if (TF_GetCode(status) != TF_OK) return nullptr;
  TFE_OpSetAttrType(op, "dtype", TF_FLOAT);
  TFE_OpAddInput(op, var_handle, status);

  // Convert 'value' to a TF_Tensor then a TFE_TensorHandle.
  std::unique_ptr<TF_Tensor, decltype(&TF_DeleteTensor)> t(
      TF_AllocateTensor(TF_FLOAT, nullptr, 0, sizeof(value)), TF_DeleteTensor);
  memcpy(TF_TensorData(t.get()), &value, TF_TensorByteSize(t.get()));

static void FloatDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<float*>(data);
}

TF_Tensor* BoolTensor(bool v) {
  const int num_bytes = sizeof(bool);
  bool* values = new bool[1];
  values[0] = v;
  return TF_NewTensor(TF_BOOL, nullptr, 0, values, num_bytes, &BoolDeallocator,
                      nullptr);
}

TF_Tensor* Int8Tensor(const int64_t* dims, int num_dims, const char* values) {
  int64_t num_values = 1;

    return nullptr;
  }
  TF_DataType dtype;
  absl::Status s = TfDataTypeFormDlDataType(dl_tensor->dtype, &dtype);
  if (!s.ok()) {
    status->status = std::move(s);
    return nullptr;
  }
  int num_dims = dl_tensor->ndim;
  const int64_t* dims = dl_tensor->shape;
  void* data = dl_tensor->data;

  if (dl_tensor->byte_offset != 0) {
    status->status = tensorflow::errors::InvalidArgument(

}

TEST_F(ShapeInferenceTest, InfersShapesFromInputTensors) {
  // Prepare some tensors for shape.
  TF_Tensor* tensor_1X6 = Int32Tensor({1, 6});
  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);
  TF_Tensor* tensor_1X1X6 = Int32Tensor({1, 1, 6});
  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);

#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/test.h"

using tensorflow::Status;

        /*in_flight_nodes_limit=*/0);
    TFE_ContextSetExecutorForThread(ctx, executor);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

    TF_Tensor* t =
        TF_AllocateTensor(TF_INT32, nullptr, 0, 1 * sizeof(tensorflow::int32));
    *reinterpret_cast<tensorflow::int32*>(TF_TensorData(t)) = 42;
    TFE_TensorHandle* h = TFE_NewTensorHandle(t, status);

    TFE_Context* ctx) {
  return static_cast<TFE_ContextDevicePlacementPolicy>(
      tensorflow::unwrap(ctx)->GetDevicePlacementPolicy());
}

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;

  TFE_Execute(func, &retvals[0], &num_retvals, status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  ASSERT_EQ(1, num_retvals);
  TFE_DeleteOp(func);
  TFE_DeleteTensorHandle(packed_handle);
  TF_Tensor* t = TFE_TensorHandleResolve(retvals[0], status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteTensorHandle(retvals[0]);
  float sum = 0;
  EXPECT_EQ(sizeof(sum), TF_TensorByteSize(t));

  // appended later), but should include any information specific to this custom
  // device which would be useful for debugging.
  //
  // Optional. If null, defaults to resolving the TFE_TensorHandle into a
  // TF_Tensor and summarizing that.
  TF_Buffer* (*summarize)(void* data, TF_Status* status) = nullptr;
} TFE_CustomDeviceTensorHandle;

// Creates a new TensorHandle from memory residing in a custom device. Takes

  if (t == nullptr) {
    status->status =
        tensorflow::errors::InvalidArgument("Unsupported dtype: ", dtype);
    return nullptr;
  }

  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));
}