code: def get_all_param_values(layer, **tags):
      """
      This function returns the values of the parameters of all layers below one
      or more given :class:`Layer` instances, including the layer(s) itself.
  
      This function can be used in conjunction with set_all_param_values to save
      and restore model parameters.
  
      Parameters
      ----------
      layer : Layer or list
          The :class:`Layer` instance for which to gather all parameter values,
          or a list of :class:`Layer` instances.
  
      **tags (optional)
          tags can be specified to filter the list. Specifying ``tag1=True``
          will limit the list to parameters that are tagged with ``tag1``.
          Specifying ``tag1=False`` will limit the list to parameters that
          are not tagged with ``tag1``. Commonly used tags are
          ``regularizable`` and ``trainable``.
  
      Returns
      -------
      list of numpy.array
          A list of numpy arrays representing the parameter values.
  
      Examples
      --------
      >>> from lasagne.layers import InputLayer, DenseLayer
      >>> l_in = InputLayer((100, 20))
      >>> l1 = DenseLayer(l_in, num_units=50)
      >>> all_param_values = get_all_param_values(l1)
      >>> (all_param_values[0] == l1.W.get_value()).all()
      True
      >>> (all_param_values[1] == l1.b.get_value()).all()
      True
      """
      params = get_all_params(layer, **tags)
      return [p.get_value() for p in params]
  
file_path: Lasagne/lasagne/layers/helper.py
imports: from collections import deque
  from difflib import get_close_matches
  from itertools import chain
  from warnings import warn
  import theano
  import numpy
  from ..None import utils
label_desc: Use image node_id 6 for calling a global function with example usage: get_all_param_values(layer) and returns: unknown