"//tensorflow/core:framework_internal",
        "//tensorflow/core/lib/io:path",
        "//tensorflow/core/platform:env",
        "//tensorflow/core/platform:errors",
        "//tensorflow/core/platform:stacktrace_handler",
        "//tensorflow/core/platform:test",
    ],

        "notap",
    ],
    deps = [
        ":gcs_filesystem_impl",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/core/platform:path",
        "//tensorflow/core/platform:stacktrace_handler",
        "//tensorflow/core/platform:test",
        "@com_google_absl//absl/strings",
    ],
)

cc_library(
    name = "expiring_lru_cache",
    hdrs = ["expiring_lru_cache.h"],
    deps = [

        "//tensorflow/c:tf_status_internal",
        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:immediate_execution_tensor_handle",
        "//tensorflow/c/eager:tfe_tensorhandle_internal",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
    ],
)

tf_cc_test(

  TF_Output feeds[] = {TF_Output{a, 0}, TF_Output{b, 0}};
  TF_Output fetches[] = {TF_Output{plus2, 0}, TF_Output{plusB, 0}};

  const char* handle = nullptr;
  TF_SessionPRunSetup(sess, feeds, TF_ARRAYSIZE(feeds), fetches,
                      TF_ARRAYSIZE(fetches), nullptr, 0, &handle, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Feed A and fetch A + 2.
  TF_Output feeds1[] = {TF_Output{a, 0}};

        ->DevicePointer();
  }
  // TODO(b/175427838): It would be nice to be able to use tensorflow::isa here.
  if (!tensorflow::TensorHandle::classof(unwrapped_handle)) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return nullptr;
  }
  tensorflow::TensorHandle* handle =
      tensorflow::TensorHandleFromInterface(unwrapped_handle);

        "//tensorflow/core/kernels:dataset_ops",
        "//tensorflow/core/platform:logging",
        "//tensorflow/core/platform:path",
        "//tensorflow/core/platform:stacktrace_handler",
        "//tensorflow/core/platform:statusor",
        "//tensorflow/core/platform:stringpiece",
        "//tensorflow/core/platform:types",
        "//tensorflow/core/profiler/internal:print_model_analysis",

                                               int* num_handles,
                                               TF_Status* status) {
  std::vector<tensorflow::TensorHandle*> tensor_handles;
  tensor_handles.reserve(*num_handles);
  for (int i = 0; i < *num_handles; ++i) {
    tensorflow::ImmediateExecutionTensorHandle* unwrapped_handle =
        tensorflow::unwrap(handles[i]);

  if (!status->status.ok()) {
    delete lib_handle;
    return nullptr;
  }
  return lib_handle;
}

TF_Buffer TF_GetOpList(TF_Library* lib_handle) { return lib_handle->op_list; }

void TF_DeleteLibraryHandle(TF_Library* lib_handle) {
  if (lib_handle == nullptr) return;
  tensorflow::port::Free(const_cast<void*>(lib_handle->op_list.data));
  delete lib_handle;
}

TF_Buffer* TF_GetAllOpList() {

        ],
    }),
)

cc_library(
    name = "immediate_execution_tensor_handle",
    srcs = ["immediate_execution_tensor_handle.cc"],
    hdrs = ["immediate_execution_tensor_handle.h"],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":abstract_tensor_handle",
        "//tensorflow/c:tensor_interface",
        "//tensorflow/core:framework",

*   Updates `libjpeg-turbo` to `2.0.5` to handle
    [CVE-2020-13790](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-13790).
*   Updates `junit` to `4.13.1` to handle
    [CVE-2020-15250](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2020-15250).
*   Updates `PCRE` to `8.44` to handle
    [CVE-2019-20838](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2019-20838)
    and