)

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",

    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 = [

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,

    ],
)

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",
    ],

        "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 = """

build:windows --copt=/Zc:__cplusplus
build:windows --host_copt=/Zc:__cplusplus

# Tensorflow uses M_* math constants that only get defined by MSVC headers if
# _USE_MATH_DEFINES is defined.
build:windows --copt=/D_USE_MATH_DEFINES
build:windows --host_copt=/D_USE_MATH_DEFINES

# Windows has a relatively short command line limit, which TF has begun to hit.

* `stream_executor`
  * Top level `stream_executor` directory has been deleted, users should use equivalent headers and targets under `compiler/xla/stream_executor`.
* `tf.nn`
  * Added `tf.nn.experimental.general_dropout`, which is similar to `tf.random.experimental.stateless_dropout` but accepts a custom sampler function.

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:

          # The "digest" that allows us to pull an image is not the digest as
          # returned by the API, but a sha256sum of the entire chunk of image
          # metadata. gcr.io helpfully includes it in the header of the response
          # as docker-content-digest: sha256:[digest]. Note we use egrep to
          # match exactly sha256:<hash> because curl may include a ^M symbol at
          # the end of the line.