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Mdc/add protpardelle #274

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58f9d0f
Updating tests in test_runner.py to allow them to run on only one GPU
marcuscollins Jun 2, 2026
9231374
feat(models): add Protpardelle-1c StructureModelWrapper
marcuscollins Jun 2, 2026
50fffe9
[WIP] fixing Claude's implementation of a Protenix wrapper, so it doe…
marcuscollins Jun 12, 2026
6774d82
get default model config from protpardelle module rather than keeping…
marcuscollins Jun 12, 2026
40a7f30
Starting to debug Protpardelle on actl
marcuscollins Jun 13, 2026
c53f5ad
fix(protpardelle): complete denoising step wiring (#267)
manzuoni-astera Jun 23, 2026
6713208
Modify EDMSamplerConfig options for Protpardelle-1c
marcuscollins Jun 29, 2026
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4 changes: 3 additions & 1 deletion .actlignore
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,9 @@
.pixi/
grid_search_results/
outputs/
/data/
data/
!/src/sampleworks/data/
!/src/sampleworks/data/**
initial_dataset_40*/
checkpoints/
release_data/
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16,758 changes: 11,807 additions & 4,951 deletions pixi.lock
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46 changes: 44 additions & 2 deletions pyproject.toml
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Expand Up @@ -23,16 +23,51 @@ pypi-dependencies = {"boltz" = "*", "cuequivariance-torch" = "*", "cuequivarianc
platforms = ["linux-64"]

[tool.pixi.feature.boltz-osx]
pypi-dependencies = {"boltz" = "*", "cuequivariance-torch" = "*", "rdkit" = ">=2025.3.6"}
pypi-dependencies = {"boltz" = "*", "cuequivariance-torch" = "*", "rdkit" = ">=2025.3.6", "joblib" = "*", "sfcalculator-torch" = ">=0.3.2"}
platforms = ["osx-arm64"]


[tool.pixi.feature.protenix]
pypi-dependencies = {"protenix" = "*", "einx" = "*", "triton" = "*"}
platforms = ["linux-64"]

[tool.pixi.feature.protpardelle]
platforms = ["linux-64", "osx-arm64"]

[tool.pixi.feature.protpardelle.dependencies]
biopython = "*"
einops = "*"
huggingface_hub = "*"
hydra-core = "*"
jupyter = "*"
numpy = ">=1.25.0,<2.0"
omegaconf = "*"
pandas = "==2.3.1"
prody = "*"
pyyaml = "*"
scipy = "*"
pytorch = ">=2.6.0,<2.8"
tqdm = "*"
typer = "*"

[tool.pixi.feature.protpardelle.pypi-dependencies]
protpardelle = {git = "https://github.com/ProteinDesignLab/protpardelle-1c.git"}
biotite = "*"
dm-tree = "*"
jaxtyping = "*"
ml_collections = "*"
modelcif = "*"
transformers = "*"
wandb = "*"

[tool.pixi.feature.protpardelle.pypi-options.dependency-overrides]
pandas = "==2.3.1"

[project]
authors = [{email = "karson.chrispens@ucsf.edu", name = "Karson Chrispens"}]
authors = [
{email = "karson.chrispens@ucsf.edu", name = "Karson Chrispens"},
{email = "marcus.collins@astera.org", name = "Marcus D. Collins"}
]
dependencies = [
"atomworks[ml]==2.1.1",
"python-dotenv",
Expand Down Expand Up @@ -90,6 +125,8 @@ boltz-dev = {features = ["boltz", "dev"]}
boltz-osx = {features = ["boltz-osx", "dev", "analysis"]}
protenix = {features = ["protenix"]}
protenix-dev = {features = ["protenix", "dev"]}
protpardelle = {features = ["protpardelle"]}
protpardelle-dev = {features = ["protpardelle", "dev"]}
rf3 = {features = ["rf3"]}
rf3-dev = {features = ["rf3", "dev"]}

Expand All @@ -99,6 +136,11 @@ rdkit = ">=2024.3.5,<2025.9"
[tool.pixi.feature.rf3.pypi-dependencies]
rc-foundry = {editable = true, extras = ["rf3"], git = "https://github.com/k-chrispens/foundry.git"}

[tool.pixi.pypi-options.dependency-overrides]
pandas = "==2.3.1"
gemmi = "==0.6.7"
Comment on lines +139 to +141

@coderabbitai coderabbitai Bot Jun 29, 2026

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🩺 Stability & Availability | 🟠 Major | ⚡ Quick win

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
set -euo pipefail
python - <<'PY'
import pathlib, tomllib
data = tomllib.loads(pathlib.Path("pyproject.toml").read_text())
pixi = data["tool"]["pixi"]

print("Top-level dependency overrides:")
print(pixi.get("pypi-options", {}).get("dependency-overrides", {}))

for feature_name, feature_cfg in pixi.get("feature", {}).items():
    deps = feature_cfg.get("dependencies", {})
    pypi_deps = feature_cfg.get("pypi-dependencies", {})
    overrides = feature_cfg.get("pypi-options", {}).get("dependency-overrides", {})
    if "gemmi" in deps or "gemmi" in pypi_deps or overrides:
        print(f"\nfeature={feature_name}")
        if "gemmi" in deps:
            print("  dependencies.gemmi =", deps["gemmi"])
        if "gemmi" in pypi_deps:
            print("  pypi-dependencies.gemmi =", pypi_deps["gemmi"])
        if overrides:
            print("  dependency-overrides =", overrides)
PY

echo
echo "Other gemmi references in the repo:"
rg -n '\bgemmi\b' .

