提交 c44035b7 编写于 作者: Z zylyyyyyy

Fri Jan 24 13:42:00 CST 2025 inscode

上级 0a575cc3
run = "pip install -r requirements.txt;python main.py"
language = "python"
[packager]
AUTO_PIP = true
[env]
VIRTUAL_ENV = "/root/${PROJECT_DIR}/venv"
PATH = "${VIRTUAL_ENV}/bin:${PATH}"
PYTHONPATH = "$PYTHONHOME/lib/python3.10:${VIRTUAL_ENV}/lib/python3.10/site-packages"
REPLIT_POETRY_PYPI_REPOSITORY = "http://mirrors.csdn.net.cn/repository/csdn-pypi-mirrors/simple"
MPLBACKEND = "TkAgg"
POETRY_CACHE_DIR = "/root/${PROJECT_DIR}/.cache/pypoetry"
[debugger]
program = "main.py"
{ pkgs }: {
deps = [
pkgs.python310Packages.pip
pkgs.python310Full
];
}
\ No newline at end of file
print('欢迎来到 InsCode')
\ No newline at end of file
# CRISP: Curriculum based Sequential neural decoders for Polar code family
This repository contains code used to run experiments in the above paper.
## For running the CRISP model
The bash files `run_crisp.sh` trains using the best curricula and GRUs. By default we use the hyperparameters that gave us decent performance for a reasonable training time. They may be changed inside the file.
## For running alternate models
The bash files `run_alt.sh` trains using the best curricula and CNNs. Other models can be trained by changing the `--model` option (can choose between `conv`(CNNs), `gpt`(GPT), `encoder`(BERT)). By default we use the hyperparameters that gave us decent performance for a reasonable training time. They may be changed inside the file. The curriculum can be changed with `--curriculum` option (choose between `l2r`, `r2l`, `c2n` and `n2c`).
## Python requirements
The required Python packages can be installed by using:
```
pip install -r requirements.txt
```
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#
# This file is autogenerated by pip-compile
# To update, run:
#
# pip-compile requirements.in
#
argparse==1.4.0
# via -r requirements.in
cycler==0.11.0
# via matplotlib
fonttools==4.34.4
# via matplotlib
kiwisolver==1.4.4
# via matplotlib
matplotlib==3.5.2
# via -r requirements.in
numpy==1.21.6
# via
# -r requirements.in
# matplotlib
packaging==21.3
# via matplotlib
pillow==9.2.0
# via matplotlib
pyparsing==3.0.9
# via
# matplotlib
# packaging
python-dateutil==2.8.2
# via matplotlib
six==1.16.0
# via python-dateutil
torch==1.12.0
# via -r requirements.in
tqdm==4.64.0
# via -r requirements.in
typing-extensions==4.3.0
# via
# kiwisolver
# torch
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