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import numpy as np
import theano
import theano.tensor as T

class Layer(object):
    def __init__(self, inputs, in_size, out_size, activation_function=None):
        self.w = theano.shared(np.random.normal(0,1,(in_size, out_size)))
        self.b = theano.shared(np.zeros(out_size,) + 0.1)
        self.wx_plus_b = T.dot(inputs, w) + self.b
        self.activation_function = activation_function
        if activation_function == None:
            self.outputs = self.wx_plus_b
        else:
            self.outputs = self.activation_function(self.wx_plus_b)
    
l1 = Layer(inputs, 10, 1, T.nnet.relu)