diff --git a/tensorflow/cc/framework/while_gradients.cc b/tensorflow/cc/framework/while_gradients.cc
index 0734075fc61..81870a0efa3 100644
--- a/tensorflow/cc/framework/while_gradients.cc
+++ b/tensorflow/cc/framework/while_gradients.cc
@@ -72,9 +72,9 @@ Status AddForwardLoopCounter(WhileContext* while_ctx, const Scope& scope,
};
// Body function that adds one to input.
- BodyGraphBuilderFn body_fn = [while_ctx](const Scope& scope,
- const std::vector<Output>& inputs,
- std::vector<Output>* outputs) {
+ BodyGraphBuilderFn body_fn = [](const Scope& scope,
+ const std::vector<Output>& inputs,
+ std::vector<Output>* outputs) {
DCHECK_EQ(inputs.size(), 1);
outputs->emplace_back(ops::Add(scope, inputs[0], 1));
return scope.status();
diff --git a/tensorflow/contrib/image/kernels/segmentation_ops.cc b/tensorflow/contrib/image/kernels/segmentation_ops.cc
index fe8bf6e21c7..93722896233 100644
--- a/tensorflow/contrib/image/kernels/segmentation_ops.cc
+++ b/tensorflow/contrib/image/kernels/segmentation_ops.cc
@@ -101,8 +101,8 @@ struct ImageConnectedComponentsFunctor<CPUDevice, T> {
int cost = (union_find.block_height() + union_find.block_width()) * 20;
Shard(worker_threads->num_threads, worker_threads->workers,
num_images * num_blocks_vertically * num_blocks_horizontally, cost,
- [&union_find, num_images, num_blocks_vertically,
- num_blocks_horizontally](int64 start_block, int64 limit_block) {
+ [&union_find, num_blocks_vertically, num_blocks_horizontally](
+ int64 start_block, int64 limit_block) {
for (int64 i = start_block; i < limit_block; i++) {
int64 block_x = i % num_blocks_horizontally;
int64 block_y =
diff --git a/tensorflow/core/common_runtime/memory_types.cc b/tensorflow/core/common_runtime/memory_types.cc
index 090a16ebeb1..116750fbfd6 100644
--- a/tensorflow/core/common_runtime/memory_types.cc
+++ b/tensorflow/core/common_runtime/memory_types.cc
@@ -92,7 +92,7 @@ static Status ProcessMemoryTypes(
Status ValidateMemoryTypes(const DeviceType& device_type, const Graph* g) {
return ProcessMemoryTypes(
- device_type, g, [g](const Edge* e, MemoryType sm, MemoryType dm) {
+ device_type, g, [](const Edge* e, MemoryType sm, MemoryType dm) {
if (sm == dm) {
return Status::OK();
}
@@ -155,7 +155,7 @@ Status EnsureMemoryTypes(const DeviceType& device_type,
};
std::vector<Item> edges;
TF_RETURN_IF_ERROR(ProcessMemoryTypes(
- device_type, g, [g, &edges](const Edge* e, MemoryType sm, MemoryType dm) {
+ device_type, g, [&edges](const Edge* e, MemoryType sm, MemoryType dm) {
if (sm == dm) {
return Status::OK();
}
diff --git a/tensorflow/core/distributed_runtime/graph_mgr.cc b/tensorflow/core/distributed_runtime/graph_mgr.cc
index 9768a244f20..8447c55bf43 100644
--- a/tensorflow/core/distributed_runtime/graph_mgr.cc
+++ b/tensorflow/core/distributed_runtime/graph_mgr.cc
@@ -438,7 +438,7 @@ void GraphMgr::ExecuteAsync(const string& handle, const int64 step_id,
StartParallelExecutors(handle, step_id, item, rendezvous, collector,
cost_graph, cancellation_manager,
- [this, item, rendezvous, done](const Status& s) {
+ [item, rendezvous, done](const Status& s) {
done(s);
rendezvous->Unref();
item->Unref();
diff --git a/tensorflow/core/distributed_runtime/worker.cc b/tensorflow/core/distributed_runtime/worker.cc
index 63455493671..598652fb981 100644
--- a/tensorflow/core/distributed_runtime/worker.cc
+++ b/tensorflow/core/distributed_runtime/worker.cc
@@ -215,7 +215,7 @@ void Worker::DoPartialRunGraph(CallOptions* opts,
GraphMgr::NamedTensors in;
GraphMgr::NamedTensors* out = new GraphMgr::NamedTensors;
Status s = PrepareRunGraph(request, &in, out);
- auto finish = [this, done, out, opts](const Status& s) {
+ auto finish = [done, out, opts](const Status& s) {
opts->ClearCancelCallback();
delete out;
done(s);
@@ -247,7 +247,7 @@ void Worker::DoPartialRunGraph(CallOptions* opts,
session->graph_mgr->ExecuteAsync(
graph_handle, step_id, session.get(), request->exec_opts(),
nullptr /* collector */, nullptr /* response */, cm, in,
- [this, token, step_id, session, cm](Status s) {
+ [this, token, step_id, session](Status s) {
{
mutex_lock l(mu_);
cancellation_manager_->DeregisterCallback(token);
diff --git a/tensorflow/core/kernels/data/iterator_ops.cc b/tensorflow/core/kernels/data/iterator_ops.cc
index 6fe3746a735..780f927a4f1 100644
--- a/tensorflow/core/kernels/data/iterator_ops.cc
+++ b/tensorflow/core/kernels/data/iterator_ops.cc
@@ -867,7 +867,7 @@ class IteratorGetNextOp : public AsyncOpKernel {
// inter-op thread pool thread, so we issue the call from the
// owned thread pool.
