Hi there,
I get different results from Conv1d when using sub-length of data.
A simple example:
conv = torch.nn.Conv1d(40, 30, 3, stride=1, padding=1, dilation=1)
test_data = torch.randn((1, 40, 705), dtype=torch.float32)

I expect to get the same results passing all data vs. sub-length of data (of course, only for the sub-length results).
But when I compute the following results
r1 = conv(test_data)
r2 = conv(test_data[:,:,:405])
r3 = conv(test_data[:,:,:603])

they differ - I only compare a sub-length of 30 for the results:
(r1[:,:,:30] == r2[:,:,:30]).all()
>>> tensor(False)
(r1[:,:,:30] == r3[:,:,:30]).all()
>>> tensor(True)

What am I missing? I expect all results to be the same, but they differ for a sub-length of 405, but not for a larger sub-length of 603.