opt.load_size = 80
opt.crop_size = 64
opt.size = 64
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")
opt.n_downsample = 2 # Downsample times
opt.n_blocks = 2 # Numebr of residual blocks
opt.first_kernel = 5 # The filter size of the first convolutional layer in encoder
# Set the input dataset
opt.dataset_mode = 'CIFAR10' # Current dataset: CIFAR10, CelebA
# Set up the training procedure
opt.batchSize = 64 # batch size
opt.n_epochs = 80 # # of epochs without lr decay
opt.n_epochs_decay = 80 # # of epochs with lr decay
opt.lr = 5e-4 # Initial learning rate
opt.lr_policy = 'linear' # decay policy. Availability: see options/train_options.py
opt.beta1 = 0.5 # parameter for ADAM
opt.beta = 1
opt.K = 16
opt.is_Feat = False # Whether to use feature matching loss or not
opt.lambda_feat = 1
##############################################################################################################
if opt.gan_mode == 'wgangp':
opt.norm_D = 'instance' # Use instance normalization when using WGAN. Available: 'instance', 'batch', 'none'
else:
opt.norm_D = 'batch' # Used batch normalization otherwise
opt.activation = 'sigmoid' # The output activation function at the last layer in the decoder
opt.norm_EG = 'batch'
if opt.dataset_mode == 'CIFAR10':
