code: def read_sharded_runtime_tsvs(path_string: str) -> pd.DataFrame:
      """Imports data from a single or sharded path into a pandas dataframe.
  
      Args:
        path_string: The path to the input file, which may be sharded.
  
      Returns:
        A dataframe matching the TSV file(s) but with added Task column.
      """
      if sharded_file_utils.is_sharded_file_spec(path_string):
          paths = sharded_file_utils.generate_sharded_filenames(
              path_string
          )
      else:
          paths = [path_string]
      list_of_dataframes = []
      for i, path in enumerate(paths):
          if path.startswith("gs://"):
              # Once pandas is updated to 0.24+, pd.read_csv will work for gs://
              # without this workaround.
              with tf.io.gfile.GFile(path) as f:
                  d = pd.read_csv(f, sep="\t")
          else:
              d = pd.read_csv(path, sep="\t")
          d["Task"] = i
          list_of_dataframes.append(d)
  
      return pd.concat(list_of_dataframes, axis=0, ignore_index=True)
  
imports: from typing import Dict, Sequence, List, Tuple, Text, Union
  from absl import app
  from absl import flags
  import altair
  import pandas
  import tensorflow
  from third_party.nucleus.io import sharded_file_utils
  from deepvariant import dashboard_utils
label_desc: Use image node_id 1 for calling a global function with example usage: read_sharded_runtime_tsvs(path_string) and returns: pd