Fix warnings.

Fixes #9138.
* lstm_ops: use_peephole checked twice, merged "if" bodies.
* unpack_path_op: cast to 1LL for shift to operate on full range.
* sample_input_ops: add CHECK to ensure that sparse_input_start is
initialized.
* function: make sure we deref "e" after checking for nullptr
* master_session: remove unused variable
* encode_jpeg_op: remove double assignment
* resize_area_op: use unused variable
* strcat: remove double parentheses

PiperOrigin-RevId: 159443547

8 files changed, 10 insertions, 14 deletions

diff --git a/tensorflow/contrib/rnn/kernels/lstm_ops.h b/tensorflow/contrib/rnn/kernels/lstm_ops.h
index d9ed9e3ab7..6317f32ac3 100644
--- a/tensorflow/contrib/rnn/kernels/lstm_ops.h
+++ b/tensorflow/contrib/rnn/kernels/lstm_ops.h
@@ -279,9 +279,6 @@ struct LSTMBlockCellBprop : public LSTMBlockCell {
           cs_prev_grad +
           di * wci.reshape(p_shape).broadcast(p_broadcast_shape) +
           df * wcf.reshape(p_shape).broadcast(p_broadcast_shape);
-    }
-
-    if (use_peephole) {
       wci_grad.device(d) = (di * cs_prev).sum(Eigen::array<int, 1>({0}));
       wcf_grad.device(d) = (df * cs_prev).sum(Eigen::array<int, 1>({0}));
       wco_grad.device(d) = (do_ * cs).sum(Eigen::array<int, 1>({0}));
diff --git a/tensorflow/contrib/tensor_forest/hybrid/core/ops/unpack_path_op.cc b/tensorflow/contrib/tensor_forest/hybrid/core/ops/unpack_path_op.cc
index 555674ca69..9d5e1400a5 100644
--- a/tensorflow/contrib/tensor_forest/hybrid/core/ops/unpack_path_op.cc
+++ b/tensorflow/contrib/tensor_forest/hybrid/core/ops/unpack_path_op.cc
@@ -52,7 +52,7 @@ REGISTER_OP("UnpackPath")
       auto tree_depth = c->Dim(params, 1);
       int64 num_nodes = InferenceContext::kUnknownDim;
       if (c->ValueKnown(tree_depth)) {
-        num_nodes = (1 << c->Value(tree_depth)) - 1;
+        num_nodes = (static_cast<int64>(1) << c->Value(tree_depth)) - 1;
       }
 
       c->set_output(0, c->Matrix(num_points, num_nodes));
diff --git a/tensorflow/contrib/tensor_forest/kernels/sample_inputs_op.cc b/tensorflow/contrib/tensor_forest/kernels/sample_inputs_op.cc
index 6bfc29d96f..3ddc72f216 100644
--- a/tensorflow/contrib/tensor_forest/kernels/sample_inputs_op.cc
+++ b/tensorflow/contrib/tensor_forest/kernels/sample_inputs_op.cc
@@ -284,6 +284,8 @@ class SampleInputs : public OpKernel {
             index = rand_feature;
             val = inputs(*it, rand_feature);
           } else {
+            CHECK(sparse_input) << rand_feature << " selected, and dense is "
+                                << input_spec_.dense_features_size();
             const auto indices = sparse_input_indices.matrix<int64>();
             const auto values = sparse_input_values.vec<float>();
             const int32 sparse_index = sparse_input_start + rand_feature -
diff --git a/tensorflow/core/common_runtime/function.cc b/tensorflow/core/common_runtime/function.cc
index 320e214117..b0b834b66a 100644
--- a/tensorflow/core/common_runtime/function.cc
+++ b/tensorflow/core/common_runtime/function.cc
@@ -1047,10 +1047,12 @@ void ToGraphDef(const Graph* g, GraphDef* gdef, bool pretty) {
     // to be unique and stable after optimization rewrites. Therefore,
     // we use "n<node id>" instead.
     for (const Edge* e : inputs) {
-      const string srcname = NewName(e->src(), pretty);
       if (e == nullptr) {
         ndef->add_input("unknown");
-      } else if (!e->src()->IsOp()) {
+        continue;
+      }
+      const string srcname = NewName(e->src(), pretty);
+      if (!e->src()->IsOp()) {
       } else if (e->IsControlEdge()) {
         ndef->add_input(strings::StrCat("^", srcname));
       } else if (e->src_output() == 0) {
diff --git a/tensorflow/core/distributed_runtime/master_session.cc b/tensorflow/core/distributed_runtime/master_session.cc
index 94fec4f6d0..c79f68a068 100644
--- a/tensorflow/core/distributed_runtime/master_session.cc
+++ b/tensorflow/core/distributed_runtime/master_session.cc
@@ -1165,7 +1165,6 @@ WorkerCacheInterface* MasterSession::get_worker_cache() const {
 Status MasterSession::StartStep(const BuildGraphOptions& opts, int64* count,
                                 ReffedClientGraph** rcg, bool is_partial) {
   const uint64 hash = HashBuildGraphOptions(opts);
-  ReffedClientGraph* to_unref = nullptr;
   {
     mutex_lock l(mu_);
     // Keep track of how many times this subgraph has been executed in
@@ -1196,7 +1195,6 @@ Status MasterSession::StartStep(const BuildGraphOptions& opts, int64* count,
     *rcg = iter->second;
     (*rcg)->Ref();
   }
-  if (to_unref) to_unref->Unref();
   return Status::OK();
 }
 
