Nn.dropout

Batchnorm1d pytorch

class network(nn.Module):
    def __init__(self):
        super(network, self).__init__()
        self.linear1 = nn.Linear(in_features=40, out_features=320)
        self.bn1 = nn.BatchNorm1d(num_features=320)
        self.linear2 = nn.Linear(in_features=320, out_features=2)

    def forward(self, input):  # Input is a 1D tensor
        y = F.relu(self.bn1(self.linear1(input)))
        y = F.softmax(self.linear2(y), dim=1)
        return y
    
model = network()
x = torch.randn(10, 40)
output = model(x)

Source: discuss.pytorch.org

Nn.dropout

>>> m = nn.Dropout(p=0.2)
>>> input = torch.randn(20, 16)
>>> output = m(input)

Source: pytorch.org

Similar codes

0 vote167 views1 answer
Legend text color matplotlib
Python
0 vote200 views2 answers
Javascript parse url
Python
0 vote183 views1 answer
Python declare variable type array
Python
9 votes153 views2 answers
TypeError: 'method' object is not subscriptable
Python
0 vote166 views3 answers
How to install idle on ubuntu 20.04
Python
0 vote172 views1 answer
Rqg3
Python
0 vote167 views1 answer
Standard streams with python3
Python
0 vote156 views1 answer
Raymenschechorne
Python
0 vote227 views1 answer
Module level import not at top of file
Python
1 vote166 views2 answers
1d array to one hot
Python