dataset = create_dataset(opt) # create a dataset given opt.dataset_mode and other options
dataset_size = len(dataset)
print('#training images = %d' % dataset_size)
else:
raise Exception('Not implemented yet')
######################################## OFDM setting ###########################################
size_after_compress = (opt.size // (2**opt.n_downsample))**2 * (opt.C_channel // 2)
opt.N = opt.batchSize # Batch size
opt.P = 1 # Number of symbols
opt.M = 64 # Number of subcarriers per symbol
opt.K = 16 # Length of CP
opt.L = 8 # Number of paths
opt.decay = 4
opt.S = size_after_compress // opt.M # Number of packets
opt.is_cfo = False
opt.is_trick = True
opt.is_cfo_random = False
opt.max_ang = 1.7
opt.ang = 1.7
if opt.CE not in ['LS', 'MMSE', 'TRUE', 'IMPLICIT']:
raise Exception("Channel estimation method not implemented")
if opt.EQ not in ['ZF', 'MMSE', 'IMPLICIT']:
raise Exception("Equalization method not implemented")
if opt.feedforward not in ['IMPLICIT', 'EXPLICIT-CE', 'EXPLICIT-CE-EQ', 'EXPLICIT-RES']:
raise Exception("Forward method not implemented")
