code: def Exact_Match_Ratio(
      y_pred: Tensor,
      y_true: Tensor,
      sigmoid: bool = True,
      thresh: float = CLASSIFICATION_THRESHOLD,
      normalize: bool = True,
      sample_weight=None,
      **kwargs,
  ):
      if sigmoid:
          y_pred = y_pred.sigmoid()
      y_pred = (y_pred > thresh).float()
      return accuracy_score(
          y_true,
          y_pred,
          normalize=normalize,
          sample_weight=sample_weight,
      )
  
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 7 for calling a global function with example usage: Exact_Match_Ratio(y_pred, y_true, sigmoid, thresh, normalize, sample_weight) and returns: accuracy_score