nn.functional.relu(self.fc1(x))
时间: 2024-02-01 07:03:45 浏览: 59
This code snippet represents the activation function used in a neural network model. Specifically, it applies the ReLU (Rectified Linear Unit) function to the output of the first fully connected layer (fc1) in the neural network.
The ReLU function takes the input value x and returns the maximum between 0 and x. In other words, if x is positive, the function returns x; if x is negative, the function returns 0.
By applying the ReLU function to the output of the fc1 layer, the neural network is able to introduce non-linearity into the model. Non-linearity is important because many real-world problems are not linearly separable, and therefore require non-linear transformations to solve effectively.