Number of devices: 1 initialize network with normal type
时间: 2024-03-23 07:42:43 浏览: 29
Sure, I can help you with that. To initialize a neural network with normal type in Python, you can use the following code snippet:
```python
import torch.nn as nn
# Define your network architecture
class MyNetwork(nn.Module):
def __init__(self):
super(MyNetwork, self).__init__()
self.layer1 = nn.Linear(10, 20)
self.layer2 = nn.Linear(20, 1)
def forward(self, x):
x = self.layer1(x)
x = nn.functional.relu(x)
x = self.layer2(x)
return x
# Initialize the network with normal type
my_network = MyNetwork()
for name, parameter in my_network.named_parameters():
if 'weight' in name:
nn.init.normal_(parameter)
```
In the code above, we first define our neural network architecture using the `nn.Module` class. We then define the `forward` method which specifies the forward pass of our network. Finally, we initialize the network with normal type using the `nn.init.normal_` method. This method initializes the weights of the network with values drawn from a normal distribution with mean 0 and standard deviation 1.
I hope this helps! Let me know if you have any further questions.
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