thread_pool_->Schedule(std::bind(
- [this, ctx, iterator](DoneCallback done) {
+ [ctx, iterator](DoneCallback done) {
std::vector<Tensor> components;
bool end_of_sequence = false;
diff --git a/tensorflow/core/kernels/mutex_ops.cc b/tensorflow/core/kernels/mutex_ops.cc
index b02a584d73d..ddb7a606c1a 100644
--- a/tensorflow/core/kernels/mutex_ops.cc
+++ b/tensorflow/core/kernels/mutex_ops.cc
@@ -127,7 +127,7 @@ class Mutex : public ResourceBase {
}
}
thread_pool_->Schedule(std::bind(
- [this, c, cm, cancelled,
+ [this, cm, cancelled,
token](std::function<void(const Status& s, SharedLockReleaser&& lock)>
fn_) {
bool local_locked;
@@ -173,7 +173,7 @@ class MutexLockOp : public AsyncOpKernel {
OP_REQUIRES_OK_ASYNC(
c,
LookupOrCreateResource<Mutex>(c, HandleFromInput(c, 0), &mutex,
- [this, c](Mutex** ptr) {
+ [c](Mutex** ptr) {
*ptr = new Mutex(
c, HandleFromInput(c, 0).name());
return Status::OK();
@@ -186,10 +186,10 @@ class MutexLockOp : public AsyncOpKernel {
mutex->AcquireAsync(
c, std::bind(
- [this, c, variant, mutex](DoneCallback done_,
- // End of bound arguments.
- const Status& s,
- Mutex::SharedLockReleaser&& lock) {
+ [c, variant, mutex](DoneCallback done_,
+ // End of bound arguments.
+ const Status& s,
+ Mutex::SharedLockReleaser&& lock) {
VLOG(2) << "Finished locking mutex " << mutex
<< " with lock: " << lock.shared_lock.get()
<< " status: " << s.ToString();
diff --git a/tensorflow/core/kernels/resource_variable_ops.cc b/tensorflow/core/kernels/resource_variable_ops.cc
index f254036ba7a..aecad0185fd 100644
--- a/tensorflow/core/kernels/resource_variable_ops.cc
+++ b/tensorflow/core/kernels/resource_variable_ops.cc
@@ -351,7 +351,7 @@ class AssignVariableOp<Device, Variant> : public OpKernel {
Var* variable = nullptr;
OP_REQUIRES_OK(context, LookupOrCreateResource<Var>(
context, HandleFromInput(context, 0), &variable,
- [this, context](Var** ptr) {
+ [](Var** ptr) {
// Created on host.
*ptr = new Var(DT_VARIANT);
return Status::OK();
diff --git a/tensorflow/core/kernels/sparse_cross_op.cc b/tensorflow/core/kernels/sparse_cross_op.cc
index 7cd4532ad63..4b5df7aff0e 100644
--- a/tensorflow/core/kernels/sparse_cross_op.cc
+++ b/tensorflow/core/kernels/sparse_cross_op.cc
@@ -327,7 +327,7 @@ class SparseCrossOp : public OpKernel {
typename CrossTraits<HASHED_OUTPUT, InternalType>::Updater updater(
output_start_indices, indices_out, values_out);
- auto do_work = [this, &columns, crosser, updater](int64 begin, int64 end) {
+ auto do_work = [&columns, crosser, updater](int64 begin, int64 end) {
for (int b = begin; b < end; b++) {
ProductIterator<InternalType> product_iterator(columns, b);
int64 cross_count = 0;
diff --git a/tensorflow/core/kernels/split_v_op.cc b/tensorflow/core/kernels/split_v_op.cc
index 0ce0b552e63..5c19a45fb18 100644
--- a/tensorflow/core/kernels/split_v_op.cc
+++ b/tensorflow/core/kernels/split_v_op.cc
@@ -208,10 +208,10 @@ class SplitVOpCPUImpl {
input_element_count >= std::max(num_threads, num_split) * 4096 &&
input_element_count < num_split * 180 * 1024);
- auto range_output_func = [&indices, context, &input_shape, prefix_dim_size,
- split_dim, &split_sizes_vec, &split_start_points,
- suffix_dim_size, use_parallelism_between_outputs,
- &input_reshaped, &make_sizes,
+ auto range_output_func = [&indices, context, &input_shape, split_dim,
+ &split_sizes_vec, &split_start_points,
+ use_parallelism_between_outputs, &input_reshaped,
+ &make_sizes,
&reshape_result](int64 start, int64 limit) {
for (int64 i = start; i < limit; ++i) {
TensorShape output_shape(input_shape);