class UnifiedCAPI
    : public ::testing::TestWithParam<std::tuple<const char*, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    absl::Status s = StatusFromTF_Status(status.get());
    CHECK_EQ(errors::OK, s.code()) << s.message();
  }
};

TEST_P(UnifiedCAPI, TestBasicEager) {

		export GOARCH=arm
		export GOARM=5
	fi

	# Build and vet everything.
	# cmd/go/internal/work/exec.go enables the same vet flags during go test of std cmd
	# and should be kept in sync with any vet flag changes here.
	if ! "$GOROOT/bin/go" build std cmd || ! "$GOROOT/bin/go" vet -unsafeptr=false std cmd; then
		failed=true
		if $sete; then
			exit 1
		fi
	fi
done

if [ "$failed" = "true" ]; then
	echo "" 1>&2

    // Input tensors
    const std::vector<std::pair<string, Tensor>>& input_pairs,
    // Output tensors
    const std::vector<string>& output_tensor_names, TF_Tensor** c_outputs,
    // Target nodes
    const std::vector<string>& target_oper_names, TF_Buffer* run_metadata,
    TF_Status* status) {
  const int noutputs = output_tensor_names.size();
  std::vector<Tensor> outputs(noutputs);
  Status result;

Vendoring in std and cmd
========================

The Go command maintains copies of external packages needed by the
standard library in the src/vendor and src/cmd/vendor directories.

There are two modules, std and cmd, defined in src/go.mod and
src/cmd/go.mod. When a package outside std or cmd is imported
by a package inside std or cmd, the import path is interpreted
as if it had a "vendor/" prefix. For example, within "crypto/tls",

#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"

namespace tensorflow {

std::string ImmediateExecutionTensorHandle::DebugString() const {
  PartialTensorShape shape;
  std::string shape_string;
  if (Shape(&shape).ok()) {
    shape_string = shape.DebugString();
  } else {
    shape_string = "<error computing shape>";
  }
  std::string value_string;
  if (!SummarizeValue(value_string).ok()) {

// manual user-provided gradients.
class GradientCheckerTest
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());

    {
      absl::Status s = StatusFromTF_Status(status.get());

  TF_DeleteBuffer(buffer);
  return ret;
}

std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def) {
  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }
  std::sort(grads.begin(), grads.end());
  return grads;
}

    return nullptr;
  }
  std::vector<std::unique_ptr<tensorflow::Device>> devices;
  status->status = tensorflow::DeviceFactory::AddDevices(
      opts->session_options.options, "/job:localhost/replica:0/task:0",
      &devices);
  if (!status->status.ok()) return nullptr;
  std::unique_ptr<tensorflow::DeviceMgr> device_mgr(
      new tensorflow::DynamicDeviceMgr(std::move(devices)));

  absl::Status Run(const std::string& function_name,
                   const tensorflow::DeviceSet& device_set,
                   const tensorflow::ConfigProto& config_proto,
                   const FunctionOptions& function_options,
                   std::unique_ptr<tensorflow::Graph>* graph,
                   tensorflow::FunctionLibraryDefinition* flib_def,
                   std::vector<std::string>* control_ret_node_names,

// gradient registerer to instantiate a GradientFunction.
struct ForwardOperation {
 public:
  string op_name;
  std::vector<AbstractTensorHandle*> inputs;
  std::vector<AbstractTensorHandle*> outputs;
  std::vector<int64_t> skip_input_indices;
  AttrBuilder attrs;
};

using GradientFunctionFactory =
    std::function<GradientFunction*(const ForwardOperation& op)>;

// Map from op name to a `GradientFunctionFactory`.