def __call__(self, output, std):
assert (len(output) == len(std))
lengthStd = len(std)
self.ans = None
for i in range(lengthStd):
v = op.Value("const", std[i])
if self.ans == None:
self.ans = -v * op.log(output[i])
else:
self.ans = self.ans - v * op.log(output[i])
return self
def __init__(self, shape, net, initialWeights=None):
self.net = net
thisNum = len(self.net.linearNames)
self.name = "_Linear" + str(thisNum)
self.net.linearNames[self.name] = shape
if len(shape) != 2:
raise ValueError
self.input_shape = shape[0]
self.output_shape = shape[1]
self.params = []
self.net.weights[self.name] = self.params
for i in range(shape[0]):
self.params.append([])
for j in range(shape[1]):
if initialWeights == None:
self.params[i].append(
op.Value(self.name + str(i) + str(j), 0))
else:
self.params[i].append(
op.Value(self.name + str(i) + str(j),
initialWeights[i][j]))
self.net.weights[self.name] = self.params
def __call__(self, inputArray):
if self.input_shape != len(inputArray):
raise ValueError
output = []
if not isinstance(inputArray[0], op.Op):
inputArray = list(map(lambda t: op.Value("const", t), inputArray))
for j in range(self.output_shape):
res = None
for i in range(self.input_shape):
if res == None:
res = self.params[i][j] * inputArray[i]
else:
res += self.params[i][j] * inputArray[i]
output.append(res)
return output
# test homework function
import op
import numpy as np
import math as m
def npFunc(x1, x2, x3):
return (np.sin(x1 + 1) + np.cos(2 * x2)) * np.tan(np.log(x3)) \
+ (np.sin(x2 + 1) + np.cos(2 * x1)) * np.exp(1 + np.sin(x3))
x1_ = x2_ = x3_ = 2.5
# define a function
x1 = op.Value("x1", 2.5)
x2 = op.Value("x2", 2.5)
x3 = op.Value("x3", 2.5)
const1 = op.Value("const1", 1)
const2 = op.Value("const2", 2)
func = (op.sin(x1 + const1) + op.cos(const2 * x2)) * op.tan(op.log(x3)) \
+ (op.sin(x2 + const1) + op.cos(const2 * x1)) * op.exp(const1 + op.sin(x3))
print("test getRes(): ")
print(func.getRes())
print(npFunc(x1_, x2_, x3_))
print("test Df(): ")
print([func.Df("x1"), func.Df("x2"), func.Df("x3")])
print([
m.cos(x1_ + 1) * m.tan(m.log(x3_)) -
2 * m.sin(2 * x1_) * m.exp(1 + m.sin(x3_)),
def forward(self, x):
init_x = list(map(lambda t: op.Value("const", t), x))
x = Sigmoid(self.fc1(x))
x = listAdd(self.fc2(x), init_x)
# x = self.fc2(x)
return x