class_docstr: Core trainable object in OpenNMT. Implements a trainable interface
  for a simple, generic encoder / decoder or decoder only model.
  
  Args:
    encoder (onmt.encoders.EncoderBase): an encoder object
    decoder (onmt.decoders.DecoderBase): a decoder object
class_docstr_tok: ["Core","trainable","object","in","OpenNMT",".","Implements","a","trainable","interface","for","a","simple",",","generic","encoder","\/","decoder","or","decoder","only","model",".","Args",":","encoder","(","onmt.encoders.EncoderBase",")",":","an","encoder","object","decoder","(","onmt.decoders.DecoderBase",")",":","a","decoder","object"]
code: def count_parameters(self, log=print):
      raise NotImplementedError
  
imports: import torch
  import torch.nn
  from glob import glob
label_desc: Use image node_id 4 for calling the BaseModel obj's underlying member method code with example usage: obj.count_parameters(log) without return types