compile_pip_requirements_3_9(
    name = "requirements_3_9",
    extra_args = ["--allow-unsafe"],
    requirements_in = REQUIREMENTS_FILE_NAME,
    requirements_txt = "requirements_lock_3_9.txt",
)

compile_pip_requirements_3_10(
    name = "requirements_3_10",
    extra_args = ["--allow-unsafe"],
    requirements_in = REQUIREMENTS_FILE_NAME,
    requirements_txt = "requirements_lock_3_10.txt",
)

  TF_Tensor* t = TF_NewTensor(TF_FLOAT, dims, 2, values, num_bytes,
                              &Deallocator, &deallocator_called);

  TF_Tensor* o = TF_TensorMaybeMove(t);
  ASSERT_TRUE(o == nullptr);  // It is unsafe to move memory TF might not own.
  TF_DeleteTensor(t);
  EXPECT_TRUE(deallocator_called);
}

TEST(CAPI, LibraryLoadFunctions) {
  // TODO(b/73318067): Fix linking for the GPU test generated by the

cc_library(
    name = "parallel_device_lib",
    srcs = [":lib_sources"],
    hdrs = [":lib_headers"],
    visibility = ["//tensorflow:internal"],
    deps = [
        "//tensorflow/c:c_api",
        "//tensorflow/c:safe_ptr",
        "//tensorflow/c:tf_status_internal",
        "//tensorflow/c/eager:c_api",
        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:tfe_cancellation_manager_internal",

    licenses = ["notice"],
)

filegroup(
    name = "safe_ptr_hdr",
    srcs = ["safe_ptr.h"],
    visibility = [
        "//tensorflow:internal",
    ],
)

cc_library(
    name = "safe_ptr",
    srcs = [
        "safe_ptr.cc",
        "//tensorflow/c/eager:headers",
    ],
    hdrs = ["safe_ptr.h"],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [

// call Session::Extend().
bool ExtendSessionGraphHelper(TF_Session* session, TF_Status* status) {
  if (session->graph != nullptr) {
    // Take the graph lock before the session lock to avoid deadlock. This is
    // safe since session->graph does not change.
    session->graph->mu.lock();
    mutex_lock session_lock(session->mu);
    const Graph& graph = session->graph->graph;

*   TF XLA

    *   Add new enum value `MLIR_BRIDGE_ROLLOUT_SAFE_MODE_ENABLED` to
        `tf.config.experimental.mlir_bridge_rollout` to enable a \"safe\" mode.
        This runs the MLIR bridge only when an analysis of the graph only when
        an analysis of the graph determines that it is safe to run.
    *   Add new enum value `MLIR_BRIDGE_ROLLOUT_SAFE_MODE_FALLBACK_ENABLED'

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
#
# Usage: rename_and_verify_wheels.sh
# This script is aware of TFCI_ variables, so it doesn't need any arguments.
# Puts new wheel through auditwheel to rename and verify it, deletes the old

}

// Note: this function looks up a thread local policy. So it should be called in
// the appropriate client thread. In particular, in async mode, it may not be
// safe to call this function from the async EagerExecutor threads.
extern TFE_ContextDevicePlacementPolicy TFE_ContextGetDevicePlacementPolicy(
    TFE_Context* ctx) {
  return static_cast<TFE_ContextDevicePlacementPolicy>(

          }
        }
      }
      auto usage_count_it = state.tensor_usage_counts.find(id);
      if (usage_count_it == state.tensor_usage_counts.end()) {
        VLOG(1) << "Tensor " << id << " not used";
        continue;
      }
      usage_count_it->second--;
      if (usage_count_it->second > 0) {
        VLOG(1) << "Tensor " << id << " usage count " << usage_count_it->second;
        continue;
      }

  if (!status->status.ok()) {
    return 0;
  }
  return op_reg_data->op_def.is_stateful();
}

void TF_InitMain(const char* usage, int* argc, char*** argv) {
  tensorflow::port::InitMain(usage, argc, argv);
}

int TF_PickUnusedPortOrDie() {
  return tensorflow::internal::PickUnusedPortOrDie();
}

TFE_TensorHandle* TFE_NewTensorHandleFromScalar(TF_DataType data_type,