deps = [
        ":tf_status_headers",
        "@local_tsl//tsl/platform:status",
        "@local_xla//xla/tsl/c:tsl_status_helper",
    ],
)

tf_cc_test(
    name = "tf_status_helper_test",
    srcs = ["tf_status_helper_test.cc"],
    deps = [
        ":tf_status",
        ":tf_status_helper",
        "@local_tsl//tsl/platform:errors",
        "@local_tsl//tsl/platform:status",

done
popd

# Python 3.10 include headers fix:
# sysconfig.get_path('include') incorrectly points to /usr/local/include/python
# map /usr/include/python3.10 to /usr/local/include/python3.10
if [[ ! -f "/usr/local/include/$VERSION" ]]; then
  ln -sf /usr/include/$VERSION /usr/local/include/$VERSION
fi

# Install pip

#      Ex. linux_x86_cuda   -- x86_64 Linux platform, with Nvidia CUDA support
#      Ex. macos_arm64      -- arm64 MacOS platform
# 3. Add modifiers. Some modifiers for local execution are:
#      Ex. disk_cache -- Use a local cache
#      Ex. public_cache -- Use TF's public cache (read-only)
#      Ex. public_cache_push -- Use TF's public cache (read and write, Googlers only)

}

# Print out any ResultStore URLs for Bazel invocations' results.
# Each failed target there will have its own representation, making failures
# easier to find and read.
function resultstore_extract {
  local \
    XML_PATH="$TFCI_OUTPUT_DIR/Bazel_Test_and_Build_Results/sponge_log.xml"

  python3 \
    "$TFCI_GIT_DIR/ci/official/utilities/extract_resultstore_links.py" \
    "$TFCI_OUTPUT_DIR/script.log" \
    --print \

        "//tensorflow/c:tf_status_internal",
        "//tensorflow/core/platform:env",
        "//tensorflow/core/platform:errors",
        "//tensorflow/core/platform:status",
        "@local_tsl//tsl/platform:errors",
    ],
)

# Compliance test for modules and for interface
tf_cc_test(
    name = "modular_filesystem_test",
    size = "small",
    srcs = ["modular_filesystem_test.cc"],

TF_CAPI_EXPORT extern bool TFE_ContextCheckAlive(TFE_Context* ctx,
                                                 const char* worker_name,
                                                 TF_Status* status);

// Sync pending nodes in local executors (including the context default executor
// and thread executors) and streaming requests to remote executors, and get the
// combined status.
TF_CAPI_EXPORT extern void TFE_ContextAsyncWait(TFE_Context* ctx,

    ```

    If the tests are to be run on the GPU, add CUDA paths to LD_LIBRARY_PATH and
    add the `cuda` option flag

    ```bash
    export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH"
    export flags="--config=opt --config=cuda -k"
    ```

    For example, to run all tests under tensorflow/python, do:

    ```bash

# directories.
mkdir -p "${TARGET}/usr/include/aarch64-linux-gnu"
PYTHON_VERSIONS=("python3.8" "python3.9" "python3.10" "python3.11")
for v in "${PYTHON_VERSIONS[@]}"; do
  ln -s "/usr/local/include/${v}" "${TARGET}/usr/include/aarch64-linux-gnu/${v}"

    return nullptr;
  }
  tensorflow::TensorHandle* handle =
      tensorflow::TensorHandleFromInterface(tensorflow::unwrap(h));
  if (handle->Type() != TensorHandle::LOCAL) {
    status->status = tensorflow::errors::InvalidArgument(
        "DLPack doesn't support ", handle->TypeString(), " tensor");
    return nullptr;
  }
  const tensorflow::Tensor* tensor;

    case DT_RESOURCE:
    case DT_VARIANT:
      return true;
    case DT_QINT8:
    case DT_QINT16:
    case DT_QINT32:
    case DT_QUINT8:
    case DT_QUINT16:
      return tensorflow::flags::Global()
          .enable_quantized_dtypes_training.value();
    default:
      return false;
  }
}

template <typename Gradient, typename BackwardFunction, typename TapeTensor>