break;
    case TF_DataType::TF_INT8:
    case TF_DataType::TF_INT16:
    case TF_DataType::TF_INT32:
    case TF_DataType::TF_INT64:
      dtype.code = DLDataTypeCode::kDLInt;
      break;
    case TF_DataType::TF_UINT8:
    case TF_DataType::TF_UINT16:
    case TF_DataType::TF_UINT32:
    case TF_DataType::TF_UINT64:
      dtype.code = DLDataTypeCode::kDLUInt;
      break;

        ],
    }),
)

cc_library(
    name = "tf_datatype_hdrs",
    hdrs = ["tf_datatype.h"],
    visibility = ["//tensorflow:internal"],
    deps = [
        ":c_api_macros_hdrs",
    ],
)

cc_library(
    name = "tf_datatype",
    srcs = ["tf_datatype.cc"],
    hdrs = ["tf_datatype.h"],
    copts = tf_copts(),
    visibility = ["//visibility:public"],
    deps = [

                                  tsl::profiler::TraceMeLevel::kInfo);
  if (h) {
    tensorflow::unwrap(h)->Unref();
  }
}

TF_DataType TFE_TensorHandleDataType(TFE_TensorHandle* h) {
  return static_cast<TF_DataType>(tensorflow::unwrap(h)->DataType());
}

int TFE_TensorHandleNumDims(TFE_TensorHandle* h, TF_Status* status) {
  if (h == nullptr) {

int TF_CheckpointReaderSize(TF_CheckpointReader* reader) {
  return reader->variable_list.size();
}

TF_DataType TF_CheckpointReaderGetVariableDataType(TF_CheckpointReader* reader,
                                                   const char* name) {
  const auto& m = reader->GetVariableToDataTypeMap();
  return static_cast<TF_DataType>(m.at(name));
}

TF_Tensor* TF_CheckpointReaderGetTensor(TF_CheckpointReader* reader,

  EXPECT_EQ(TF_FLOAT, static_cast<TF_DataType>(tensorflow::DT_FLOAT));
  EXPECT_EQ(TF_DOUBLE, static_cast<TF_DataType>(tensorflow::DT_DOUBLE));
  EXPECT_EQ(TF_INT32, static_cast<TF_DataType>(tensorflow::DT_INT32));
  EXPECT_EQ(TF_UINT8, static_cast<TF_DataType>(tensorflow::DT_UINT8));
  EXPECT_EQ(TF_INT16, static_cast<TF_DataType>(tensorflow::DT_INT16));
  EXPECT_EQ(TF_INT8, static_cast<TF_DataType>(tensorflow::DT_INT8));

#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/strings/str_cat.h"
#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/core/framework/types.pb.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"

#include "tensorflow/c/env.h"
#include "tensorflow/c/kernels.h"

// A create function. This will never actually get called in this test, it's
// just nice to know that it compiles.
void* create(TF_OpKernelConstruction* ctx) {
  TF_DataType type;
  TF_Status* s = TF_NewStatus();
  TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s);
  TF_DeleteStatus(s);
  return NULL;
}

// one cannot call ASSERT_* methods in non-void-returning functions (when
// exceptions are disabled during compilation)
void PlaceholderHelper(TF_Graph* graph, TF_Status* s, const char* name,
                       TF_DataType dtype, const std::vector<int64_t>& dims,
                       TF_Operation** op) {
  TF_OperationDescription* desc = TF_NewOperation(graph, "Placeholder", name);
  TF_SetAttrType(desc, "dtype", dtype);

                                           const int64_t** shapes,
                                           const int* ranks,
                                           const TF_DataType* types,
                                           TF_Status* status);

void RecordMutation(TF_Graph* graph, const TF_Operation& op,
                    const char* mutation_type)

}

void TF_SetAttrType(TF_OperationDescription* desc, const char* attr_name,
                    TF_DataType value) {
  desc->node_builder.Attr(attr_name, static_cast<DataType>(value));
}

void TF_SetAttrTypeList(TF_OperationDescription* desc, const char* attr_name,
                        const TF_DataType* values, int num_values) {
  desc->node_builder.Attr(
      attr_name, ArraySlice<const DataType>(