Hi, I have an input of shape `14 x 10 x 128 x 128`

, where `14`

is `batch_size`

, `10`

is the `sequence_length`

and each item in the sequence is of shape `128 x 128`

. I want to learn to map this input to output of shape `14 x 10 x 128`

, i.e., for each item in the sequence I want to learn 128-binary classifiers.

Does the following model make sense? So, first I reshape my input to `140 x 128 x 128`

and then pass it through the model and reshape the output back to `14 x 10 x 128`

.

```
classifier = nn.Sequential(
nn.Conv1d(128, 128, 1),
nn.ReLU(),
nn.BatchNorm1d(128),
nn.Conv1d(128, 128, 1),
nn.ReLU(),
nn.BatchNorm1d(128),
nn.Conv1d(128, 1, 1)
)
```

Thank you.