It is hard to see what you are trying to do with so little code and an error with no stack trace.
Could you post a little more of your code?
At a guess, you need something like this…
self.conv1_1 = nn.Conv1d(1, 150, 5, padding=something_complicated)

The arguments being, in order, 1 feature input per timestep, 150 features generated, …
and you would feed it data of shape (batch_size, features, timesteps), in your case (1, 1, 64).
The padding is complicated because you need the right amount of padding on one side in order to ensure that the output at time t does not see any input from time t+1.
I wrote a subclass of Conv1d that calculates the necessary padding and reshapes the input. You might find it helpful. https://github.com/jpeg729/pytorch_bits/blob/master/nn/causal.py 190