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Thank you for the easy-to-follow code, but I have some questions about the differences between "Teacher Forcing" vs "Diffusion Forcing" at inference (denosing) time.
After I investigated and prin…
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have you tried teacher forcing rate set to 1.0 during training cotatron ?
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firstly,thanks for your code,it's really helpful to me,but could i know where is the teacher forcing part,thanks again^_^
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I trained the model on small corpus (3 hr, collected by myself) and I expected that the model is going to be overfitted however it's not happened. The loss value closes to 0.2 however the generate spe…
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Something I've been thinking about with expansion of library: a decent amount of the work we've been using involves application of inductive biases and teacher-prompted training to model architecture.…
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You mentioned in Readme about teacher forcing in your implementation. But I am unable to see it. Please explain more about it, if it has been implemented.
Thanks!
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Hi,
I don't understand why the teacher forcing is being done per the whole sequence. The definition of the teacher forcing claims that at each timestep, a predicted or the ground truth token should…
ghost updated
3 years ago
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I try to run test.py/seq2seq with teacher forcing on tensorflow backend:
```
if __name__ == '__main__':
x = np.random.random((samples, input_length, input_dim))
y = np.random.random((sam…
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This is where, with some random chance, we give the RNN like ConvLSTM the ground truth label when its generating sequences in training. This can help with convergenc especially in the beginning, since…
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It's mentioned in Readme that your model is trained during 10 epochs and still have good result on validation. It's not a surprise as you use full Teacher Forcing. The issue is that if you try inferen…