AnhP

/

DJCM-Test

like 4

• "__main__.ResDecoderBlock",
• "__builtin__.set",
• "torch.nn.modules.activation.PReLU",
• "numpy.core.multiarray._reconstruct",
• "torch.nn.modules.conv.ConvTranspose2d",
• "torch._utils._rebuild_tensor_v2",
• "__main__.Encoder",
• "torch.FloatStorage",
• "torch.nn.modules.conv.Conv2d",
• "__main__.DJCM",
• "__main__.STFT",
• "__main__.PE_Decoder",
• "torch.nn.modules.rnn.GRU",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "__main__.ResEncoderBlock",
• "torch.nn.modules.container.ModuleList",
• "collections.OrderedDict",
• "torch._utils._rebuild_parameter",
• "torch.nn.parallel.data_parallel.DataParallel",
• "__main__.BiGRU",
• "torch.nn.modules.conv.Conv1d",
• "__main__.LatentBlocks",
• "torch.nn.modules.container.Sequential",
• "numpy.ndarray",
• "__main__.Decoder",
• "torch.LongStorage",
• "einops.layers.torch.Rearrange",
• "numpy.dtype",
• "_codecs.encode",
• "torch.device",
• "torch.nn.modules.activation.Sigmoid",
• "__main__.ResConvBlock",
• "torch.nn.modules.linear.Linear",
• "__main__.Spectrogram",
• "torch.nn.modules.pooling.MaxPool2d"

How to fix it?