using tensorflow::string;
using tensorflow::tstring;

TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value) {
  float data[] = {value};
  TF_Status* status = TF_NewStatus();
  TF_Tensor* t = TFE_AllocateHostTensor(ctx, TF_FLOAT, nullptr, 0, status);
  memcpy(TF_TensorData(t), &data[0], TF_TensorByteSize(t));
  TFE_TensorHandle* th = TFE_NewTensorHandleFromTensor(ctx, t, status);

// returned will be on the device in which the TFE_TensorHandle resides (so e.g.
// for a GPU tensor this will return a pointer to GPU memory). The pointer is
// only guaranteed to be valid until TFE_DeleteTensorHandle is called on this
// TensorHandle. Only supports POD data types.
TF_CAPI_EXPORT extern void* TFE_TensorHandleDevicePointer(TFE_TensorHandle*,
                                                          TF_Status*);

// Gets tensor from eager tensor handle.
const Tensor* GetTensorFromHandle(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return nullptr;
  }
  tensorflow::TensorHandle* handle =
      tensorflow::TensorHandleFromInterface(tensorflow::unwrap(h));
  if (handle->Type() != TensorHandle::LOCAL) {
    status->status = tensorflow::errors::InvalidArgument(

}

TFE_TensorHandle* TFE_NewTensorHandle(const TF_Tensor* t, TF_Status* status) {
  tensorflow::Tensor tensor;
  status->status = tensorflow::TF_TensorToTensor(t, &tensor);
  if (!status->status.ok()) return nullptr;

  return tensorflow::wrap(tensorflow::TensorHandle::CreateLocalHandle(tensor));
}

void TFE_DeleteTensorHandle(TFE_TensorHandle* h) {
  if (h == nullptr) return;

std::unique_ptr<ParallelTensor> ParallelDevice::CopyToParallelDevice(
    TFE_Context* context, TFE_TensorHandle* tensor, TF_Status* status) const {
  std::vector<TensorHandlePtr> components;
  components.reserve(underlying_devices_.size());
  for (const std::string& underlying_device_name : underlying_devices_) {
    TFE_TensorHandle* t = TFE_TensorHandleCopyToDevice(
        tensor, context, underlying_device_name.c_str(), status);

  const char task2_name[] = "/job:localhost/replica:0/task:2/device:CPU:0";

  // Create one variable per task.
  TFE_TensorHandle* h0 = TestVariable(ctx, 1.0, task1_name);
  TFE_TensorHandle* h1 = TestVariable(ctx, 2.0, task2_name);
  TFE_TensorHandle* h2 = TestVariable(ctx, 3.0, task0_name);

  // Add a sync point to make sure that variables have been initialized
  // before the function execution starts.

  return new TF_Tensor{t};
}

TFE_TensorHandle* TFE_NewTensorHandleFromTensor(TFE_Context* ctx, TF_Tensor* t,
                                                TF_Status* status) {
  return tensorflow::wrap(
      tensorflow::unwrap(ctx)->CreateLocalHandle(t->tensor));
}

TFE_TensorHandle* TFE_CreatePackedTensorHandle(TFE_Context* ctx,
                                               TFE_TensorHandle** handles,

    ],
)

cc_library(
    name = "tfe_tensorhandle_internal",
    hdrs = ["tfe_tensorhandle_internal.h"],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":immediate_execution_tensor_handle",
        "//tensorflow/c:conversion_macros",
    ],
)

cc_header_only_library(
    name = "tfe_tensorhandle_internal_hdrs_only",
    extra_deps = [

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/tfe_context_internal.h"
#include "tensorflow/c/eager/tfe_op_internal.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/compiler/jit/flags.h"
#include "tensorflow/core/common_runtime/eager/attr_builder.h"
#include "tensorflow/core/common_runtime/eager/context.h"

        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_internal",
        "//tensorflow/c/eager:tfe_context_internal",
        "//tensorflow/c/eager:tfe_op_internal",
        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "//tensorflow/compiler/jit:flags",
        "//tensorflow/compiler/jit:get_compiler_ir",
        "//tensorflow/core:core_cpu",
        "//tensorflow/core:framework",
        "//tensorflow/core:lib",