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':