// Attempts to look up the tensor named "name" and stores the found result in
  // "out_tensor".
  void GetTensor(const string& name,
                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.

    if: |
      github.repository == 'tensorflow/tensorflow' &&
      startsWith(github.event.head_commit.message, 'Rollback of PR #')
    steps:
      - name: Checkout repo
        uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0
      - name: Create a new Github Issue
        uses: actions/github-script@d556feaca394842dc55e4734bf3bb9f685482fa0 # v6.3.3
        with:
          github-token: ${{secrets.GITHUB_TOKEN}}

  TF_OperationDescription* init(string type) {
    // Construct op_name to match the name used by REGISTER_OP in the
    // ATTR_TEST_REGISTER calls above.
    string op_name = "CApiAttributesTestOp";
    if (type.find("list(") == 0) {
      op_name += "List";
      type = type.replace(0, 5, "");
      type = type.replace(type.size() - 1, 1, "");
    }
    op_name += type;
    return TF_NewOperation(

  string gpu_device_name;
  if (GetDeviceName(ctx, &gpu_device_name, "GPU")) {
    TFE_TensorHandle* hgpu = TFE_TensorHandleCopyToDevice(
        hcpu, ctx, gpu_device_name.c_str(), status.get());
    ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

    TFE_Op* shape_op = ShapeOp(ctx, hgpu);
    TFE_OpSetDevice(shape_op, gpu_device_name.c_str(), status.get());

#include "tensorflow/c/tf_status.h"

void RegisterLoggingDevice(TFE_Context* context, const char* name,
                           bool strict_scope_placement, bool* arrived_flag,
                           bool* executed_flag, TF_Status* status);
void AllocateLoggingDevice(const char* name, bool* arrived_flag,
                           bool* executed_flag, TFE_CustomDevice** device,

  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each

  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);

  // Start a new function / execution context.
  string fn_name = "double";
  TF_ExecutionContext* graph_ctx =
      TF_CreateFunction(fn_name.c_str(), status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  auto* placeholder_t =

package(default_visibility = ["//visibility:public"])

licenses(["notice"])  # Apache 2.0

filegroup(
    name = "model_files",
    srcs = glob(
        [
            "**/*",
        ],
        exclude = [
            "**/BUILD",
            "**/WORKSPACE",
            "**/LICENSE",
            "**/*.zip",
        ],
    ),

  std::unique_ptr<WritableFile> same_file;
  status = env_->NewAppendableFile(filepath, &same_file);
  if (!status.ok())
    GTEST_SKIP() << "NewAppendableFile() not supported: " << status;

  const std::string more_test_data("qwer");
  EXPECT_EQ(same_file->Append(more_test_data).code(), Code::OK);
  EXPECT_EQ(same_file->Flush().code(), Code::OK);
  EXPECT_EQ(same_file->Close().code(), Code::OK);

        # To get the as-merged branch during the CI tests
        git diff --diff-filter ACMRT --name-only pull_branch^ pull_branch > $BATS_FILE_TMPDIR/changed_files
    else
        # If the branch is not present, then diff against origin/master
        git diff --diff-filter ACMRT --name-only origin/master > $BATS_FILE_TMPDIR/changed_files
    fi
}