Method set_weights

tensorflow/python/keras/engine/base_layer.py:1329–1360

Sets the weights of the layer, from Numpy arrays. Arguments: weights: a list of Numpy arrays. The number of arrays and their shape must match number of the dimensions of the weights of the layer (i.e. it should match the output of `get_wei

(self, weights)

    self._updates += updates

  def set_weights(self, weights):
    """Sets the weights of the layer, from Numpy arrays.

    Arguments:
        weights: a list of Numpy arrays. The number
            of arrays and their shape must match
            number of the dimensions of the weights
            of the layer (i.e. it should match the
            output of `get_weights`).

    Raises:
        ValueError: If the provided weights list does not match the
            layer's specifications.
    """
    params = self.weights
    if len(params) != len(weights):
      raise ValueError('You called `set_weights(weights)` on layer "' +
                       self.name + '" with a  weight list of length ' +
                       str(len(weights)) + ', but the layer was expecting ' +
                       str(len(params)) + ' weights. Provided weights: ' +
                       str(weights)[:50] + '...')
    if not params:
      return
    weight_value_tuples = []
    for p, w in zip(params, weights):
      ref_shape = p.shape
      if not ref_shape.is_compatible_with(w.shape):
        raise ValueError('Layer weight shape ' + str(ref_shape) +
                         ' not compatible with '
                         'provided weight shape ' + str(w.shape))
      weight_value_tuples.append((p, w))
    backend.batch_set_value(weight_value_tuples)

  def get_weights(self):
    """Returns the current weights of the layer.