Your Keras model probably uses NHWC ordering for the convolutions. PyTorch uses NCHW for convolutions.
This means your input should be transposed. Also, it looks like you’re doing a 1-d convolution so you probably want to change the kernel size to: (8, 1).
a = torch.randn(32, 1, 720, 1)
torch.nn.Conv2d(1, 128, kernel_size=(8,1), stride=1)(a)

Here N=32, C=1, H=720, W=1. In the output C will be 128. N is batch. C is channels. H and W are the spatial dimensions of the inputs.