for (int i = 0; i < noutputs; ++i) {
    c_outputs[i] = nullptr;
  }
}

// TF_TensorToTensorV1 decodes a string serialization to DT_RESOURCE.
// In the TFv1 convention, TF_Tensor can hold a string serialization of
// DT_RESOURCE. The string serialization is converted back to a
// ResourceHandle during Session run where the TF_Tensor is converted to a
// Tensor.
// TFv2 does not depend on this conversion. There is no matching

#include "tensorflow/c/experimental/filesystem/plugins/gcs/gcs_helper.h"

#include <stdio.h>

#include <fstream>
#include <string>
#include <utility>

TempFile::TempFile(const std::string& temp_file_name, std::ios::openmode mode)
    : std::fstream(temp_file_name, mode), name_(temp_file_name) {}

TempFile::TempFile(TempFile&& rhs)

using tensorflow::string;

namespace tensorflow {
namespace tracing {
typedef absl::flat_hash_map<std::string, tracing::FactoryFunction> FactoriesMap;

static FactoriesMap& GetFactories() {
  static FactoriesMap* factories = new FactoriesMap;
  return *factories;
}

static tracing::FactoryFunction default_factory;

void RegisterTracingEngineFactory(const string& name, FactoryFunction factory) {

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#include <array>
#include <memory>
#include <string>

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_experimental.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"

    DCHECK(upstream_grad);

    // Recover data format from forward pass for gradient.
    std::string data_format;
    TF_RETURN_IF_ERROR(forward_attrs_.Get("data_format", &data_format));

    // Grad for A
    grad_inputs[0] = upstream_grad;
    grad_inputs[0]->Ref();

    // Grad for bias
    std::string name = "bias_add_grad";
    TF_RETURN_IF_ERROR(BiasAddGrad(ctx, upstream_grad, &grad_inputs[1],

limitations under the License.
==============================================================================*/

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

#include <string.h>
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/test.h"

TEST(CApiDebug, ScalarCPU) {
  TF_Status* status = TF_NewStatus();

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include <stdlib.h>
#include <string.h>

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"
#include "tensorflow/c/tf_status.h"

// Implementation of a filesystem for POSIX environments.

#include "tensorflow/c/experimental/filesystem/plugins/posix/posix_filesystem_helper.h"

#include <errno.h>
#include <fcntl.h>
#include <limits.h>
#include <stdint.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>

#include "tensorflow/c/experimental/filesystem/plugins/posix/copy_file.h"

namespace tf_posix_filesystem {

int TransferFileContents(const char* src, const char* dst, mode_t mode,

  if (ret) ret = attr_value->ParseFromArray(buffer->data, buffer->length);
  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());
  }

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()) {
    value_string = "<error computing value>";
  }