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Merged
ffelten merged 3 commits into from
Jul 16, 2025
Merged

Push model to wandb only if tracking enabled #42

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063c1e5
Push model to wandb only if tracking enabled
ffelten Jul 16, 2025
5127430
Update collab to not use wandb by default
ffelten Jul 16, 2025
e06e493
Add colab badge
ffelten Jul 16, 2025
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1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -3,6 +3,7 @@
https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](
https://github.com/astral-sh/ruff)
[![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/IDEALLab/EngiOpt/blob/main/example_easy_model.ipynb)

# EngiOpt

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15 changes: 8 additions & 7 deletions engiopt/cgan_1d/cgan_1d.py
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Expand Up @@ -394,12 +394,13 @@ def sample_designs(n_designs: int) -> tuple[th.Tensor, th.Tensor]:

th.save(ckpt_gen, "generator.pth")
th.save(ckpt_disc, "discriminator.pth")
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])
if args.track:
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])

wandb.finish()
15 changes: 8 additions & 7 deletions engiopt/cgan_2d/cgan_2d.py
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Expand Up @@ -313,12 +313,13 @@ def sample_designs(n_designs: int) -> tuple[th.Tensor, th.Tensor]:

th.save(ckpt_gen, "generator.pth")
th.save(ckpt_disc, "discriminator.pth")
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])
if args.track:
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])

wandb.finish()
13 changes: 7 additions & 6 deletions engiopt/cgan_bezier/cgan_bezier.py
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Expand Up @@ -636,13 +636,14 @@ def sample_designs(n_designs: int) -> tuple[th.Tensor, th.Tensor, th.Tensor]:

th.save(ckpt_gen, "bezier_generator.pth")
th.save(ckpt_disc, "bezier_discriminator.pth")
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("bezier_generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("bezier_discriminator.pth")
if args.track:
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("bezier_generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("bezier_discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])

if args.track:
wandb.finish()
15 changes: 8 additions & 7 deletions engiopt/cgan_cnn_2d/cgan_cnn_2d.py
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Expand Up @@ -410,12 +410,13 @@ def sample_designs(n_designs: int) -> tuple[th.Tensor, th.Tensor]:

th.save(ckpt_gen, "generator.pth")
th.save(ckpt_disc, "discriminator.pth")
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])
if args.track:
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])

wandb.finish()
7 changes: 4 additions & 3 deletions engiopt/diffusion_1d/diffusion_1d.py
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Expand Up @@ -269,9 +269,10 @@ class Args:
}

th.save(ckpt, "model.pth")
artifact = wandb.Artifact(f"{args.problem_id}_{args.algo}_model", type="model")
artifact.add_file("model.pth")
if args.track:
artifact = wandb.Artifact(f"{args.problem_id}_{args.algo}_model", type="model")
artifact.add_file("model.pth")

wandb.log_artifact(artifact, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact, aliases=[f"seed_{args.seed}"])

wandb.finish()
7 changes: 4 additions & 3 deletions engiopt/diffusion_2d_cond/diffusion_2d_cond.py
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Expand Up @@ -437,9 +437,10 @@ def sample_designs(model: UNet2DConditionModel, n_designs: int = 25) -> tuple[th
}

th.save(ckpt_model, "model.pth")
artifact_model = wandb.Artifact(f"{args.problem_id}_{args.algo}_model", type="model")
artifact_model.add_file("model.pth")
if args.track:
artifact_model = wandb.Artifact(f"{args.problem_id}_{args.algo}_model", type="model")
artifact_model.add_file("model.pth")

wandb.log_artifact(artifact_model, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_model, aliases=[f"seed_{args.seed}"])

wandb.finish()
15 changes: 8 additions & 7 deletions engiopt/gan_1d/gan_1d.py
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Expand Up @@ -334,12 +334,13 @@ def prepare_data(problem: Problem, device: th.device) -> tuple[th.utils.data.Ten

th.save(ckpt_gen, "generator.pth")
th.save(ckpt_disc, "discriminator.pth")
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])
if args.track:
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])

wandb.finish()
15 changes: 8 additions & 7 deletions engiopt/gan_2d/gan_2d.py
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Expand Up @@ -272,12 +272,13 @@ def sample_designs(n_designs: int) -> th.Tensor:

th.save(ckpt_gen, "generator.pth")
th.save(ckpt_disc, "discriminator.pth")
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])
if args.track:
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])

wandb.finish()
13 changes: 7 additions & 6 deletions engiopt/gan_bezier/gan_bezier.py
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Expand Up @@ -611,13 +611,14 @@ def prepare_data(problem, batch_size, device):

th.save(ckpt_gen, "bezier_generator.pth")
th.save(ckpt_disc, "bezier_discriminator.pth")
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("bezier_generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("bezier_discriminator.pth")
if args.track:
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("bezier_generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("bezier_discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])

if args.track:
wandb.finish()
15 changes: 8 additions & 7 deletions engiopt/gan_cnn_2d/gan_cnn_2d.py
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Expand Up @@ -328,12 +328,13 @@ def sample_designs(n_designs: int) -> th.Tensor:

th.save(ckpt_gen, "generator.pth")
th.save(ckpt_disc, "discriminator.pth")
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])
if args.track:
artifact_gen = wandb.Artifact(f"{args.problem_id}_{args.algo}_generator", type="model")
artifact_gen.add_file("generator.pth")
artifact_disc = wandb.Artifact(f"{args.problem_id}_{args.algo}_discriminator", type="model")
artifact_disc.add_file("discriminator.pth")

wandb.log_artifact(artifact_gen, aliases=[f"seed_{args.seed}"])
wandb.log_artifact(artifact_disc, aliases=[f"seed_{args.seed}"])

wandb.finish()
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