please show the source code of using momentum in pytorch
时间: 2024-01-08 11:03:11 浏览: 34
Sure, here is an example code snippet showing how to use momentum in PyTorch:
```python
import torch
import torch.optim as optim
# Define your model
model = ...
# Define your optimizer with momentum
optimizer = optim.SGD(model.parameters(), lr=0.01, momentum=0.9)
# Train your model
for epoch in range(num_epochs):
for inputs, labels in dataloader:
# Zero the gradients
optimizer.zero_grad()
# Forward pass
outputs = model(inputs)
loss = ...
# Backward pass
loss.backward()
# Update the weights
optimizer.step()
```
In this example, we use the `SGD` optimizer with a learning rate of 0.01 and momentum of 0.9. During training, we zero the gradients using `optimizer.zero_grad()`, compute the forward pass using the model, compute the loss, compute the backward pass using `loss.backward()`, and update the weights using `optimizer.step()`. The momentum term helps to accelerate the optimization process by adding a fraction of the previous update vector to the current update vector.
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