srcs = [":device_sources"],
    hdrs = [":device_headers"],
    visibility = ["//visibility:private"],
    deps = [
        ":parallel_device_lib",
        "//tensorflow/c:c_api",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "@com_google_absl//absl/strings",

  bool found_neg = false;
  size_t pos = 0;
  TF_Operation* oper;
  while ((oper = TF_GraphNextOperation(graph, &pos)) != nullptr) {
    if (oper == feed) {
      EXPECT_FALSE(found_placeholder);
      found_placeholder = true;
    } else if (oper == three) {
      EXPECT_FALSE(found_scalar_const);
      found_scalar_const = true;
    } else if (oper == add) {
      EXPECT_FALSE(found_add);
      found_add = true;

const char* TF_OperationName(TF_Operation* oper) {
  return oper->node.name().c_str();
}

const char* TF_OperationOpType(TF_Operation* oper) {
  return oper->node.type_string().c_str();
}

const char* TF_OperationDevice(TF_Operation* oper) {
  return oper->node.requested_device().c_str();
}

int TF_OperationNumOutputs(TF_Operation* oper) {
  return oper->node.num_outputs();
}

filegroup(
    name = "checkpoint_reader_hdrs",
    srcs = [
        "checkpoint_reader.h",
        "tf_status_helper.h",
    ],
    visibility = ["//tensorflow:__subpackages__"],
)

tf_cuda_library(
    name = "tf_status_helper",
    srcs = ["tf_status_helper.cc"],
    hdrs = ["tf_status_helper.h"],
    visibility = ["//visibility:public"],
    deps = [
        ":tf_status_headers",

    # convert to modular filesystems everywhere
    visibility = ["//visibility:public"],
    deps = [
        ":filesystem_interface",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c:tf_status_internal",
        "//tensorflow/core/platform:env",
        "//tensorflow/core/platform:errors",
        "//tensorflow/core/platform:status",
        "@local_tsl//tsl/platform:errors",

        ":abstract_tensor_handle",
        ":c_api_experimental",
        ":c_api_test_util",
        ":c_api_unified_internal",
        "//tensorflow/c:tf_status",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c:tf_tensor",
        "//tensorflow/core:framework",
        "//tensorflow/core/lib/llvm_rtti",
        "//tensorflow/core/platform:errors",
        "//tensorflow/core/platform:status",

#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/graph_function.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "xla/tsl/c/tsl_status_internal.h"
#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/tensor_shape.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_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "xla/tsl/c/tsl_status_internal.h"
#include "xla/tsl/distributed_runtime/coordination/coordination_service_agent.h"
#include "tensorflow/core/common_runtime/composite_device.h"

        "//tensorflow/c:c_api_internal",
        "//tensorflow/c:c_api_no_xla",
        "//tensorflow/c:checkpoint_reader",
        "//tensorflow/c:tensor_interface",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c:tf_tensor_internal",
        "//tensorflow/cc/saved_model:loader",
        "//tensorflow/compiler/mlir/lite/metrics:error_collector",

# Release 2.9.1

Add an upper bound for `protobuf` in `setup.py` since `protobuf` after version 3.20 is currently incompatible with TensorFlow. See https://github.com/tensorflow/tensorflow/issues/53234, https://github.com/protocolbuffers/protobuf/issues/9954 and https://github.com/tensorflow/tensorflow/issues/56077.

# Release 2.8.2