idiap / attention-sampling

This Python package enables the training and inference of deep learning models for very large data, such as megapixel images, using attention-sampling
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Suggestion of Environment (OS, package version, etc.) #16

Open discrim opened 3 years ago

discrim commented 3 years ago

Hi,

I just posted an issue, but I think I can use another one parallelly.

Can you suggest the simplest working environment for this library?
For the OS, I can use:

Please specify the versions of packages such as:

Thanks in advance.

angeloskath commented 3 years ago

Hi,

I have never tested the library with Windows so with respect to that, your mileage may vary.

A working environment would be the following (as reported from conda list).

# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                        main  
_tflow_select             2.1.0                       gpu  
absl-py                   0.10.0                   py36_0  
astor                     0.8.1                    py36_0  
attention-sampling        0.2                      pypi_0    pypi
blas                      1.0                         mkl  
c-ares                    1.15.0            h7b6447c_1001  
ca-certificates           2020.7.22                     0  
certifi                   2020.6.20                py36_0  
cudatoolkit               10.0.130                      0  
cudnn                     7.6.5                cuda10.0_0  
cupti                     10.0.130                      0  
gast                      0.4.0                      py_0  
grpcio                    1.31.0           py36hf8bcb03_0  
h5py                      2.10.0           py36hd6299e0_1  
hdf5                      1.10.6               hb1b8bf9_0  
importlib-metadata        1.7.0                    py36_0  
intel-openmp              2020.2                      254  
keras                     2.2.0                    pypi_0    pypi
keras-applications        1.0.2                    pypi_0    pypi
keras-preprocessing       1.0.1                    pypi_0    pypi
ld_impl_linux-64          2.33.1               h53a641e_7  
libedit                   3.1.20191231         h14c3975_1  
libffi                    3.3                  he6710b0_2  
libgcc-ng                 9.1.0                hdf63c60_0  
libgfortran-ng            7.3.0                hdf63c60_0  
libprotobuf               3.12.4               hd408876_0  
libstdcxx-ng              9.1.0                hdf63c60_0  
markdown                  3.2.2                    py36_0  
mkl                       2020.2                      256  
mkl-service               2.3.0            py36he904b0f_0  
mkl_fft                   1.1.0            py36h23d657b_0  
mkl_random                1.1.1            py36h0573a6f_0  
mock                      4.0.2                      py_0  
ncurses                   6.2                  he6710b0_1  
numpy                     1.19.1           py36hbc911f0_0  
numpy-base                1.19.1           py36hfa32c7d_0  
opencv-python             4.4.0.42                 pypi_0    pypi
openssl                   1.1.1g               h7b6447c_0  
pip                       20.2.2                   py36_0  
protobuf                  3.12.4           py36he6710b0_0  
pydot                     1.4.1                    pypi_0    pypi
pyparsing                 2.4.7                    pypi_0    pypi
python                    3.6.12               hcff3b4d_2  
pyyaml                    5.3.1                    pypi_0    pypi
readline                  8.0                  h7b6447c_0  
scipy                     1.5.2            py36h0b6359f_0  
setuptools                49.6.0                   py36_0  
six                       1.15.0                     py_0  
sqlite                    3.33.0               h62c20be_0  
tensorboard               1.13.1           py36hf484d3e_0  
tensorflow                1.13.1          gpu_py36h3991807_0  
tensorflow-base           1.13.1          gpu_py36h8d69cac_0  
tensorflow-estimator      1.13.0                     py_0  
tensorflow-gpu            1.13.1               h0d30ee6_0  
termcolor                 1.1.0                    py36_1  
tk                        8.6.10               hbc83047_0  
werkzeug                  1.0.1                      py_0  
wheel                     0.35.1                     py_0  
xz                        5.2.5                h7b6447c_0  
zipp                      3.1.0                      py_0  
zlib                      1.2.11               h7b6447c_3  

Most of these will be installed as dependencies so I would focus on tensorflow=1.13.1 and keras=2.2.0.

The g++ version that I am using is 8.3.0 . You can read more about installing the library in the docs.

Cheers, Angelos