Comments (12)
Make sure that you're using Theano 0.9.0 (python -c 'import theano; print(theano.__version__)'
should print 0.9.0.something
).
Make sure you've followed all of the Theano installation instructions. Specifically, if you're using a GPU, that means running conda install pygpu
or installing cuDNN (although I think cuDNN support is getting phased out). If using a CPU, that means running conda install mkl-service
.
I think this issue on the Keras tracker (and maybe this one) should help.
from acapellabot.
Thanks, I solved this problem by add 'optimizer = None ' in .theanorc. But I come to a new problem. I don't know if it is because I use theano 0.8.2. In line 24 of conversion.py, newX is float and can not be as index. so I use int(newX), but the it comes to
" newSpectrogram[:spectrogram.shape[0], :spectrogram.shape[1]] = spectrogram
ValueError: could not broadcast input array from shape (769,21859) into shape (768,21856) "
That is the size is not right, so I change it to
" newSpectrogram[:newX, :newY] = spectrogram[:newX, :newY] "
and it seems to work, but I run few hours and it is still running and gets nothing. Is that reasonable?
from acapellabot.
Hmm. It should be able to do the isolation process in ~30s or so, at least on a GPU. Are you using python 3? I've only tested on python 3.
If you're determined to make it work on py2, first make sure that the spectrograms that expandToGrid
is returning are padded to multiples of gridSize
. The point of that method is to pad the spectrograms to a nice size so that the network can handle them (they get cropped after getting output). If that works, then everything else should work.
It's not clear to me how things could run for hours unless you're training–could you show the output for the case where it hangs?
from acapellabot.
sorry, I used python 2. I will try this again with python 3.
from acapellabot.
from acapellabot.
You can configure the file parsing code however you want for your dataset by messing with the functions at the top of data.py
. Some examples of valid filenames for the format I'm using are:
5 Lana Del Rey - Young & Beautiful [Acapella].mp3
5 Dubvision - Triton.mp3
11 Borgeous - Invincible [Acapella].mp3
11 Carta - Shanghai.mp3
The number at the start is the camelot key (without the A/B).
Files are mashed up (combined to form a set of training examples) if they start with the same number, and only mashed up if one is an acapella and the other is not. So the data that would be generated is:
x : (Lana Del Rey - Young & Beautiful [Acapella]) + (Dubvision - Triton) -> y: (Lana Del Rey - Young & Beautiful [Acapella])
x : (Borgeous - Invincible [Acapella]) + (Carta - Shanghai) -> y: (Borgeous - Invincible [Acapella])
Where (x, y)
are sets of input, output pairs for the model.
The reason the data is generated this way is that it allows me to make a lot of data with fewer examples, while still keeping the training data realistic (i.e. the vocals are always in the same key as the song).
To get key information you can use KeyFinder or other software tools. I haven't tested performance with/without key matching though; it's possible that you could just give everything the same key and still get good results. I hope that helps!
from acapellabot.
from acapellabot.
I am also having this error
AssertionError: AbstractConv2d Theano optimization failed: there is no implementation available supporting the requested options. Did you exclude both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, is cuDNN available and does the GPU support it? If on CPU, do you have a BLAS library installed Theano can link against?
I am working with keras 1.0 and theano 0.8.0 in windows
According to #ghoshaw I cannot locate the file .theanorc to set optimizer =None as by ghoshaw,
Any one can help me, Thanks
from acapellabot.
@ghoshaw, could you help find the .theanorc file? Thanks!
from acapellabot.
@ghoshaw it will be your great favor if you can help us to locate .theanorc file, thanks
from acapellabot.
@alchemz , Sorry, I do not know where the .theanorc file is, but you can try to create one in ~/.theano if you can not find it.
from acapellabot.
According to some it's in "C:\Users\USERNAME.theanorc.txt".
Mine wasn't there and I still haven't fixed my problem but hopefully this will help someone.
from acapellabot.
Related Issues (13)
- Indexing elements must be in increasing order HOT 7
- python data.py . gives IndexError: too many indices for array HOT 4
- ValueError: all the input array dimensions except for the concatenation axis must match exactly
- how to extract only the music part?
- Acapellabot not responsing
- TypeError: Indexing elements must be in increasing order
- how to train this model by myself? HOT 4
- Fitting step runs out of memory on GPU's HOT 1
- CorrMM issue HOT 4
- network construction question HOT 4
- TypeError: 'float' object cannot be interpreted as an index HOT 3
- ERROR (theano.gof.opt)
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from acapellabot.