Comments (1)
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
from attention-sampling.
Related Issues (20)
- RuntimeError: Couldn't compile and install ats.ops.extract_patches.libpatches HOT 4
- file not found HOT 2
- Allow use of a patch generator HOT 5
- Offsets for extracting patches HOT 4
- Why using random sampling during inference and not pick instead the X patches with maximum attention? HOT 1
- C++ versions less than C++11 are not supported
- Implementation of eq. 12 HOT 2
- Validation Accuracy Does not Change HOT 1
- MNIST noise overlaps signal
- expected_with_replacement
- Installation document no longer available
- Segmentation fault (core dumped) HOT 2
- What's the softmax temperature? HOT 1
- pip install runtime error: Couldn't compile and install ats.ops.extract_patches.libpatches HOT 4
- Unable to install on Macbook pro HOT 4
- It's not learning HOT 2
- Extracting weird patches HOT 6
- Batch size for all the experiments in the papaer HOT 2
- What is the role of "receptive field"? HOT 2
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from attention-sampling.