My mistake. I misunderstood what you were asking. I’ve tried some code below and got these results.
simulated_batch_size = 64
X = torch.rand((simulated_batch_size, 2, 200, 100), dtype=torch.float64)

x1 = X[:, 0, :, :]
print(x1.shape)  # [64, 200, 100]
x2 = X[:, 1, :, :]
print(x2.shape)  # [64, 200, 100]

#### Reshaped for Conv ####
x1 = x1.view(x1.shape[0], 1, 200, 100)
print(x1.shape) # [64, 1, 200, 100]
x2 = x2.view(x2.shape[0], 1, 200, 100)
print(x2.shape) # [64, 1, 200, 100]

So I believe in your case, it would be
x1= x.data[:, 0, :, :]

It should give you a tensor of shape [1, 200, 100]