I might have come up with a solution, but i am not sure whether the sequence order would be intact:
 # Long sequenced data
a = torch.randn((32, 1024, 3 , 28, 28)) 

# Get the original shape and modify it
b = [i for i in a.size()]  
b[0] = -1
b[1] = int(b[1] / 4) 

# Desired length sequences
c = a.view(b) 

>>>c.shape
torch.Size([128, 256, 3, 28, 28])