class_docstr: Keeper of structured log for intermediate values during sampling.
class_docstr_tok: ["Keeper","of","structured","log","for","intermediate","values","during","sampling","."]
docstr: Context manager that logs to a section nested one level deeper.
  
  Args:
    label: A short name for the section.
    subsample_factor: Rate at which to subsample logging in this section.
  
  Yields:
    yields to caller.
docstr_tok: ["Context","manager","that","logs","to","a","section","nested","one","level","deeper",".","Args",":","label",":","A","short","name","for","the","section",".","subsample_factor",":","Rate","at","which","to","subsample","logging","in","this","section",".","Yields",":","yields","to","caller","."]
code: def section(self, label, subsample_factor=None):
      """Context manager that logs to a section nested one level deeper.
  
      Args:
        label: A short name for the section.
        subsample_factor: Rate at which to subsample logging in this section.
  
      Yields:
        yields to caller.
      """
      new_section = _Section(label, subsample_factor=subsample_factor)
      self.stack[-1].log(new_section)
      self.stack.append(new_section)
      yield
      self.stack.pop()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import contextlib
  import os
  from magenta.models.coconet import lib_util
  import numpy
label_desc: Use image node_id 2 for calling the Logger obj's underlying member method code with example usage: obj.section(label, subsample_factor) without return types