class_docstr: Base class for models
class_docstr_tok: ["Base","class","for","models"]
docstr: Apply drops upon the input value.
  
  Args:
      logit (object): The input value.
      keep_prob (float): The probability of keeping each element.
  
  Returns:
      object: A tensor of the same shape of logit.
docstr_tok: ["Apply","drops","upon","the","input","value",".","Args",":","logit","(","object",")",":","The","input","value",".","keep_prob","(","float",")",":","The","probability","of","keeping","each","element",".","Returns",":","object",":","A","tensor","of","the","same","shape","of","logit","."]
code: def _dropout(self, logit, keep_prob):
      """Apply drops upon the input value.
  
      Args:
          logit (object): The input value.
          keep_prob (float): The probability of keeping each element.
  
      Returns:
          object: A tensor of the same shape of logit.
      """
      return tf.nn.dropout(x=logit, rate=1 - (keep_prob))
  
imports: from os.path import join
  import abc
  import time
  import os
  import numpy
  import tensorflow
  from recommenders.models.deeprec.deeprec_utils import cal_metric
label_desc: Use image node_id 16 for calling the BaseModel obj's underlying member method code with example usage: obj._dropout(logit, keep_prob) and returns: tf