Hi,

I am new to PyTorch. I have a doubt about converting a data frame with 6 columns and 50,000 rows. I want to form 6 channels with these 6 columns and 100 rows such that it can be given as input to a CNN that takes input with 6 channels. Could any of you please help me to sort this out?

I assume you would want your data sample to be of the shape - `[batch, 6, 100]`

So Initialize a NumPy array of that shape

`data = numpy.zeros((1, 6, 100)) #batch size equal to 1`

and then populate this NumPy array the way you want.

Then convert this Numpy array to a torch tensor using -

`torch_tensor = torch.from_numpy(data)`

if you want to batch it, you could stack these tensors on top of each other at the `0th`

dimension making the input of shape `batch_size, 6, 100`