Ecosyste.ms: Repos

An open API service providing repository metadata for many open source software ecosystems.

GitHub / fangvv / MTACP

Code for paper "Deep Reinforcement Learning based Multi-task Automated Channel Pruning for DNNs"

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/fangvv%2FMTACP

Stars: 1
Forks: 0
Open Issues: 0

License: None
Language: Python
Repo Size: 1020 KB
Dependencies: 106

Created: 11 months ago
Updated: 10 months ago
Last pushed: 9 months ago
Last synced: 9 months ago

Topics: deep-learning, deep-reinforcement-learning, distributed, dnn, ijcnn, impala, inference-acceleration, multi-task, nas, network-architecture-search, neural-networks, prunning, reinforcement-learning-algorithms

Files

Loading...

Readme

Loading...

Dependencies

conda_requirements.txt pypi

blas =1.0=mkl
ca-certificates =2021.7.5=h06a4308_1
certifi =2021.5.30=py37h06a4308_0
cffi =1.14.0=py37h2e261b9_0
freetype =2.10.4=h5ab3b9f_0
intel-openmp =2021.3.0=h06a4308_3350
jpeg =9d=h7f8727e_0
lcms2 =2.12=h3be6417_0
libedit =3.1.20210714=h7f8727e_0
libffi =3.2.1=hf484d3e_1007
libgcc-ng =9.3.0=h5101ec6_17
libgomp =9.3.0=h5101ec6_17
libpng =1.6.37=hbc83047_0
libstdcxx-ng =9.3.0=hd4cf53a_17
libtiff =4.2.0=h85742a9_0
libwebp-base =1.2.0=h27cfd23_0
lz4-c =1.9.3=h295c915_1
mkl =2021.3.0=h06a4308_520
mkl-service =2.4.0=py37h7f8727e_0
mkl_fft =1.3.0=py37h42c9631_2
mkl_random =1.2.2=py37h51133e4_0
ncurses =6.2=he6710b0_1
ninja =1.10.2=hff7bd54_1
olefile =0.46=py37_0
openjpeg =2.4.0=h3ad879b_0
openssl =1.1.1l=h7f8727e_0
pillow =8.3.1=py37h2c7a002_0
pip =21.2.2=py37h06a4308_0
pycparser =2.20=py_2
python =3.7.3=h0371630_0
readline =7.0=h7b6447c_5
setuptools =58.0.4=py37h06a4308_0
six =1.16.0=pyhd3eb1b0_0
sqlite =3.33.0=h62c20be_0
tk =8.6.10=hbc83047_0
wheel =0.37.0=pyhd3eb1b0_1
xz =5.2.5=h7b6447c_0
zlib =1.2.11=h7b6447c_3
zstd =1.4.9=haebb681_0

pip_requirement.txt pypi

joblib ==1.0.1
numpy ==1.21.3
protobuf ==3.18.0
ptflops ==0.6.9
scikit-learn ==0.24.2
scipy ==1.1.0
tensorboardx ==2.4
threadpoolctl ==2.2.0
torch ==1.9.0
torchvision ==0.2.1
typing-extensions ==3.10.0.2

requirements_atari.txt pypi