Python Basic_Decoder Exemples

Exemple #1

Fichier : qr_mainnew.py Projet : Saket-mangalam/Comm-GAN

    pass
else:
    try:
        pretrained_model = torch.load('./Encoders/' + args.model_id + '.pt')
        try:
            netE.load_state_dict(pretrained_model.state_dict())
        except:
            netE.load_state_dict(pretrained_model)
    except:
        print('Encoder weight not match, random init')

# Print the model
print(netE)

# Create the decoder
netDec = Decoder(args).to(device)

# Handle multi-gpu if desired
if (device.type == 'cuda') and (args.ngpu > 1):
    netDec = nn.DataParallel(netDec, list(range(args.ngpu)))

# Apply the weights_init function to randomly initialize all weights
#  to mean=0, stdev=0.2.
if args.model_id is 'default':
    netDec.apply(weights_init)
    pass
else:
    try:
        pretrained_model = torch.load('./Decoders/' + args.model_id + '.pt')
        try:
            netDec.load_state_dict(pretrained_model.state_dict())

Exemple #2

Fichier : test.py Projet : Saket-mangalam/Comm-GAN

    pass
else:
    try:
        pretrained_model = torch.load('./Encoders/' + args.model_id + '.pt')
        try:
            netE.load_state_dict(pretrained_model.state_dict())
        except:
            netE.load_state_dict(pretrained_model)
    except:
        print('Encoder weight not match, random init')

# Print the model
print(netE)

# Create the decoder
netDec = Decoder(args).to(device)

# Handle multi-gpu if desired
if (device.type == 'cuda') and (args.ngpu > 1):
    netDec = nn.DataParallel(netDec, list(range(args.ngpu)))

# Apply the weights_init function to randomly initialize all weights
#  to mean=0, stdev=0.2.
if args.model_id is 'default':
    netDec.apply(weights_init)
    pass
else:
    try:
        pretrained_model = torch.load('./Decoders/' + args.model_id + '.pt')
        try:
            netDec.load_state_dict(pretrained_model.state_dict())