class_docstr: Materializes reports.
  
  Specifically it materializes a subnetwork's :class:`adanet.subnetwork.Report`
  instances into :class:`adanet.subnetwork.MaterializedReport` instances.
  
  Requires an input function `input_fn` that returns a tuple of:
  
  * features: Dictionary of string feature name to `Tensor`.
  * labels: `Tensor` of labels.
  
  Args:
    input_fn: The input function.
    steps: Number of steps for which to materialize the ensembles. If an
      `OutOfRangeError` occurs, materialization stops. If set to None, will
      iterate the dataset until all inputs are exhausted.
  
  Returns:
    A `ReportMaterializer` instance.
docstr: Return the number of steps.
docstr_tok: ["Return","the","number","of","steps","."]
code: def steps(self):
      """Return the number of steps."""
      return self._steps
  
file_path: adanet/adanet/core/report_materializer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from absl import logging
  from adanet import subnetwork
  from adanet import tf_compat
  import tensorflow.compat.v2
label_desc: Use image node_id 3 for calling the ReportMaterializer obj's underlying member method code with example usage: obj.steps() and returns: self