Repository: diff-use/sampleworks

Length of output: 670

🏁 Script executed:

#!/bin/bash
set -euo pipefail
nl -ba pyproject.toml | sed -n '55,170p'

Repository: diff-use/sampleworks

Length of output: 198

🏁 Script executed:

#!/bin/bash
set -euo pipefail

echo "Relevant pyproject.toml slice:"
sed -n '55,170p' pyproject.toml

echo
echo "Occurrences of dependency-overrides headers:"
grep -n '^\[tool\.pixi\.pypi-options\.dependency-overrides\]$' pyproject.toml || true

echo
echo "All gemmi/pandas override lines:"
grep -nE '^(pandas|gemmi)\s*=' pyproject.toml || true

Repository: diff-use/sampleworks

Length of output: 3634

Remove the duplicate dependency-overrides table. pyproject.toml declares [tool.pixi.pypi-options.dependency-overrides] twice (around lines 139 and 150), which makes the file invalid TOML. Keep a single table and move gemmi = "==0.6.7" into it only if that pin is meant to apply globally.

🤖 Prompt for AI Agents 
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@pyproject.toml` around lines 139 - 141, The pyproject.toml currently defines
the dependency-overrides table twice under tool.pixi.pypi-options, which breaks
TOML parsing. Consolidate the duplicate
[tool.pixi.pypi-options.dependency-overrides] blocks into a single table, and
keep the pandas and gemmi pins together there only if they are intended to apply
globally.



[tool.pixi.pypi-dependencies]
sampleworks = {editable = true, path = "."}

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2 changes: 2 additions & 0 deletions src/sampleworks/cli/guidance.py
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Expand Up @@ -3,13 +3,15 @@
from __future__ import annotations

import sys
from loguru import logger

from sampleworks.utils.guidance_script_arguments import GuidanceConfig
from sampleworks.utils.guidance_script_utils import get_model_and_device, run_guidance


def main(argv: list[str] | None = None) -> int:
config = GuidanceConfig.from_cli(argv)
logger.info(f"Running guidance with config: {config}")
device, model_wrapper = get_model_and_device(
config.device,
getattr(config, "model_checkpoint", None),
Expand Down
2 changes: 1 addition & 1 deletion src/sampleworks/core/samplers/edm.py
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Expand Up @@ -415,7 +415,7 @@ def step(

# Store eps separately for proper frame transformation
# eps_scale will be float if check_context didn't raise
eps = torch.randn_like(maybe_augmented_state) * eps_scale # ty: ignore[unsupported-operator]
eps = torch.randn_like(maybe_augmented_state) * eps_scale
noisy_state = maybe_augmented_state + eps
noisy_state = torch.as_tensor(noisy_state).detach().requires_grad_(allow_gradients)

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101 changes: 101 additions & 0 deletions src/sampleworks/data/cc89_epoch415.yaml
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@@ -0,0 +1,101 @@
data:
auto_calc_sigma_data: true
chain_residx_gap: 200
dummy_fill_mode: zero
fixed_size: 512
mixing_ratios:
- 1.0
n_aatype_tokens: 21
n_examples_for_sigma_data: 500
pdb_paths:
- /scratch/users/tianyulu/augmented_ingraham_cath_bugfree
se3_data_augment: true
sigma_data: 10.3
subset:
- designable_
translation_scale: 1.0
diffusion:
sampling:
function: uniform
s_max: 80
s_min: 0.001
training:
function: lognormal
psigma_mean: -0.5
psigma_std: 1.5
model:
compute_loss_on_all_atoms: false
conditioning_style: concat
crop_conditional: true
dummy_fill_masked_atoms: false
full_mpnn_model_path: /scratch/users/tianyulu/farfalle/ProteinMPNN/vanilla_model_weights
mpnn_model:
label_smoothing: 0.1
n_channel: 128
n_layers: 3
n_neighbors: 32
noise_cond_mult: 4
use_self_conditioning: true
mpnn_model_checkpoint: ''
pretrained_modules: []
struct_model:
arch: dit
n_atoms: 37
n_channel: 256
noise_cond_mult: 4
uvit:
cat_pwd_to_conv: false
conv_skip_connection: false
dim_head: 32
n_blocks_per_layer: 2
n_filt_per_layer: []
n_heads: 8
n_layers: 10
patch_size: 1
position_embedding_max: 32
position_embedding_type: rotary
struct_model_checkpoint: ''
task: ai-allatom
train:
batch_size: 32
checkpoint_freq: 1
checkpoints: []
ckpt_path: /scratch/users/tianyulu/farfalle/out_dir/farfalle/cc89/checkpoints/epoch206_training_state.pth
clip_grad_norm: true
crop_cond:
contiguous_prob: 0.05
discontiguous_prob: 0.9
dist_threshold: 45.0
max_discontiguous_res: 24
max_span_len: 12
recenter_coords: true
sidechain_only_prob: 0.0
sidechain_prob: 0.9
terms_prob: 0.5
crop_conditional: true
decay_steps: 2000000
eval_freq: 8000000
eval_loss_t:
- 0.1
- 0.3
- 0.5
- 0.7
- 0.9
fpd_length_ranges_per_chain:
- - 50
- 256
grad_clip_val: 1.0
length_ranges_per_chain:
- - 166
- 188
lr: 0.0001
max_epochs: 10000
n_eval_samples: 10
n_fpd_samples: 0
sc_num_seqs: 4
seed: 0
self_cond_train_prob: 0.9
shapes_path: /scratch/users/tianyulu/protein_shapes
subsample_eval_set: 0.05
warmup_steps: 1000
weight_decay: 0.0
1 change: 1 addition & 0 deletions src/sampleworks/models/protpardelle/__init__.py
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@@ -0,0 +1 @@
"""Protpardelle-1c model wrapper."""
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