class_docstr: Resize 2D/3D images using ``tf.image.resize_bilinear``
  (without trainable parameters).
docstr: :param new_size: integer or a list of integers set the output
      2D/3D spatial shape.  If the parameter is an integer ``d``,
      it'll be expanded to ``(d, d)`` and ``(d, d, d)`` for 2D and
      3D inputs respectively.
  :param name: layer name string
code: def __init__(self, new_size, name="trilinear_resize"):
      """
  
      :param new_size: integer or a list of integers set the output
          2D/3D spatial shape.  If the parameter is an integer ``d``,
          it'll be expanded to ``(d, d)`` and ``(d, d, d)`` for 2D and
          3D inputs respectively.
      :param name: layer name string
      """
      super(LinearResizeLayer, self).__init__(name=name)
      self.new_size = new_size
  
file_path: NiftyNet/niftynet/layer/linear_resize.py
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from niftynet.layer.base_layer import Layer
  from niftynet.layer.layer_util import expand_spatial_params
  from niftynet.layer.layer_util import infer_spatial_rank
label_desc: Use image node_id 1 to create a new LinearResizeLayer object from inherited base classes: Layer with example: obj = LinearResizeLayer(new_size, name)