def forward(self):
if self.alpha.ndim == 1:
return Tensor(np.random.dirichlet(self.alpha.value), function=self)
else:
raise NotImplementedError
def forward(self, x):
self.x = x
if isinstance(self.x, Constant):
return Constant(x.value)
return Tensor(x.value, function=self)
def forward(self):
self.output = np.random.gamma(self.shape.value, 1 / self.rate.value)
if isinstance(self.shape, Constant) and isinstance(
self.rate, Constant):
return Constant(self.output)
return Tensor(self.output, function=self)
def forward(self):
self.eps = np.random.normal(size=self.mu.shape)
output = self.mu.value + self.std.value * self.eps
if isinstance(self.mu, Constant) and isinstance(self.var, Constant):
return Constant(output)
return Tensor(output, self)