code: def F1(
      y_pred: Tensor,
      y_true: Tensor,
      threshold: float = CLASSIFICATION_THRESHOLD,
      **kwargs,
  ):
      return fbeta(y_pred, y_true, thresh=threshold, beta=1)
  
file_path: fast-bert/fast_bert/metrics.py
imports: import numpy
  from torch import Tensor
  from sklearn.metrics import roc_curve, auc, hamming_loss, accuracy_score, confusion_matrix
  import pdb
  import logging
label_desc: Use image node_id 8 for calling a global function with example usage: F1(y_pred, y_true, threshold) and returns: fbeta