From 1dee8c014aeda2f392d05fa766f9354cd701368a Mon Sep 17 00:00:00 2001
From: D-X-Y <280835372@qq.com>
Date: Fri, 4 Oct 2019 23:32:19 +1000
Subject: [PATCH] update README
---
README.md | 5 ++++-
exps/search-shape.py | 1 +
scripts/KD-train.sh | 50 -------------------------------------------
scripts/base-train.sh | 14 +++---------
4 files changed, 8 insertions(+), 62 deletions(-)
delete mode 100644 scripts/KD-train.sh
diff --git a/README.md b/README.md
index 1d58efc..7c2f4af 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
# Nueral Architecture Search
-This project contains the following neural architecture search algorithms, implemented in [PyTorch](http://pytorch.org).
+This project contains the following neural architecture search algorithms, implemented in [PyTorch](http://pytorch.org). More NAS resources can be found in [Awesome-NAS](https://github.com/D-X-Y/Awesome-NAS).
- Network Pruning via Transformable Architecture Search, NeurIPS 2019
- One-Shot Neural Architecture Search via Self-Evaluated Template Network, ICCV 2019
@@ -20,6 +20,7 @@ In this paper, we proposed a differentiable searching strategy for transformable
+
### Usage
Use `bash ./scripts/prepare.sh` to prepare data splits for `CIFAR-10`, `CIFARR-100`, and `ILSVRC2012`.
@@ -50,6 +51,7 @@ Highlight: we equip one-shot NAS with an architecture sampler and train network
### Usage
+
Please use the following scripts to train the searched SETN-searched CNN on CIFAR-10, CIFAR-100, and ImageNet.
```
CUDA_VISIBLE_DEVICES=0 bash ./scripts/nas-infer-train.sh cifar10 SETN 96 -1
@@ -81,6 +83,7 @@ Searching codes come soon!
# Citation
+
If you find that this project helps your research, please consider citing some of the following papers:
```
@inproceedings{dong2019tas,
diff --git a/exps/search-shape.py b/exps/search-shape.py
index 1b91589..2a8fc96 100644
--- a/exps/search-shape.py
+++ b/exps/search-shape.py
@@ -10,6 +10,7 @@ from copy import deepcopy
from pathlib import Path
lib_dir = (Path(__file__).parent / '..' / 'lib').resolve()
+print ('lib_dir : {:}'.format(lib_dir))
if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir))
from config_utils import load_config, configure2str, obtain_search_single_args as obtain_args
from procedures import prepare_seed, prepare_logger, save_checkpoint, copy_checkpoint
diff --git a/scripts/KD-train.sh b/scripts/KD-train.sh
deleted file mode 100644
index 56630b6..0000000
--- a/scripts/KD-train.sh
+++ /dev/null
@@ -1,50 +0,0 @@
-#!/bin/bash
-# bash ./scripts/KD-train.sh cifar10 ResNet110 ResNet110 0.5 1 -1
-echo script name: $0
-echo $# arguments
-if [ "$#" -ne 6 ] ;then
- echo "Input illegal number of parameters " $#
- echo "Need 6 parameters for the dataset / the-model-name / the-teacher-path / KD-alpha / KD-temperature / the-random-seed"
- exit 1
-fi
-if [ "$TORCH_HOME" = "" ]; then
- echo "Must set TORCH_HOME envoriment variable for data dir saving"
- exit 1
-else
- echo "TORCH_HOME : $TORCH_HOME"
-fi
-
-dataset=$1
-model=$2
-teacher=$3
-alpha=$4
-temperature=$5
-epoch=E300
-LR=L1
-batch=256
-rseed=$6
-
-save_dir=./output/KD/${dataset}-${teacher}.2.${model}-${alpha}-${temperature}
-rm -rf ${save_dir}
-
-PY_C="./env/bin/python"
-if [ ! -f ${PY_C} ]; then
- echo "Local Run with Python: "`which python`
- PY_C="python"
-else
- echo "Cluster Run with Python: "${PY_C}
-fi
-
-${PY_C} --version
-
-${PY_C} ./exps/KD-main.py --dataset ${dataset} \
- --data_path $TORCH_HOME/cifar.python \
- --model_config ./configs/archs/CIFAR-${model}.config \
- --optim_config ./configs/opts/CIFAR-${epoch}-W5-${LR}-COS.config \
- --KD_checkpoint $TORCH_HOME/TAS-checkpoints/basemodels/${dataset}/${teacher}.pth \
- --procedure Simple-KD \
- --save_dir ${save_dir} \
- --KD_alpha ${alpha} --KD_temperature ${temperature} \
- --cutout_length -1 \
- --batch_size ${batch} --rand_seed ${rseed} --workers 4 \
- --eval_frequency 1 --print_freq 100 --print_freq_eval 200
diff --git a/scripts/base-train.sh b/scripts/base-train.sh
index fcdecc5..521dd02 100644
--- a/scripts/base-train.sh
+++ b/scripts/base-train.sh
@@ -22,21 +22,13 @@ batch=$5
rseed=$6
-PY_C="./env/bin/python"
-if [ ! -f ${PY_C} ]; then
- echo "Local Run with Python: "`which python`
- PY_C="python"
- SAVE_ROOT="./output"
-else
- echo "Cluster Run with Python: "${PY_C}
- SAVE_ROOT="./hadoop-data/SearchCheckpoints"
-fi
+SAVE_ROOT="./output"
save_dir=${SAVE_ROOT}/basic/${dataset}/${model}-${epoch}-${LR}-${batch}
-${PY_C} --version
+python --version
-${PY_C} ./exps/basic-main.py --dataset ${dataset} \
+python ./exps/basic-main.py --dataset ${dataset} \
--data_path $TORCH_HOME/cifar.python \
--model_config ./configs/archs/CIFAR-${model}.config \
--optim_config ./configs/opts/CIFAR-${epoch}-W5-${LR}-COS.config \