class_docstr: Training callback which allows collecting batch training times. The primary use is epoch training time estimation in adaptive epoch number selection.
class_docstr_tok: ["Training","callback","which","allows","collecting","batch","training","times",".","The","primary","use","is","epoch","training","time","estimation","in","adaptive","epoch","number","selection","."]
code: def __init__(self, batches_to_measure):
      self.batches_to_measure = batches_to_measure
      self.batches_finished = 0
      self.batch_start_time = None
      self.batch_measured_time = None
  
imports: import logging
  import time
  import numpy
  from fastai.callback.core import Callback, CancelFitException
  from fastai.callback.tracker import TrackerCallback
  from fastcore.basics import store_attr
label_desc: Use image node_id 1 to create a new BatchTimeTracker object from inherited base classes: Callback with example: obj = BatchTimeTracker(batches_to_measure)