Lira2021: fix readme install instructions
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@ -8,14 +8,15 @@ by Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, and F
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### INSTALLING
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### INSTALLING
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You will need to install fairly standard dependencies
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You will need to install fairly standard dependencies and python 3.11 minimum.
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`pip install scipy, sklearn, numpy, matplotlib`
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```
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pip install scipy scikit-learn numpy matplotlib tensorflow tensorflow_datasets objax
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and also some machine learning framework to train models. We train our models
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RELEASE_URL="https://storage.googleapis.com/jax-releases/jax_cuda_releases.html"
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with JAX + ObJAX so you will need to follow build instructions for that
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JAX_VERSION=`python3 -c 'import jax; print(jax.__version__)'`
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https://github.com/google/objax
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pip uninstall -y jaxlib
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https://objax.readthedocs.io/en/latest/installation_setup.html
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pip install -f $RELEASE_URL jax[cuda]==$JAX_VERSION
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```
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### RUNNING THE CODE
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### RUNNING THE CODE
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@ -11,7 +11,7 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# limitations under the License.
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mkdir logs
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mkdir -p logs
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SECONDS=0
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SECONDS=0
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@ -11,6 +11,7 @@
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# limitations under the License.
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mkdir -p logs
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CUDA_VISIBLE_DEVICES='0' python3 -u train.py --dataset=cifar10 --epochs=100 --save_steps=20 --arch wrn28-2 --num_experiments 16 --expid 0 --logdir exp/cifar10 &> logs/log_0 &
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CUDA_VISIBLE_DEVICES='0' python3 -u train.py --dataset=cifar10 --epochs=100 --save_steps=20 --arch wrn28-2 --num_experiments 16 --expid 0 --logdir exp/cifar10 &> logs/log_0 &
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CUDA_VISIBLE_DEVICES='1' python3 -u train.py --dataset=cifar10 --epochs=100 --save_steps=20 --arch wrn28-2 --num_experiments 16 --expid 1 --logdir exp/cifar10 &> logs/log_1 &
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CUDA_VISIBLE_DEVICES='1' python3 -u train.py --dataset=cifar10 --epochs=100 --save_steps=20 --arch wrn28-2 --num_experiments 16 --expid 1 --logdir exp/cifar10 &> logs/log_1 &
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