class_docstr: Two convolutional layers, number of output channels are ``n_chns`` for both
  of them.
  
  --conv--conv--
code: def __init__(self, n_chns, conv_params):
      TrainableLayer.__init__(self, name="TwoConv")
      self.n_chns = n_chns
      self.conv_params = conv_params
  
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from niftynet.layer.base_layer import TrainableLayer, Layer
  from niftynet.layer.convolution import ConvolutionalLayer
  from niftynet.layer.crop import CropLayer
  from niftynet.layer.deconvolution import DeconvolutionalLayer
  from niftynet.layer.downsample import DownSampleLayer
  from niftynet.layer.elementwise import ElementwiseLayer
  from niftynet.layer.linear_resize import LinearResizeLayer
  from niftynet.network.base_net import BaseNet
label_desc: Use image node_id 1 to create a new TwoLayerConv object from inherited base classes: TrainableLayer with example: obj = TwoLayerConv(n_chns, conv_params)