code: def test_transform_thin_plate_spline_shift(self):
      from lasagne.layers import InputLayer, TPSTransformerLayer
      from theano.tensor import constant
  
      batchsize = 5
      num_control_points = 16
      dest_offset = np.ones(shape=(batchsize, 2 * num_control_points))
      l_in = InputLayer((batchsize, 3, 28, 28))
      l_loc = InputLayer((batchsize, 2 * num_control_points))
      layer = TPSTransformerLayer(
          l_in, l_loc, control_points=num_control_points
      )
      image = np.zeros(shape=(28, 28))
      image[[0, -1], :] = 1
      image[:, [0, -1]] = 1
      inputs = np.tile(image, (batchsize, 3, 1, 1))
      shifted_input = np.ones(shape=(28, 28))
      shifted_input[:13, :13] = 0
      shifted_input[13, :13] = 0.50000271
      shifted_input[:13, 13] = 0.50000271
      shifted_input[13, 13] = 0.75000271
      shifted_input = np.tile(shifted_input, (batchsize, 3, 1, 1))
      outputs = layer.get_output_for(
          [constant(inputs), constant(dest_offset)]
      ).eval()
      np.testing.assert_allclose(shifted_input, outputs, atol=1e-5)
  
imports: from mock import Mock
  import numpy
  import pytest
  import theano
  from lasagne.layers import InputLayer, standardize, get_output, get_all_params
  from lasagne.utils import floatX
label_desc: Use image node_id 5 for calling the TestTPSTransformLayer obj's underlying member method code with example usage: obj.test_transform_thin_plate_spline_shift() without return types