def test_math_layer(self):
addto = layer.addto(input=[pixel, pixel])
linear_comb = layer.linear_comb(weights=weight, vectors=hidden, size=10)
interpolation = layer.interpolation(
input=[hidden, hidden], weight=score)
bilinear = layer.bilinear_interp(input=conv, out_size_x=4, out_size_y=4)
power = layer.power(input=pixel, weight=score)
scaling = layer.scaling(input=pixel, weight=score)
slope = layer.slope_intercept(input=pixel)
tensor = layer.tensor(a=pixel, b=pixel, size=1000)
cos_sim = layer.cos_sim(a=pixel, b=pixel)
trans = layer.trans(input=tensor)
print layer.parse_network(addto, linear_comb, interpolation, power,
scaling, slope, tensor, cos_sim, trans)
def test_math_layer(self):
addto = layer.addto(input=[pixel, pixel])
linear_comb = layer.linear_comb(
weights=combine_weight, vectors=hidden, size=10)
interpolation = layer.interpolation(
input=[hidden, hidden], weight=score)
bilinear = layer.bilinear_interp(input=conv, out_size_x=4, out_size_y=4)
power = layer.power(input=pixel, weight=score)
scaling = layer.scaling(input=pixel, weight=score)
slope = layer.slope_intercept(input=pixel)
tensor = layer.tensor(a=pixel, b=pixel, size=1000)
cos_sim = layer.cos_sim(a=pixel, b=pixel)
trans = layer.trans(input=tensor)
print layer.parse_network([
addto, linear_comb, interpolation, power, scaling, slope, tensor,
cos_sim, trans
])