Should i flatten before the Linear layer

nlp
1

import torch.nn as nn
self.convs = nn.ModuleList([
nn.Conv2d(in_channels = 1,
out_channels = n_filters,
kernel_size = (fs, embedding_dim))
for fs in filter_sizes
])

2

Yes, you should have something of the shape (batch_size, linear_in), and after the linear layer you will have something of the shape (batch_size, linear_out), where your linear layer should be declared like nn.Linear(linear_in, linear_out).

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