Comments (5)
The training process does not automatically terminate. In our paper, we terminate after some fixed number of iterations (200k IIRC). You can till the training script whenever the generated examples are to your liking.
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The checkpoints should be saving intermittently to the training directory specified to the training script. You can load the most recent checkpoint for generation. More info in the README, nothing about that in the paper
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Sorry it's taken me a while to respond. The metagraphs from the checkpoint directory don't have the proper named tensors to support the code snippet you sent. Try downloading the inference metagraph from the example notebook and loading that before loading the weights:
!wget https://s3.amazonaws.com/wavegan-v1/models/sc09_infer.meta -O infer.meta
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Related Issues (20)
- Invalid argument: You must feed a value for placeholder tensor 'ngl' with dtype int32 HOT 2
- Can we change (increase) amount of training data in between sessions?
- Last layer of the generator in the CNN (size 16384) HOT 1
- Tensorflow2.4 support HOT 5
- Multi-channel audio doesn't work with --data_num_channels 2 in Jupyter Lab HOT 1
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- OSS License compatibility question
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- int() argument must be a string, a bytes-like object or a real number, not 'Tensor'
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