<li><a href="http://sponge/target:$KOKORO_JOB_NAME">Sponge - recent jobs</a></li>
<li><a href="http://fusion2/ci/kokoro/prod:$(echo "$KOKORO_JOB_NAME" | sed 's!/!%2F!g')">Test Fusion - recent jobs</a></li>
<li><a href="http://cs/f:devtools/kokoro/config/prod/$KOKORO_JOB_NAME">Codesearch - job definition</a></li>

**Libtensorflow Windows GPU** | Status Temporarily Unavailable                                                                                                                                                   | [Nightly Binary](https://storage.googleapis.com/libtensorflow-nightly/prod/tensorflow/release/windows/lates...

#     flag_values = {":tf_no_prod_deps": "True"},
# )
#
# selects.config_setting_group(
#     name = "no_prod_deps",
#     match_any = [
#         ":no_prod_deps_define",
#         ":no_prod_deps_flag",
#     ],
# )
#
# config_setting(
#     name = "no_prod_deps_cuda",
#     define_values = {
#         "tf_no_prod_deps": "1",
#         "GOOGLE_CUDA_COMPILER": "clang",
#     },

        including complex types (if supported): `tf.math.segment_prod`,
        `tf.math.segment_sum`, `tf.math.unsorted_segment_mean`,
        `tf.math.unsorted_segment_sqrt_n`, `tf.math.unsorted_segment_prod`,
        `tf.math.unsorted_segment_sum`, and therefore also
        `tf.convert_to_tensor` when `value` is of type `tf.IndexedSlices` (such
        as in the back prop though `tf.gather` into a dense embedding). See

  struct stat st;
  fstat(fd, &st);
  if (S_ISDIR(st.st_mode)) {
    TF_SetStatus(status, TF_FAILED_PRECONDITION, "path is a directory");
  } else {
    const void* address =
        mmap(nullptr, st.st_size, PROT_READ, MAP_PRIVATE, fd, 0);
    if (address == MAP_FAILED) {
      TF_SetStatusFromIOError(status, errno, path);
    } else {
      region->plugin_memory_region =

  if not paths:
    raise FileNotFoundError(
        "Can't find 'find_cuda_config.py' script inside working directory")
  proc = subprocess.Popen(
      [environ_cp['PYTHON_BIN_PATH'], paths[0]] + cuda_libraries,
      stdout=subprocess.PIPE,
      env=maybe_encode_env(environ_cp))

  if proc.wait():
    # Errors from find_cuda_config.py were sent to stderr.
    print('Asking for detailed CUDA configuration...\n')