Hello all,

I am building a model that needs to perform the mathematical operation of convolution between the batches of 1D input `c`

and a parameter, call it `E`

.

Thus, I want something similar to`np.convolve(E,c)`

but in native pytorch . Am I taking i correctly, that Conv1D is not the right tool for the job? The documentation states it uses the valid cross-correlation operator insead of a convolution operator.

I found the following (at least) working solution to give reasonable yet wrong results:

```
conv = torch.nn.Conv1d(
1, #number of batches
1, #number of features (just 1)
40, #length of the 1D kernel (E)
bias=False,
padding=n_kernel - 1 #make it a "full" convolution or correlation, I guess
)
sol = conv(c[None, :])
```

Am I overlooking something and if so, how can I recreate the expected (numpy) behavior? And also, on a less serious note,why is it not called Cor1D then?

Thanks so much for your help!