
   do {                                      \
diff --git a/tensorflow/core/kernels/quantized_concat_op.cc b/tensorflow/core/kernels/quantized_concat_op.cc
index ee573f1bb8..d67f1ab3ec 100644
--- a/tensorflow/core/kernels/quantized_concat_op.cc
+++ b/tensorflow/core/kernels/quantized_concat_op.cc
@@ -174,13 +174,13 @@ class QuantizedConcatOp : public OpKernel {
     OP_REQUIRES(context, (input_mins.size() == N),
                 errors::InvalidArgument(
                     "QuantizedConcatOp : Expected mins input list length ",
-                    input_mins.size(), " to equal values length ", N))
+                    input_mins.size(), " to equal values length ", N));
     OpInputList input_maxes;
     OP_REQUIRES_OK(context, context->input_list("input_maxes", &input_maxes));
     OP_REQUIRES(context, (input_maxes.size() == N),
                 errors::InvalidArgument(
                     "QuantizedConcatOp : Expected maxes input list length ",
-                    input_maxes.size(), " to equal values length ", N))
+                    input_maxes.size(), " to equal values length ", N));
     const int input_dims = values[0].dims();
     const TensorShape& input_shape = values[0].shape();
     OP_REQUIRES(
diff --git a/tensorflow/core/kernels/variable_ops.h b/tensorflow/core/kernels/variable_ops.h
index 355140d44c..820b90d041 100644
--- a/tensorflow/core/kernels/variable_ops.h
+++ b/tensorflow/core/kernels/variable_ops.h
@@ -160,7 +160,7 @@ class DestroyTemporaryVariableOp : public OpKernel {
   explicit DestroyTemporaryVariableOp(OpKernelConstruction* context)
       : OpKernel(context) {
     OP_REQUIRES(context, IsRefType(context->input_type(0)),
-                errors::InvalidArgument("lhs input needs to be a ref type"))
+                errors::InvalidArgument("lhs input needs to be a ref type"));
     OP_REQUIRES_OK(context, context->GetAttr("var_name", &var_name_));
     OP_REQUIRES(context, var_name_ != "",
                 errors::InvalidArgument("Missing var_name attribute"));