raise TypeError('`--print` or `--xml-out-path` must be specified')

  return parsed_args


def parse_log(file_path: str,
              verbose: bool = False) -> ResultDictType:
  """Finds ResultStore links, and tries to determine their status."""
  with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
    log_lines = f.read().splitlines()

  result_store_links: ResultDictType = {}

  return timer_seconds_() - block->timestamp <= max_staleness_;
}

std::shared_ptr<RamFileBlockCache::Block> RamFileBlockCache::Lookup(
    const Key& key) {
  absl::MutexLock lock(&mu_);
  auto entry = block_map_.find(key);
  if (entry != block_map_.end()) {
    if (BlockNotStale(entry->second)) {
      return entry->second;
    } else {
      // Remove the stale block and continue.
      RemoveFile_Locked(key.first);
    }
  }

            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f
      - name: Clean repository
        shell: bash
        run: find /home/ubuntu/actions-runner/_work/tensorflow/tensorflow/. -name . -o -prune -exec sudo rm -rf -- {} + || true
      - name: Checkout repository
        uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1

    ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
    string device_name(dev);
    if (device_name.find("GPU:0") != string::npos) {
      has_gpu0 = true;
    }
    if (device_name.find("GPU:1") != string::npos) {
      has_gpu1 = true;
    }
  }

  const char* kCPUDevice = "CPU:0";
  if (!has_gpu0 || !has_gpu1) {
    TF_DeleteDeviceList(devices);

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_0);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  {
    const std::vector<std::string>& device_names = ListDeviceNames(ctx_1);
    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

                                                      "a_dir", "another_dir"};
  EXPECT_EQ(children.size(), filenames.size() + dirnames.size());
  for (const auto& child : expected_children)
    EXPECT_NE(std::find(children.begin(), children.end(), child),
              children.end());
}

TEST_P(ModularFileSystemTest, TestGetChildrenEmpty) {
  const std::string dirpath = GetURIForPath("dir");

                                      size_t n, char* buffer,
                                      TF_Status* status) -> int64_t {
    EXPECT_EQ(n, block_size);
    EXPECT_EQ(offset % block_size, 0);
    EXPECT_EQ(calls.find(offset), calls.end()) << "at offset " << offset;
    calls.insert(offset);
    memset(buffer, 'x', n);
    TF_SetStatus(status, TF_OK, "");
    return n;
  };
  const uint32 block_count = 256;

    ASSERT_GE(op_list.op_size(), 1);
    typedef tensorflow::protobuf::RepeatedPtrField<tensorflow::OpDef> OpDefs;
    const OpDefs& ops = op_list.op();
    bool found = std::find_if(ops.begin(), ops.end(),
                              [](const tensorflow::OpDef& op_def) {
                                return op_def.name() == "TestCApi";
                              }) != ops.end();

  /// arguments for all other methods in the filesystem API.
  ///
  /// DEFAULT IMPLEMENTATION: Uses `io::CleanPath` and `io::ParseURI`.
  char* (*translate_name)(const TF_Filesystem* filesystem, const char* uri);

  /// Finds all entries in the directory given by `path`.
  ///
  /// The returned entries are paths relative to `path`.
  ///
  /// Plugins must allocate `entries` to hold all names that need to be returned

# TF_LoadLibrary/tf.load_op_library) register their ops and kernels with this
# shared object directly.
#
# For example, from Python tf.load_op_library loads a custom op library (via
# dlopen() on Linux), the library finds libtensorflow_framework.so (no
# filesystem search takes place, since libtensorflow_framework.so has already
# been loaded by pywrap_tensorflow) and registers its ops and kernels via