def forward(self, x):
W1, b1 = self.params['W1'], self.params['b1']
W2, b2 = self.params['W2'], self.params['b2']
a, fc_cache1 = affine_forward(x, W1, b1)
a2, relu_cache = relu_forward(a)
out, fc_cache2 = affine_forward(a2, W2, b2)
self.cache = (fc_cache1, relu_cache, fc_cache2)
return out
def forward(self, x):
W1, b1 = self.params['W1'], self.params['b1']
W2, b2 = self.params['W2'], self.params['b2']
a, fc_cache1 = affine_forward(x, W1, b1)
a2, relu_cache = relu_forward(a)
out, fc_cache2 = affine_forward(a2, W2, b2)
self.cache = (fc_cache1, relu_cache, fc_cache2)
return out
def forward(self, x):
W, b = self.params['W'], self.params['b']
sigma, mu = self.params['sigma'], self.params['mu']
a, fc_cache = affine_forward(x, W, b)
a2, sigmoid_cache = sigmoid_forward(a)
out, scale_cache = scale_shift_forward(a2, sigma, mu)
self.cache = (fc_cache, sigmoid_cache, scale_cache)
return out
def forward(self, x):
W, b = self.params['W'], self.params['b']
sigma, mu = self.params['sigma'], self.params['mu']
a, fc_cache = affine_forward(x, W, b)
a2, sigmoid_cache = sigmoid_forward(a)
out, scale_cache = scale_shift_forward(a2, sigma, mu)
self.cache = (fc_cache, sigmoid_cache, scale_cache)
return out
def forward(self, x):
W = self.params['W']
b = self.params['b']
out, self.cache = affine_forward(x, W, b)
return out
def forward(self, x):
W = self.params['W']
b = self.params['b']
out, self.cache = affine_forward(x, W, b)
return out
