)

filegroup(
    name = "device_headers",
    srcs = ["parallel_device.h"],
)

filegroup(
    name = "device_sources",
    srcs = ["parallel_device.cc"],
)

filegroup(
    name = "headers",
    srcs = [
        ":device_headers",
        ":lib_headers",
    ],
    visibility = ["//tensorflow/python:__pkg__"],
)

filegroup(
    name = "sources",
    srcs = [
        ":device_sources",

        "@local_tsl//tsl/platform:test",
        "@local_tsl//tsl/platform:test_main",
    ],
)

tf_cuda_library(
    name = "checkpoint_reader",
    srcs = ["checkpoint_reader.cc"],
    hdrs = ["checkpoint_reader.h"],
    visibility = ["//visibility:public"],
    deps = [
        ":tf_status",
        ":tf_status_helper",
        "//tensorflow/core:framework",

    ],
)

filegroup(
    name = "headers",
    srcs = [
        "c_api.h",
        "c_api_experimental.h",
        "dlpack.h",
    ],
    visibility = ["//tensorflow:__subpackages__"],
)

filegroup(
    name = "pywrap_headers_monitoring_reader",
    srcs = [
        "c_api_experimental_reader.h",
        "tfe_monitoring_reader_internal.h",
    ],

NUMPY_ANNOTATIONS = {
    "numpy": package_annotation(
        additive_build_content = """\
filegroup(
    name = "includes",
    srcs = glob(["site-packages/numpy/core/include/**/*.h"]),
)
cc_library(
    name = "numpy_headers",
    hdrs = [":includes"],
    strip_include_prefix="site-packages/numpy/core/include/",
)
""",
    ),
}

pip_parse(
    name = "pypi",
    annotations = NUMPY_ANNOTATIONS,

        "tf_exported_symbols.lds",
        "tf_private_symbols.lds",
    ],
)

genrule(
    name = "install_headers",
    srcs = [
        "//tensorflow/c:headers",
        "//tensorflow/c/eager:headers",
        "//tensorflow/cc:headers",
        "//tensorflow/core:headers",
        "@local_xla//xla/stream_executor:stream_executor_install_hdrs",
    ],
    outs = ["include"],
    cmd = """

    *   Moving the checkpoint reader from `swig` to `pybind11`.
    *   `tf.device` & `MirroredStrategy` now supports passing in a
        `tf.config.LogicalDevice`
    *   If you're building Tensorflow from source, consider using
        [bazelisk](https://github.com/bazelbuild/bazelisk) to automatically
        download and use the correct Bazel version. Bazelisk reads the

  TF_CheckpointReader* reader = new TF_CheckpointReader(filename, status);
  if (!status->status.ok()) {
    TF_DeleteCheckpointReader(reader);
    return nullptr;
  }
  const auto& m = reader->GetVariableToDataTypeMap();
  for (auto it = m.begin(); it != m.end(); ++it)
    reader->variable_list.push_back(it->first);
  std::sort(reader->variable_list.begin(), reader->variable_list.end());
  return reader;
}

    hdrs = ["ram_file_block_cache.h"],
    deps = [
        ":cleanup",
        "//tensorflow/c:env",
        "//tensorflow/c:logging",
        "//tensorflow/c:tf_status",
        "@com_google_absl//absl/base:core_headers",
        "@com_google_absl//absl/synchronization",
    ],
)

tf_cc_test(
    name = "ram_file_block_cache_test",
    size = "small",
    srcs = ["ram_file_block_cache_test.cc"],
    deps = [

build:mkl_aarch64_threadpool --define=build_with_mkl_aarch64=true
build:mkl_aarch64_threadpool -c opt

# CUDA: This config refers to building CUDA op kernels with nvcc.
build:cuda --repo_env TF_NEED_CUDA=1
build:cuda --crosstool_top=@local_config_cuda//crosstool:toolchain
build:cuda --@local_config_cuda//:enable_cuda

# CUDA: This config refers to building CUDA op kernels with clang.
build:cuda_clang --config=cuda

def set_tf_cuda_paths(environ_cp):
  """Set TF_CUDA_PATHS."""
  ask_cuda_paths = (
      'Please specify the comma-separated list of base paths to look for CUDA '
      'libraries and headers. [Leave empty to use the default]: ')
  tf_cuda_paths = get_from_env_or_user_or_default(environ_cp, 'TF_CUDA_PATHS',
                                                  ask_cuda_paths, '')
  if tf_cuda_paths: