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As README.md says,
> "all the offset data has been normalized to have a standard deviation of 1.0 on the training set, after simplifying the strokes. ...Thus each dataclass has its own scale_facto…
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I get high accuracy score on this way :
isCorrect = tf.equal(tf.argmax(predict_Y, 1), tf.argmax(Y_holder, 1))
accuracy = tf.reduce_mean(tf.cast(isCorrect, tf.float32))
your code:
accuracy = tf.met…
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The current melody model uses time-based encoder/decoders; each RNN step is one 16th note by default. We should also try note-based encoder/decoders, where each RNN step is an event of the form "play…
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This is interesting, I tried to build it and done it with some hassle (using import soundfile, some type conversions), then injected a new file into training_data\raw_audio\vocal_tracks as survive_4_v…
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encoder_cell = rnn_cell.EmbeddingWrapper(
en_cell, embedding_classes=num_encoder_symbols,
embedding_size=embedding_size)
不能用成
encoder_cell = my_rnn_cell.Embedding…
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- naive RNN
![image](https://user-images.githubusercontent.com/18360240/61843402-0c0a2c00-aece-11e9-8ca1-a83535b064f7.png)
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I'm getting this error when trying to train given the instructions in the README
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Excuse me,I encountered the bug.Can you run the code using the command"python3 train_rl.py train cifar10_rnn_gate_rl_38 --resume resnet-38-rnn-sp-cifar10.pth.tar -d cifar10 --gate-type rnn
" normally…
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MWDT version: R-2021.03
COMMIT: bbbdd0e34abc3e997db4944ca2fb80086664b02a
`gmake ROUND_MODE=CONVERGENT TCF_FILE=../../hw/em9d.tcf`
```
cmake --build /SCRATCH2/Watson/mliproject/embarc_mli/obj/a…
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```
Loading model parameters.
/usr/local/lib/python3.7/dist-packages/torchtext/data/field.py:197: UserWarning: volatile was removed and now has no effect. Use `with torch.no_grad():` instead.
ret…