EXPECT_EQ(22, product[3]);
  TF_DeleteStatus(status);
}
TEST(CAPI, Executor_MatMul_CPU) { Executor_MatMul_CPU(false); }
TEST(CAPI, Executor_MatMul_CPUAsync) { Executor_MatMul_CPU(true); }

void Deleter(void* data, size_t unused, void* tensor_handle) {
  TFE_DeleteTensorHandle(static_cast<TFE_TensorHandle*>(tensor_handle));
}

TEST(CAPI, TensorHandleOnDeviceMemory) {
  TF_Status* status = TF_NewStatus();

  TFE_DeleteContext(ctx);
}
TEST(CAPI, TensorHandleSilentCopy) {
  TensorHandleSilentCopy(false, TFE_DEVICE_PLACEMENT_SILENT,
                         TFE_DEVICE_PLACEMENT_SILENT, false);
}
TEST(CAPI, TensorHandleSilentCopyAsync) {
  TensorHandleSilentCopy(true, TFE_DEVICE_PLACEMENT_SILENT,
                         TFE_DEVICE_PLACEMENT_SILENT, false);
}
TEST(CAPI, TensorHandleSilentCopyLocalPolicy) {

  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteGraph(graph);
  TF_DeleteStatus(s);
}

TEST(CAPI, Session_Min_CPU) { RunMinTest(/*device=*/"", /*use_XLA=*/false); }

TEST(CAPI, Session_Min_XLA_CPU) { RunMinTest(/*device=*/"", /*use_XLA=*/true); }

TEST(CAPI, Session_Min_GPU) {
  const string gpu_device = GPUDeviceName();
  // Skip this test if no GPU is available.

                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,
            std::unique_ptr<TensorSliceReader::VarToDataTypeMap> >

} TFE_CancelCallback;
TF_CAPI_EXPORT extern TFE_CancellationManager* TFE_NewCancellationManager();
TF_CAPI_EXPORT extern bool TFE_CancellationManagerIsCancelled(
    TFE_CancellationManager*);
TF_CAPI_EXPORT extern bool TFE_CancellationManagerIsCancelling(
    TFE_CancellationManager*);
TF_CAPI_EXPORT extern void TFE_CancellationManagerStartCancel(
    TFE_CancellationManager*);

TF_CAPI_EXPORT extern TF_VariableInfo* TF_CreateVariableInfoFromContext(
    TF_OpKernelContext* ctx, int index, TF_Status* status);

TF_CAPI_EXPORT extern void TF_LockVariableInfos(TF_VariableInfo** vars,
                                                int num_vars,
                                                TF_Status* status);

TF_CAPI_EXPORT extern void TF_AllocateTempForVariableInfo(

}

TF_CAPI_EXPORT extern int TFE_OpGetInputLength(TFE_Op* op,
                                               const char* input_name,
                                               TF_Status* status) {
  int ret = -1;
  status->status = tensorflow::unwrap(op)->InputLength(input_name, &ret);
  return ret;
}

TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op,

  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return -1;
  }
  return tensorflow::unwrap(h)->DeviceId(&status->status);
}

TF_CAPI_EXPORT extern void TFE_TensorHandleGetStatus(TFE_TensorHandle* h,
                                                     TF_Status* status) {
  status->status = tensorflow::unwrap(h)->TensorHandleStatus();
}

    *   In `map_vectorization` optimization, reduce the degree of parallelism in
        the vectorized map node.
    *   Add variant wrapper for `absl::string_view`.
    *   Add OpKernels for some stateless maps.
    *   DType is no longer convertible to an int. Use `dtype.as_datatype_enum`
        instead of `int(dtype)` to get the same result.
    *   Support both binary and -1/1 label input in v2 hinge and squared hinge

  status->status = absl::OkStatus();
  return tensorflow::wrap(tensorflow::TensorHandle::CreateLocalHandle(tensor));
}

// Set server_def on the context, possibly updating it.
TF_CAPI_EXPORT extern void TFE_EnableCollectiveOps(TFE_Context* ctx,
                                                   const void* proto,
                                                   size_t proto_len,