EXPECT_EQ(dltensor_out->device.device_type, dltensor_in->device.device_type);
  EXPECT_EQ(dltensor_out->device.device_id, dltensor_in->device.device_id);
  EXPECT_EQ(dltensor_out->ndim, dltensor_in->ndim);
  EXPECT_EQ(dltensor_out->dtype.code, dltensor_in->dtype.code);
  EXPECT_EQ(dltensor_out->dtype.bits, dltensor_in->dtype.bits);
  EXPECT_EQ(dltensor_out->dtype.lanes, dltensor_in->dtype.lanes);
  for (int i = 0; i < dltensor_in->ndim; ++i) {

                           TF_Status* s) {
  unwrap(o)->outputs.push_back(unwrap(tensor));
}

void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type,
                            TF_Status* s) {
  tsl::Set_TF_Status_from_Status(
      s, unwrap(op)->Reset(op_type,
                           /*raw_device_name=*/nullptr));
}

void TF_AbstractOpSetOpName(TF_AbstractOp* op, const char* const op_name,

    for (const auto& p : *shapes_and_types) {
      auto* out_shape_and_type = handle_data.add_shape_and_type();
      ic->ShapeHandleToProto(p.shape, out_shape_and_type->mutable_shape());
      out_shape_and_type->set_dtype(p.dtype);
      *out_shape_and_type->mutable_type() = p.type;
    }
  }
  string str_data;
  handle_data.SerializeToString(&str_data);

    }
    if (TFE_TensorHandleDataType(component.get()) != dtype) {
      TF_SetStatus(status, TF_INTERNAL,
                   "Components of a ParallelTensor must all have "
                   "the same dtype");
      return nullptr;
    }
  }
  return std::unique_ptr<ParallelTensor>(
      new ParallelTensor(parallel_device, std::move(components), shape, dtype));
}

    shape_string = "<error computing shape>";
  } else {
    shape_string = shape.DebugString();
  }
  return absl::StrCat("TensorHandle(shape=", shape_string,
                      ", dtype=", DataType_Name(DataType()),
                      ", type=", FullType().DebugString(), ")");
}

Status AbstractTensorHandle::TensorHandleStatus() const {
  // Tensor handles in current runtime don't carry error info and this method

}

TFE_TensorHandle* TFE_NewTensorHandleFromScalar(TF_DataType data_type,
                                                void* data, size_t len,
                                                TF_Status* status) {
  auto dtype = static_cast<tensorflow::DataType>(data_type);
  DCHECK(tensorflow::DataTypeCanUseMemcpy(dtype));

  tensorflow::Tensor tensor(dtype, tensorflow::TensorShape({}));

Variable* Variable::Create(TFE_Context* context, TF_DataType type,
                           const int64_t* dims, const int num_dims,
                           const char* device, TF_Status* status) {
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> op(
      TFE_NewOp(context, "VarHandleOp", status), TFE_DeleteOp);
  if (TF_GetCode(status) != TF_OK) return nullptr;
  TFE_OpSetAttrType(op.get(), "dtype", type);

  auto dtype = TFE_TensorHandleDataType(t->tensor);
  TFE_CustomDeviceTensorHandleMethods handle_methods;
  handle_methods.num_dims = &LoggedTensorNumDims;
  handle_methods.dim = &LoggedTensorDim;
  handle_methods.deallocator = &LoggedTensorDeallocator;
  return TFE_NewCustomDeviceTensorHandle(context, logging_device_name.c_str(),
                                         dtype, t.release(), handle_methods,

  Status status;
  if (reader_ != nullptr) {
    status = reader_->GetTensor(name, out_tensor);
  } else {
    tensorflow::DataType dtype;
    tensorflow::TensorShape shape;
    status = v2_reader_->LookupDtypeAndShape(name, &dtype, &shape);
    if (status.ok()) {
      out_tensor->reset(new Tensor(dtype, shape));
      status = v2_reader_->Lookup(name, out_tensor->get());
      if (!status.ok()) out_tensor->reset();
    }
  }

      TFE_NewOp(context.get(), "VarHandleOp", status.get()), TFE_DeleteOp);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_OpSetAttrType(handle_op.get(), "dtype", TF_FLOAT);
  TFE_OpSetAttrShape(handle_op.get(), "shape", /*dims=*/nullptr, /*num_dims=*/0,
                     status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  auto outputs =