class_docstr: Data collected about a :class:`adanet.subnetwork.Subnetwork`.
  
  Args:
    iteration_number: A python integer for the AdaNet iteration number, starting
      from 0.
    name: A string, which is either the name of the corresponding Builder, or
      "previous_ensemble" if it refers to the previous_ensemble.
    hparams: A dict mapping strings to python strings, ints, or floats. These
      are constants passed from the author of the
      :class:`adanet.subnetwork.Builder` that was used to construct this
      :class:`adanet.subnetwork.Subnetwork`. It is meant to contain the
      arguments that defined the :class:`adanet.subnetwork.Builder`, such as
      dropout, number of layers, or initial learning rate.
    attributes: A dict mapping strings to python strings, ints, bools, or
      floats. These are python primitives that come from materialized Tensors;
      these Tensors were defined by the author of the
      :class:`adanet.subnetwork.Builder` that was used
      to construct this :class:`adanet.subnetwork.Subnetwork`. It is meant to
      contain properties that may or may not change over the course of
      training the :class:`adanet.subnetwork.Subnetwork`, such as the number of
      parameters, the Lipschitz constant, or the :math:`L2` norm of the weights.
    metrics: A dict mapping strings to python strings, ints, or floats. These
      are python primitives that come from metrics that were evaluated on the
      trained :class:`adanet.subnetwork.Subnetwork` over some dataset; these
      metrics were defined by the author of the
      :class:`adanet.subnetwork.Builder` that was used to construct this
      :class:`adanet.subnetwork.Subnetwork`. It is meant to contain
      performance metrics or measures that could predict generalization, such
      as the training loss, complexity regularized loss, or standard deviation
      of the last layer outputs.
    included_in_final_ensemble: A boolean denoting whether the associated
      :class:`adanet.subnetwork.Subnetwork` was included in the ensemble at the
      end of the AdaNet iteration.
  
  Returns:
    An :class:`adanet.subnetwork.MaterializedReport` object.
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code: def __new__(
      cls,
      iteration_number,
      name,
      hparams,
      attributes,
      metrics,
      included_in_final_ensemble=False,
  ):
      return super(MaterializedReport, cls).__new__(
          cls,
          iteration_number=iteration_number,
          name=name,
          hparams=hparams,
          attributes=attributes,
          metrics=metrics,
          included_in_final_ensemble=included_in_final_ensemble,
      )
  
file_path: adanet/adanet/subnetwork/report.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from adanet import tf_compat
  import six
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling the MaterializedReport obj's underlying member method code with example usage: obj.__new__(cls, iteration_number, name, hparams, attributes, metrics, included_in_final_ensemble) and returns: super