def __init__(self, n_in, n_out, activation_fn=sigmoid, p_dropout=0.0):
self.n_in = n_in
self.n_out = n_out
self.activation_fn = activation_fn
self.p_dropout = p_dropout
# Initialize weights and biases
self.w = theano.shared(
np.asarray(
np.random.normal(
loc=0.0, scale=np.sqrt(1.0/n_out), size=(n_in, n_out)),
dtype=theano.config.floatX),
name='w', borrow=True)
self.b = theano.shared(
np.asarray(np.random.normal(loc=0.0, scale=1.0, size=(n_out,)),
dtype=theano.config.floatX),
name='b', borrow=True)
self.params = [self.w, self.b]
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