def predict(self, inputs: Tensor) -> Tensor:
# inputs will be (batch_size, 10)
x1 = inputs @ self.w1 + self.b1 # (batch_size, num_hidden)
x2 = tanh(x1) # (batch_size, num_hidden)
x3 = x2 @ self.w2 + self.b2 # (batch_size, 4)
return x3
def forward(self, x: Tensor) -> Tensor:
# inputs will be (batch_size, 10)
x1 = x @ self.w1
x1 = x1 + self.b1 # (batch_size, num_hidden)
x2 = tanh(x1) # (batch_size, num_hidden)
x3 = x2 @ self.w2 + self.b2 # (batch_size, 4)
return x3
def predict(self, inputs: Tensor) -> Tensor:
x1 = inputs @ self.w1 + self.b1
x2 = tanh(x1)
x3 = x2 @ self.w2 + self.b2
return x3