brownvc / deep-synth

Greetings to all the developers of deep-synth,

I am experiencing some trouble with commit cc0e991, possibly due to me using newer libraries that it's designed for. I would like to know which

12.01.2021

OS: Ubuntu 18.04
CUDA: 10.1
Python: 3.8.5
pytorch: 1.7.1 (with 0.4 I cannot even run python create_data.py)
scipy: 1.2.0

Having successfully generated the data with create_data.py, we now have several folders in the data directory: bedroom, living, office

Running location_train.py --data-dir bedroom --save-dir res_2_bedroom --train-size 500 --use-count works

Running continue_train.py --data-dir bedroom --save-dir res_1_bedroom --train-size 500 --use-count doesn't

I get the following Error:
RuntimeError: Expected object of scalar type Long but got scalar type Bool for argument #2 'target' in call to _thnn_nll_loss_forward

looking forward to hearing from you,
KR

probably a version issue - just update the binary target to Long

I have very limited knowledge of pytorch. Could you extrapolate?
Thanks & KR

deep-synth/deep-synth/continue_dataset.py

Line 67 in b800e11

output = not is_complete

change this to long

Alright, I've solved it. (Edit: Also thanks for your reply, I was typing up the response at the time at which you answered)

TLDR:
in continue_train.py, change lines 137 and 179 from
data, target = data.cuda(), target.cuda()
to
data, target = data.cuda(), target.cuda().long()

continue_train.py now runs properly
python continue_train.py --data-dir bedroom --save-dir res_1_bedroom --train-size 500 --use-count

I hadn't understood your answer linguistically, as I had been unaware of the existence of tensors, which may have Boolean type, Double type or Long type. This is something different to the standard c-family datatypes bool, double, int, long etc. If I hear update bool to long, I understand casting

This Project uses a very old version of the pytorch library 0.4.1, which was impossible to use together with CUDA 10.1 which we have installed on our system. Since 2018, the time of release of deep-synth, pytorch developers have changed things about with pytorch and at present, pytorch 1.7.1 expects to receive tensors with the type Long as opposed to Bool, as it's previously been, which we now must cast like so:
target = target.cuda().long()

This helpful link and two pythonists whom I know saved the day

A similar issue for further reading can be found here

whilst on the note of the use of outdated libraries in this commit, which is understandable considering it's from 2018, whoever else may be trying to get this thing afloat in the future, make sure that your SciPy library is 1.2 or older, as there has as well been a breaking change in version 1.3

libraries links

Matplotlib
Numpy
Numba
SciKit-learn
SciPy

Versions of the libraries for commit `cc0e991`

Here are the versions of the libraries contained in requirements.txt, which I currently have installed on my machine and which most definitely work

replace requirements.txt with this (gets you the desired versions)

matplotlib==3.3.3
numpy==1.19.2
numba==0.52.0
pybullet==2.1.3
pyquaternion==0.9.9
scikit-learn==0.24.0
scipy==1.2.0

install by running
pip install -r requirements.txt

check the library versions

And finally, this serves to save you the 20 minutes of googling

install pyTorch like so
conda install pytorch torchvision torchaudio cudatoolkit=10.1 -c pytorch

check pytorch version
python -c "import torch; print(torch.__version__)"
1.7.1

check matplotlib version
python -c "import matplotlib; print(matplotlib.__version__)"
3.3.3

check numpy version
"import numpy; print(numpy.version.version)"
1.19.2

check scipy version
python -c "import scipy; print(scipy.version.version)"
1.2.0

Training continue_data.py gives Runtimerror

libraries links

Versions of the libraries for commit cc0e991

check the library versions

Versions of the libraries for commit `cc0e991`