diff --git a/tensorflow/core/kernels/encode_jpeg_op.cc b/tensorflow/core/kernels/encode_jpeg_op.cc
index 8e021b9256..4fcae25aa6 100644
--- a/tensorflow/core/kernels/encode_jpeg_op.cc
+++ b/tensorflow/core/kernels/encode_jpeg_op.cc
@@ -55,8 +55,6 @@ class EncodeJpegOp : public OpKernel {
         context, context->GetAttr("optimize_size", &flags_.optimize_jpeg_size));
     OP_REQUIRES_OK(context, context->GetAttr("chroma_downsampling",
                                              &flags_.chroma_downsampling));
-    OP_REQUIRES_OK(context, context->GetAttr("chroma_downsampling",
-                                             &flags_.chroma_downsampling));
 
     string density_unit;
     OP_REQUIRES_OK(context, context->GetAttr("density_unit", &density_unit));
diff --git a/tensorflow/core/kernels/resize_area_op.cc b/tensorflow/core/kernels/resize_area_op.cc
index ad94de89db..ada50dfb70 100644
--- a/tensorflow/core/kernels/resize_area_op.cc
+++ b/tensorflow/core/kernels/resize_area_op.cc
@@ -33,7 +33,6 @@ namespace tensorflow {
 typedef Eigen::ThreadPoolDevice CPUDevice;
 
 namespace {
-
 struct CachedInterpolation {
   int64 start;
   int64 end;
@@ -41,7 +40,7 @@ struct CachedInterpolation {
   float end_minus_one_scale;
   bool needs_bounding;
 };
-};
+}  // namespace
 
 template <typename Device, typename T>
 class ResizeAreaOp : public OpKernel {
@@ -170,7 +169,7 @@ class ResizeAreaOp : public OpKernel {
                    : (v + 1 > in_x1 ? in_x1 - v : 1.0);
 
       v = ceil(in_x1);
-      x_interp.end = ceil(in_x1);
+      x_interp.end = v;
       v = x_interp.end - 1;
       x_interp.end_minus_one_scale =
           v < in_x ? (v + 1 > in_x1 ? st.width_scale : v + 1 - in_x)
diff --git a/tensorflow/core/lib/strings/strcat.cc b/tensorflow/core/lib/strings/strcat.cc
index 3e864c4f28..46a45a6678 100644
--- a/tensorflow/core/lib/strings/strcat.cc
+++ b/tensorflow/core/lib/strings/strcat.cc
@@ -38,7 +38,7 @@ AlphaNum::AlphaNum(Hex hex) {
   // We accomplish minimum width by OR'ing in 0x10000 to the user's value,
   // where 0x10000 is the smallest hex number that is as wide as the user
   // asked for.
-  uint64 mask = ((static_cast<uint64>(1) << (width - 1) * 4)) | value;
+  uint64 mask = (static_cast<uint64>(1) << (width - 1) * 4) | value;
   static const char hexdigits[] = "0123456789abcdef";
   do {
     *--writer = hexdigits[value & 0xF];