code: def run_forward(model, Xs, n_times=1):
      total = 0.0
      for _ in range(n_times):
          for batch in tqdm.tqdm(Xs):
              Y = model.predict(batch)
              total += Y.data.sum()
      return float(total)
  
file_path: thinc/examples/benchmarks/lstm_tagger.py
imports: from typing import List
  import typer
  import tqdm
  import numpy.random
  from timeit import default_timer
  from thinc.api import Model, Config, registry
  from thinc.api import chain, list2padded, with_array, with_padded
  from thinc.api import to_categorical, set_current_ops
  from thinc.api import Ops, NumpyOps, CupyOps, fix_random_seed, require_gpu
  from thinc.types import Ints1d, Ints2d, Floats2d, Padded
label_desc: Use image node_id 3 for calling a global function with example usage: run_forward(model, Xs, n_times) and returns: float