I’m writing a FFNN and have a problem with my one-hot encoded data.
The network should work with 28000 records of 1000 characters long strings encoded to 21 one-hot categories. The problem is that i want my model to be working on a tensor of size 1000x21, not on a one of a size 21000.
self.fc1 = nn.Linear(input_size, hidden_size) self.fc2 = nn.Linear(hidden_size, hidden_size) self.fc3 = nn.Linear(hidden_size, output_size)
I want to utilize the above architecture with an input size of 1000x21.
I’m working with data loader, this is what i do to work with batches of data:
x = x.view(x.size(0), -1) x = self.fc1(x)