Comments (2)
The command in my test is:
python synthesize.py --model_name wavenet_gaussian --num_blocks 4 --num_layers 6 --load_step 33902
I change the synthesize.py to only handle one file, by hackinging test_dataset to only include one file. The log is as below, where the 196864 is num_samples of wave.
196800/196864
7222.449482679367 seconds
So, the speed is about 196864/7222 = 27 samples per second.
I know the teacher synthesis is slow, but the speed is about 180 samples per second when I test teacher synthesis in the same machine with another wavenet implementation (https://github.com/azraelkuan/parallel_wavenet_vocoder).
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Can anybody help to give clue about this speed issue about teacher synthesis? It's really bothering me to take so long time when evaluating.....Thank you very much.
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Related Issues (9)
- High frequency in the Gaussian IAF? HOT 6
- The network crashes with the error "TypeError: 'generator' object does not support item assignment"
- Can you post any samples of outputs from this implementation please?
- Student predicts nans
- Do the synthesize inputs must be the .npy file HOT 2
- Why is teacher model used when inference? HOT 1
- KL loss becomes nan
- Is pretrained model availible?
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