TracingContext* tracing_ctx = dyn_cast<TracingContext>(unwrap(ctx));
  if (!tracing_ctx) {
    tsl::Set_TF_Status_from_Status(
        s, tensorflow::errors::InvalidArgument(
               "Only TracingContext can be converted into a function."));
    return nullptr;
  }
  tsl::Set_TF_Status_from_Status(s,
                                 tracing_ctx->Finalize(unwrap(outputs), &func));
  TF_DeleteExecutionContext(ctx);

      ->set_disable_optimize_for_static_graph(true);
}

void TF_TensorFromProto(const TF_Buffer* from, TF_Tensor* to,
                        TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  tensorflow::TensorProto from_tensor_proto;
  status->status = BufferToMessage(from, &from_tensor_proto);
  if (!status->status.ok()) {
    return;
  }
  status->status =

==============================================================================*/

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

#include <vector>

#include "absl/strings/str_join.h"
#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {

void TestHandleFromDLPack(TF_Status* status, TFE_Context* ctx,

     *
     *    dA = U
     *    dbias = reduceSum(U, dims = channel_dim)
     */

    AbstractTensorHandle* upstream_grad = grad_outputs[0];
    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();

  opts->opts.validate_colocation_constraints = enable;
}

// Load a Pluggable Device library.
// On success, returns the handle to library in result and return OK from the
// function. Otherwise return nullptr in result and error Status from the
// function.
//
// If `library_filename` has already been loaded, we return a cached handle.
// Device and Kernels/Ops are registered as globals when a library is loaded

  ops->filesystem_ops->new_writable_file = tf_posix_filesystem::NewWritableFile;
  ops->filesystem_ops->new_appendable_file =
      tf_posix_filesystem::NewAppendableFile;
  ops->filesystem_ops->new_read_only_memory_region_from_file =
      tf_posix_filesystem::NewReadOnlyMemoryRegionFromFile;
  ops->filesystem_ops->create_dir = tf_posix_filesystem::CreateDir;
  ops->filesystem_ops->delete_file = tf_posix_filesystem::DeleteFile;

    if (!v2_reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, v2_reader_->status());
      return;
    }
    auto result = BuildV2VarMaps();
    var_to_shape_map_.swap(result.first);
    var_to_data_type_map_.swap(result.second);
  } else {
    reader_.reset(new TensorSliceReader(filename));
    if (!reader_->status().ok()) {
      tsl::Set_TF_Status_from_Status(status, reader_->status());
      return;
    }

          ->LookUpOpDef(name, &op_def_ptr);
  if (!s.ok()) {
    tsl::Set_TF_Status_from_Status(status, s);
    return;
  }

  s = tensorflow::MessageToBuffer(*op_def_ptr, buf);
  if (!s.ok()) {
    tsl::Set_TF_Status_from_Status(status, s);
    return;
  }

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

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

#include <string>

#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_status_internal.h"

#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/file_system_helper.h"
#include "tsl/platform/errors.h"

// TODO(b/139060984): After all filesystems are converted, all calls to
// methods from `FileSystem` will have to be replaced to calls to private
// methods here, as part of making this class a singleton and the only way to
// register/use filesystems.

namespace tensorflow {

using UniquePtrTo_TF_Status =