Move algos to NAS-Bench-201-algos
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@ -224,16 +224,16 @@ If researchers can provide better results with different hyper-parameters, we ar
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**Note that** you need to prepare the training and test data as described in [Preparation and Download](#preparation-and-download)
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- [1] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/DARTS-V1.sh cifar10 1 -1`, where `cifar10` can be replaced with `cifar100` or `ImageNet16-120`.
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- [2] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/DARTS-V2.sh cifar10 1 -1`
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- [3] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/GDAS.sh cifar10 1 -1`
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- [4] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/SETN.sh cifar10 1 -1`
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- [5] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/ENAS.sh cifar10 1 -1`
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- [6] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/RANDOM-NAS.sh cifar10 1 -1`
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- [7] `bash ./scripts-search/algos/R-EA.sh cifar10 3 -1`
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- [8] `bash ./scripts-search/algos/Random.sh cifar10 -1`
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- [9] `bash ./scripts-search/algos/REINFORCE.sh cifar10 0.5 -1`
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- [10] `bash ./scripts-search/algos/BOHB.sh cifar10 -1`
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- [1] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NAS-Bench-201-algos/DARTS-V1.sh cifar10 1 -1`, where `cifar10` can be replaced with `cifar100` or `ImageNet16-120`.
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- [2] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NAS-Bench-201-algos/DARTS-V2.sh cifar10 1 -1`
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- [3] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NAS-Bench-201-algos/GDAS.sh cifar10 1 -1`
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- [4] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NAS-Bench-201-algos/SETN.sh cifar10 1 -1`
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- [5] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NAS-Bench-201-algos/ENAS.sh cifar10 1 -1`
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- [6] `CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NAS-Bench-201-algos/RANDOM-NAS.sh cifar10 1 -1`
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- [7] `bash ./scripts-search/NAS-Bench-201-algos/R-EA.sh cifar10 3 -1`
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- [8] `bash ./scripts-search/NAS-Bench-201-algos/Random.sh cifar10 -1`
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- [9] `bash ./scripts-search/NAS-Bench-201-algos/REINFORCE.sh cifar10 0.5 -1`
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- [10] `bash ./scripts-search/NAS-Bench-201-algos/BOHB.sh cifar10 -1`
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In commands [1-6], the first args `cifar10` indicates the dataset name, the second args `1` indicates the behavior of BN, and the first args `-1` indicates the random seed.
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@ -1,5 +1,5 @@
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#!/bin/bash
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# bash ./scripts-search/algos/BOHB.sh -1
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# bash ./scripts-search/NAS-Bench-201-algos/BOHB.sh -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 2 ] ;then
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@ -25,7 +25,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/BOHB-${dataset}
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OMP_NUM_THREADS=4 python ./exps/algos/BOHB.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/BOHB.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} \
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--search_space_name ${space} \
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@ -1,5 +1,5 @@
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#!/bin/bash
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# bash ./scripts-search/algos/DARTS-V1.sh cifar10 0 -1
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# bash ./scripts-search/NAS-Bench-201-algos/DARTS-V1.sh cifar10 0 -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -32,7 +32,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/DARTS-V1-${dataset}-BN${BN}
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OMP_NUM_THREADS=4 python ./exps/algos/DARTS-V1.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/DARTS-V1.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} --data_path ${data_path} \
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--search_space_name ${space} \
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@ -1,5 +1,5 @@
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#!/bin/bash
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# bash ./scripts-search/algos/DARTS-V2.sh cifar10 0 -1
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# bash ./scripts-search/NAS-Bench-201-algos/DARTS-V2.sh cifar10 0 -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -32,7 +32,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/DARTS-V2-${dataset}-BN${BN}
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OMP_NUM_THREADS=4 python ./exps/algos/DARTS-V2.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/DARTS-V2.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} --data_path ${data_path} \
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--search_space_name ${space} \
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@ -1,6 +1,6 @@
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#!/bin/bash
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# Efficient Neural Architecture Search via Parameter Sharing, ICML 2018
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# bash ./scripts-search/algos/ENAS.sh cifar10 0 -1
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# bash ./scripts-search/NAS-Bench-201-algos/ENAS.sh cifar10 0 -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -33,7 +33,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/ENAS-${dataset}-BN${BN}
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OMP_NUM_THREADS=4 python ./exps/algos/ENAS.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/ENAS.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} --data_path ${data_path} \
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--search_space_name ${space} \
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@ -1,5 +1,5 @@
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#!/bin/bash
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# bash ./scripts-search/algos/GDAS.sh cifar10 0 -1
