class_docstr: Neural Network ensemble class.
  
  Parameters
  ----------
  networks : list
      List of the Neural Networks.
  ensemble_fn : function or callable, optional
      Ensemble function to be applied to the predictions of the neural
      network ensemble (default: average predictions).
  num_threads : int, optional
      Number of parallel working threads.
  
  Notes
  -----
  If `ensemble_fn` is set to 'None', the predictions are returned as a list
  with the same length as the number of networks given.
  
  Examples
  --------
  Create a NeuralNetworkEnsemble from the networks. Instead of supplying
  the neural networks as parameter, they can also be loaded from file:
  
  >>> from madmom.models import ONSETS_BRNN_PP
  >>> nn = NeuralNetworkEnsemble.load(ONSETS_BRNN_PP)
  >>> nn  # doctest: +ELLIPSIS
  <madmom.ml.nn.NeuralNetworkEnsemble object at 0x...>
  >>> nn(np.array([[0], [0.5], [1], [0], [1], [2], [0]]))
  ... # doctest: +NORMALIZE_WHITESPACE
  array([0.00116, 0.00213, 0.01428, 0.00729, 0.0088 , 0.21965, 0.00532])
docstr: Instantiate a new Neural Network ensemble from a list of files.
  
  Parameters
  ----------
  nn_files : list
      List of neural network model file names.
  kwargs : dict, optional
      Keyword arguments passed to NeuralNetworkEnsemble.
  
  Returns
  -------
  NeuralNetworkEnsemble
      NeuralNetworkEnsemble instance.
docstr_tok: ["Instantiate","a","new","Neural","Network","ensemble","from","a","list","of","files",".","Parameters","--","--","--","--","--","nn_files",":","list","List","of","neural","network","model","file","names",".","kwargs",":","dict",",","optional","Keyword","arguments","passed","to","NeuralNetworkEnsemble",".","Returns","--","--","--","-","NeuralNetworkEnsemble","NeuralNetworkEnsemble","instance","."]
code: def load(cls, nn_files, **kwargs):
      """
      Instantiate a new Neural Network ensemble from a list of files.
  
      Parameters
      ----------
      nn_files : list
          List of neural network model file names.
      kwargs : dict, optional
          Keyword arguments passed to NeuralNetworkEnsemble.
  
      Returns
      -------
      NeuralNetworkEnsemble
          NeuralNetworkEnsemble instance.
  
      """
      networks = [NeuralNetwork.load(f) for f in nn_files]
      return cls(networks, **kwargs)
  
file_path: madmom/madmom/ml/nn/__init__.py
imports: from __future__ import absolute_import, division, print_function
  import numpy
  from ...processors import Processor, ParallelProcessor, SequentialProcessor
label_desc: Use image node_id 2 for calling the NeuralNetworkEnsemble obj's underlying member method code with example usage: obj.load(cls, nn_files) and returns: cls