Iterating in a sample from a batch


I am new to nlp and pytorch.

I understand (I think) how to build ‘forward’ method, but if I want to iterate over each item in a batch inside forward, how do I incorporated that?


You could just iterate the input x:

class MyModel(nn.Module):
    def __init__(self):
        super(MyModel, self).__init__()
        self.fc1 = nn.Linear(20, 10)
        self.fc2 = nn.Linear(10, 2)
    def forward(self, x):
        for x_ in x:
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        return x

model = MyModel()
x = torch.randn(2, 20)
output = model(x)

What is your use case? Since the batch size is usually varying, you shouldn’t assume to get a specific batch size.
The most common approach is to write code that works with different batch sizes.

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