parameters: (self, nr_inputs, nr_outputs, layers_file, params_file, output_layer_name, discount_factor)
docstring: Initialize a NeuralNet
  
          @param nr_inputs: number of inputs in data layer
          @param nr_outputs: number of target values in another data layer
          @param layers_file: path to layers file
          @param params_file: path to params file
          @param output_layer_name: name of the output layer
docstring_summary: Initialize a NeuralNet
docstring_tokens: Initialize a NeuralNet
function: def __init__(self, nr_inputs, nr_outputs, layers_file, params_file, output_layer_name, discount_factor):
          """
          Initialize a NeuralNet
  
          @param nr_inputs: number of inputs in data layer
          @param nr_outputs: number of target values in another data layer
          @param layers_file: path to layers file
          @param params_file: path to params file
          @param output_layer_name: name of the output layer
          """
  
          # Save data parameters
          self.discount_factor = discount_factor
          self.nr_inputs = nr_inputs
          self.nr_outputs = nr_outputs
          SimpleDataProvider.dims = (nr_inputs, nr_outputs)
  
          # Save layer parameters
          self.layers_file = layers_file
          self.params_file = params_file
          self.output_layer_name = output_layer_name
          
          # Initialise ConvNet, including self.libmodel
          op = NeuralNet.get_options_parser()
          op, load_dic = IGPUModel.parse_options(op)
          ConvNet.__init__(self, op, load_dic)
function_tokens: def __init__ ( self , nr_inputs , nr_outputs , layers_file , params_file , output_layer_name , discount_factor ) : # Save data parameters self . discount_factor = discount_factor self . nr_inputs = nr_inputs self . nr_outputs = nr_outputs SimpleDataProvider . dims = ( nr_inputs , nr_outputs ) # Save layer parameters self . layers_file = layers_file self . params_file = params_file self . output_layer_name = output_layer_name # Initialise ConvNet, including self.libmodel op = NeuralNet . get_options_parser ( ) op , load_dic = IGPUModel . parse_options ( op ) ConvNet . __init__ ( self , op , load_dic )