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# bash ./scripts-search/NAS-Bench-201-algos/GDAS.sh cifar10 0 -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -32,7 +32,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/GDAS-${dataset}-BN${BN}
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OMP_NUM_THREADS=4 python ./exps/algos/GDAS.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/GDAS.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} --data_path ${data_path} \
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--search_space_name ${space} \
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@ -1,6 +1,6 @@
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#!/bin/bash
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# Regularized Evolution for Image Classifier Architecture Search, AAAI 2019
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# bash ./scripts-search/algos/R-EA.sh cifar10 3 -1
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# bash ./scripts-search/NAS-Bench-201-algos/R-EA.sh cifar10 3 -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -28,7 +28,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/R-EA-${dataset}-SS${sample_size}
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OMP_NUM_THREADS=4 python ./exps/algos/R_EA.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/R_EA.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} \
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--search_space_name ${space} \
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@ -1,6 +1,6 @@
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#!/bin/bash
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# Random Search and Reproducibility for Neural Architecture Search, UAI 2019
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# bash ./scripts-search/algos/RANDOM-NAS.sh cifar10 0 -1
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# bash ./scripts-search/NAS-Bench-201-algos/RANDOM-NAS.sh cifar10 0 -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -33,7 +33,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/RANDOM-NAS-${dataset}-BN${BN}
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OMP_NUM_THREADS=4 python ./exps/algos/RANDOM-NAS.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/RANDOM-NAS.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} --data_path ${data_path} \
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--search_space_name ${space} \
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@ -1,5 +1,5 @@
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#!/bin/bash
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# bash ./scripts-search/algos/REINFORCE.sh 0.001 -1
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# bash ./scripts-search/NAS-Bench-201-algos/REINFORCE.sh 0.001 -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -26,7 +26,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/REINFORCE-${dataset}-${LR}
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OMP_NUM_THREADS=4 python ./exps/algos/reinforce.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/reinforce.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} \
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--search_space_name ${space} \
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@ -1,5 +1,5 @@
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#!/bin/bash
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# bash ./scripts-search/algos/Random.sh -1
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# bash ./scripts-search/NAS-Bench-201-algos/Random.sh -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 2 ] ;then
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@ -25,7 +25,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/RAND-${dataset}
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OMP_NUM_THREADS=4 python ./exps/algos/RANDOM.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/RANDOM.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} \
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--search_space_name ${space} \
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@ -1,6 +1,6 @@
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#!/bin/bash
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# One-Shot Neural Architecture Search via Self-Evaluated Template Network, ICCV 2019
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# bash ./scripts-search/algos/SETN.sh cifar10 0 -1
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# bash ./scripts-search/NAS-Bench-201-algos/SETN.sh cifar10 0 -1
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -33,7 +33,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/SETN-${dataset}-BN${BN}
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OMP_NUM_THREADS=4 python ./exps/algos/SETN.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/SETN.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} --data_path ${data_path} \
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--search_space_name ${space} \
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@ -1,5 +1,5 @@
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#!/bin/bash
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# bash ./scripts-search/algos/DARTS-test-Gradient.sh cifar10 0 5
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# bash ./scripts-search/NAS-Bench-201-algos/DARTS-test-Gradient.sh cifar10 0 5
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echo script name: $0
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echo $# arguments
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if [ "$#" -ne 3 ] ;then
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@ -33,7 +33,7 @@ benchmark_file=${TORCH_HOME}/NAS-Bench-201-v1_1-096897.pth
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save_dir=./output/search-cell-${space}/DARTS-V1-${dataset}-BN${BN}-Gradient${gradient_clip}
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OMP_NUM_THREADS=4 python ./exps/algos/DARTS-V1.py \
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OMP_NUM_THREADS=4 python ./exps/NAS-Bench-201-algos/DARTS-V1.py \
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--save_dir ${save_dir} --max_nodes ${max_nodes} --channel ${channel} --num_cells ${num_cells} \
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--dataset ${dataset} --data_path ${data_path} \
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--search_space_name ${space} \
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@ -6,5 +6,5 @@ lrs="0.01 0.02 0.1 0.2 0.5"
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for lr in ${lrs}
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do
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bash ./scripts-search/algos/REINFORCE.sh ${lr} -1
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bash ./scripts-search/NAS-Bench-201-algos/REINFORCE.sh ${lr} -1
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done
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