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",

    // 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;

#include "tensorflow/core/common_runtime/eager/tensor_handle.h"
#include "tensorflow/core/platform/status.h"

using tensorflow::string;

namespace {

std::vector<int64_t> TensorShapeAsVector(const tensorflow::TensorHandle& handle,
                                         absl::Status* status) {
  std::vector<int64_t> shape;
  int rank = -1;
  *status = handle.NumDims(&rank);
  if (!status->ok()) {
    return shape;
  }
  shape.reserve(rank);

  // `ctx_0`, `ctx_1` contains `remote_device`.
  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_1);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),

		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

  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;
}

  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server1)
                  .ok());
  ASSERT_TRUE(worker_server1->Start().ok());

  server_def.set_task_index(2);
  std::unique_ptr<tensorflow::GrpcServer> worker_server2;

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) {

  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,

      tensor, context, dev->underlying_device.c_str(), status);
  if (TF_GetCode(status) != TF_OK) return nullptr;
  auto dst = std::make_unique<LoggedTensor>(t);
  *(dev->arrived_flag) = true;
  return MakeLoggedTensorHandle(context, dev->device_name, std::move(dst),
                                status);
}

TFE_TensorHandle* CopyTensorFromLoggingDevice(TFE_Context* context,