def make_last_layer(l3,w_shape,p_drop_hidden=0.0):
w_h = ml_tools.init_kernels(w_shape[0])
hidden_layer = rectify(T.dot(l3, w_h))
l4 = dropout(hidden_layer, p_drop_hidden)
w_o = ml_tools.init_kernels(w_shape[1])
out_layer = softmax(T.dot(l4, w_o))
last_layer=LastLayer(hidden_layer,w_h,out_layer,w_o)
return last_layer
def make_conv_layer(in_data,w_shape,p_drop_conv=0.0,
first=False,flat=False):
w = ml_tools.init_kernels(w_shape)
if(first):
la = rectify(conv2d(in_data, w, border_mode='full'))
else:
la = rectify(conv2d(in_data, w))
l = max_pool_2d(la, (2, 2))
if(flat):
l = T.flatten(l, outdim=2)
layer=dropout(l, p_drop_conv)
return ConvLayer(layer,w)