def build_bottleneck_layer(input_size, encode_size, sigma=0.3):
W = theano.shared(GlorotUniform().sample(shape=(input_size, encode_size)))
layers = [
(InputLayer, {'shape': (None, input_size)}),
(GaussianNoiseLayer, {'name': 'corrupt', 'sigma': sigma}),
(DenseLayer, {'name': 'encoder', 'num_units': encode_size, 'nonlinearity': linear, 'W': W}),
(DenseLayer, {'name': 'decoder', 'num_units': input_size, 'nonlinearity': linear, 'W': W.T}),
]
return W, layers
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