class_docstr: __init__(targets, max_sample_size=1000, report_data=True, report_grad=True, plot_mean=True, plot_std=True, percentile_sigmas=(0, 0.13, 2.28, 15.87, 50, 84.13, 97.72, 99.87, 100), trigger=(1, 'epoch'), filename='statistics.png', figsize=None, marker=None, grid=True)
  
  Trainer extension to plot statistics for :class:`~chainer.Variable`\s.
  
  
  This extension collects statistics for a single :class:`Variable`, a list
  of :class:`Variable`\s or similarly a single or a list of
  :class:`Link`\s containing one or more :class:`Variable`\s. In case
  multiple :class:`Variable`\s are found, the means are computed. The
  collected statistics are plotted and saved as an image in the directory
  specified by the :class:`Trainer`.
  
  Statistics include mean, standard deviation and percentiles.
  
  This extension uses reservoir sampling to preserve memory, using a fixed
  size running sample. This means that collected items in the sample are
  discarded uniformly at random when the number of items becomes larger
  than the maximum sample size, but each item is expected to occur in the
  sample with equal probability.
  
  Args:
      targets (:class:`Variable`, :class:`Link` or list of either):
          Parameters for which statistics are collected.
      max_sample_size (int):
          Maximum number of running samples.
      report_data (bool):
          If ``True``, data (e.g. weights) statistics are plotted.  If
          ``False``, they are neither computed nor plotted.
      report_grad (bool):
          If ``True``, gradient statistics are plotted. If ``False``, they
          are neither computed nor plotted.
      plot_mean (bool):
          If ``True``, means are plotted.  If ``False``, they are
          neither computed nor plotted.
      plot_std (bool):
          If ``True``, standard deviations are plotted.  If ``False``, they
          are neither computed nor plotted.
      percentile_sigmas (float or tuple of floats):
          Percentiles to plot in the range :math:`[0, 100]`.
      trigger:
          Trigger that decides when to save the plots as an image.  This is
          distinct from the trigger of this extension itself. If it is a
          tuple in the form ``<int>, 'epoch'`` or ``<int>, 'iteration'``, it
          is passed to :class:`IntervalTrigger`.
      filename (str):
          Name of the output image file under the output directory.
          For historical reasons ``file_name`` is also accepted as an alias
          of this argument.
      figsize (tuple of int):
          Matlotlib ``figsize`` argument that specifies the size of the
          output image.
      marker (str):
          Matplotlib ``marker`` argument that specified the marker style of
          the plots.
      grid (bool):
          Matplotlib ``grid`` argument that specifies whether grids are
          rendered in in the plots or not.
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code: def available():
      _check_available()
      return _available
  
imports: from __future__ import division
  import os
  import warnings
  import numpy
  import six
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer.training import extension
  from chainer.training import trigger
  from chainer.utils import argument
label_desc: Use image node_id 2 for calling the VariableStatisticsPlot obj's underlying member method code with example usage: obj.available() and returns: _available