class_docstr: trainer based on M-step summary statistics can add mini-batch statistics
  for a full-batch update.
class_docstr_tok: ["trainer","based","on","M-step","summary","statistics","can","add","mini-batch","statistics","for","a","full-batch","update","."]
code: def __call__(self, x):
      self.add(x)
      self.update()
  
file_path: gluonts/src/gluonts/nursery/gmm_tpp/gmm_base.py
imports: import time
  import mxnet
  from mxnet import gluon
  import numpy
label_desc: Use image node_id 5 for calling the GMMTrainer obj's underlying member method code with example usage: obj.__call__(x) without return types