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Use uv to manage development environment #10

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2 changes: 1 addition & 1 deletion .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,7 @@ target/
.ipynb_checkpoints

# pyenv
.python-version
# .python-version

# celery beat schedule file
celerybeat-schedule
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1 change: 1 addition & 0 deletions .python-version
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@@ -0,0 +1 @@
3.11
16 changes: 8 additions & 8 deletions README.md
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Expand Up @@ -15,7 +15,7 @@ to the [Max-SAT Evaluation
### Preparation

```console
$ pip3 install -r requirements.txt
$ uv sync
```

### (Optional) Training model
Expand All @@ -39,11 +39,11 @@ repository and should be used with caution.
Run the following to generate the same data set submitted to Max-SAT Evaluation 2020:

```console
$ python3 generate_maxsat_instances.py --dataset mnist --model models/mnist.npz -o outdir \
$ uv run generate_maxsat_instances.py --dataset mnist --model models/mnist.npz -o outdir \
--format wcnf --card totalizer --norm inf --target adversarial --instances-per-class 2
$ python3 generate_maxsat_instances.py --dataset mnist_rot --model models/mnist_rot.npz -o outdir \
$ uv run generate_maxsat_instances.py --dataset mnist_rot --model models/mnist_rot.npz -o outdir \
--format wcnf --card totalizer --norm inf --target adversarial --instances-per-class 2
$ python3 generate_maxsat_instances.py --dataset mnist_back_image --model models/mnist_back_image.npz -o outdir \
$ uv run generate_maxsat_instances.py --dataset mnist_back_image --model models/mnist_back_image.npz -o outdir \
--format wcnf --card totalizer --norm inf --target adversarial --instances-per-class 2
```

Expand All @@ -54,11 +54,11 @@ You can also specify an individual sample by using `--instance-no` instead of `-
You can use `generate_mip_instances.py` instead:

```console
$ python3 generate_mip_instances.py --dataset mnist --model models/mnist.npz -o outdir \
$ uv run generate_mip_instances.py --dataset mnist --model models/mnist.npz -o outdir \
--norm inf --target adversarial --instances-per-class 2
$ python3 generate_mip_instances.py --dataset mnist_rot --model models/mnist_rot.npz -o outdir \
$ uv run generate_mip_instances.py --dataset mnist_rot --model models/mnist_rot.npz -o outdir \
--norm inf --target adversarial --instances-per-class 2
$ python3 generate_mip_instances.py --dataset mnist_back_image --model models/mnist_back_image.npz -o outdir \
$ uv run generate_mip_instances.py --dataset mnist_back_image --model models/mnist_back_image.npz -o outdir \
--norm inf --target adversarial --instances-per-class 2
```

Expand All @@ -67,7 +67,7 @@ $ python3 generate_mip_instances.py --dataset mnist_back_image --model models/mn
Once the solver successfully solves a problem instance, you can check the solution as follows:

```console
$ python3 verify_solution.py --dataset mnist --instance 7 \
$ uv run verify_solution.py --dataset mnist --instance 7 \
--output-image perturbated.png \
--output-orig-image orig.png \
--format maxsat \
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4 changes: 0 additions & 4 deletions requirements.txt
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