To install this project, only Jittor needs to be installed. The Jittor framework has the following requirements for the environment:
Operating System: Ubuntu >= 16.04 or Windows Subsystem of Linux (WSL)
Python: version >= 3.7
C++ compiler (at least one of the following is required):
g++ (>= 5.4.0)
clang (>= 8.0)
GPU compiler (optional): nvcc >=10.0
GPU acceleration library (optional): cudnn-dev (cudnn development version, installation with tar is recommended, please refer to the link for instructions)
If you do not wish to manually configure the environment, we recommend using Docker for installation. In addition, you can also use pip for installation.
Note: Currently, Jittor runs on Windows operating systems via WSL, and the installation method for WSL can be found on the official Microsoft website. The current version of WSL does not support CUDA.
Install with Docker
# linux CPU only
docker run -it --network host jittor/jittor
# linux CPU and CUDA
docker run -it --network host --gpus all jittor/jittor-cuda
# mac/windows
docker run -it -p 8888:8888 jittor/jittor
For detailed instructions on installing via Docker, please refer to the “Install via Docker” section in the “Jittor Installation Guide” for Windows, Mac, and Linux on the Jittor website.
Install with Pip
If you are not ready with the environment or are not using the Ubuntu operating system, we recommend installing via Docker. If you have already installed the compiler and the corresponding version of Python, we strongly recommend using the Pip installation method. (If Github cannot be accessed, you can download from the Jittor homepage):
Congratulations on completing the installation if the test run is successful.
Jittor will automatically search for suitable compilers in the path. If you wish to manually specify the compiler, please use the environment variables cc_path and nvcc_path (optional).
How to use this project
Download the project.
Navigate to the root directory.
Run the program.
python3 CGAN.py
License
MIT License
Copyright (c) [year] [fullname]
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
关于
A Jittor implementation of Conditional GAN (CGAN).
abaaba_CGAN_jittor
How to install this project
To install this project, only Jittor needs to be installed. The Jittor framework has the following requirements for the environment:
Operating System: Ubuntu >= 16.04 or Windows Subsystem of Linux (WSL) Python: version >= 3.7 C++ compiler (at least one of the following is required): g++ (>= 5.4.0) clang (>= 8.0) GPU compiler (optional): nvcc >=10.0 GPU acceleration library (optional): cudnn-dev (cudnn development version, installation with tar is recommended, please refer to the link for instructions)
If you do not wish to manually configure the environment, we recommend using Docker for installation. In addition, you can also use pip for installation.
Note: Currently, Jittor runs on Windows operating systems via WSL, and the installation method for WSL can be found on the official Microsoft website. The current version of WSL does not support CUDA.
Install with Docker
For detailed instructions on installing via Docker, please refer to the “Install via Docker” section in the “Jittor Installation Guide” for Windows, Mac, and Linux on the Jittor website.
Install with Pip
If you are not ready with the environment or are not using the Ubuntu operating system, we recommend installing via Docker. If you have already installed the compiler and the corresponding version of Python, we strongly recommend using the Pip installation method. (If Github cannot be accessed, you can download from the Jittor homepage):
Congratulations on completing the installation if the test run is successful. Jittor will automatically search for suitable compilers in the path. If you wish to manually specify the compiler, please use the environment variables cc_path and nvcc_path (optional).
How to use this project
License
MIT License
Copyright (c) [year] [fullname]
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.