class_docstr: A class for modifying a neural nework using many of the operations above. 
class_docstr_tok: ["A","class","for","modifying","a","neural","nework","using","many","of","the","operations","above","."]
docstr: Constructor. 
docstr_tok: ["Constructor","."]
code: def __init__(
      self, constraint_checker=None, options=None, reporter=None
  ):
      """Constructor."""
      self.reporter = get_reporter(reporter)
      self.constraint_checker = constraint_checker
      if options is None:
          options = load_options(nn_modifier_args)
      self.options = options
  
imports: from argparse import Namespace
  from copy import deepcopy
  import numpy
  from .neural_network import ConvNeuralNetwork, MultiLayerPerceptron, MLP_RECTIFIERS, MLP_SIGMOIDS, is_a_pooling_layer_label, is_a_conv_layer_label, CNNImageSizeMismatchException, CNNNoConvAfterIPException
  from ..utils.general_utils import reorder_list_or_array, reorder_rows_and_cols_in_matrix
  from ..utils.option_handler import get_option_specs, load_options
  from ..utils.reporters import get_reporter
label_desc: Use image node_id 1 to create a new NNModifier object from inherited base classes: object with example: obj = NNModifier(constraint_checker, options, reporter)