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"""Small, CPU-only tests for the resumable direct compact_v1 builder."""
from __future__ import annotations
import json
import tempfile
import time
import unittest
from pathlib import Path
from unittest import mock
import torch
from torch_geometric.data import Data
import build_compact_v1_direct as direct
from compact_graph_dataset import CompactGraphDataset
def _synthetic_graph(
system_id: str,
pose_number: int,
*,
split_static: bool = False,
) -> Data:
n_protein = 2
n_nodes = 4
x = torch.zeros((n_nodes, 82), dtype=torch.float32)
x[:, 0] = 1.0
x[:n_protein, 11] = 1.0
x[n_protein:, 31] = 1.0
x[:n_protein, 32] = 1.0
x[n_protein:, 33] = 1.0
x[:, 61:71] = 0.25
x[:, 34:61] = float(pose_number)
x[:, 71:82] = float(pose_number) / 10.0
if split_static and pose_number == 2:
x[2, 0] = 0.0
x[2, 1] = 1.0
system_offset = 5.0 if system_id == "sys_b" else 0.0
protein_pos = torch.tensor(
[[system_offset, 0.0, 0.0], [system_offset + 1.0, 0.0, 0.0]],
dtype=torch.float32,
)
ligand_pos = torch.tensor(
[
[system_offset + 1.5, 0.1 * pose_number, 0.0],
[system_offset + 2.0, 0.2 * pose_number, 0.0],
],
dtype=torch.float32,
)
native_ligand = torch.tensor(
[
[system_offset + 1.5, 0.0, 0.0],
[system_offset + 2.0, 0.0, 0.0],
],
dtype=torch.float32,
)
pos = torch.cat((protein_pos, ligand_pos), dim=0)
y_grt = torch.cat((protein_pos, native_ligand), dim=0)
y_true = torch.linalg.vector_norm(pos - y_grt, dim=1, keepdim=True)
edge_index = torch.tensor(
[[0, 1, 1, 2, 2, 3], [1, 0, 2, 1, 3, 2]],
dtype=torch.int64,
)
src, dst = edge_index
distance = torch.linalg.vector_norm(
pos[src].to(torch.float64) - pos[dst].to(torch.float64),
dim=1,
)
edge_attr = torch.stack(
(
(distance / 6.0).to(torch.float32),
torch.exp(-distance / 3.0).to(torch.float32),
(src < n_protein).to(torch.float32),
(dst < n_protein).to(torch.float32),
),
dim=1,
)
is_protein = torch.zeros((n_nodes, 1), dtype=torch.float32)
is_protein[:n_protein] = 1.0
return Data(
x=x,
edge_index=edge_index,
edge_attr=edge_attr,
pos=pos,
is_protein=is_protein,
y_true=y_true,
y_pred=pos.clone(),
y_grt=y_grt,
num_nodes=n_nodes,
)
class DirectCompactBuilderTest(unittest.TestCase):
def test_exclusive_output_lock_rejects_concurrent_resume(self) -> None:
with tempfile.TemporaryDirectory(prefix="direct_compact_lock_") as temp:
output = Path(temp) / "compact"
with direct._exclusive_build_lock(output):
with self.assertRaisesRegex(
RuntimeError, "another direct compact build"
):
with direct._exclusive_build_lock(output):
self.fail("the second lock must not be acquired")
def test_corrupt_pose_checkpoint_is_rebuilt(self) -> None:
with tempfile.TemporaryDirectory(prefix="direct_compact_corrupt_") as temp:
root = Path(temp)
for name in ("protein.pdb", "native.pdb", "pose_1.pdb"):
(root / name).write_text("test\n", encoding="utf-8")
pose = direct.PoseSpec(
source_graph_index=0,
system_id="sys_a",
protein=(root / "protein.pdb"),
ligand_native=(root / "native.pdb"),
ligand_pred=(root / "pose_1.pdb"),
)
system = direct.SystemSpec(
ordinal=0,
system_id="sys_a",
protein=pose.protein,
ligand_native=pose.ligand_native,
poses=(pose,),
)
work_dir = root / "work"
work_dir.mkdir()
corrupt = direct._pose_graph_path(work_dir, 0)
corrupt.write_bytes(b"not a torch checkpoint")
calls = []
def graph_builder(**kwargs):
calls.append(kwargs["ligand_pred_pdb"])
return _synthetic_graph("sys_a", 1)
config = direct.BuildConfig(
data_dir=root,
output_dir=root / "output",
method="protenix",
)
graphs = direct.build_pose_graphs(
system,
work_dir,
config,
graph_builder=graph_builder,
)
self.assertEqual(len(calls), 1)
self.assertEqual(len(graphs), 1)
rebuilt = torch.load(corrupt, map_location="cpu", weights_only=False)
self.assertTrue(torch.equal(rebuilt.x, graphs[0].x))
def test_resume_atomic_publish_and_original_system_index(self) -> None:
with tempfile.TemporaryDirectory(prefix="direct_compact_test_") as temp:
root = Path(temp)
data_dir = root / "docking"
output_dir = root / "compact"
raw_poses = []
for system_id in ("sys_a", "sys_b"):
system_dir = data_dir / system_id
system_dir.mkdir(parents=True)
protein = system_dir / "protein.pdb"
native = system_dir / "ligand_native.pdb"
protein.write_text("test\n", encoding="utf-8")
native.write_text("test\n", encoding="utf-8")
for pose_number in (1, 2):
pose = system_dir / f"{system_id}_pose_{pose_number}.pdb"
pose.write_text("test\n", encoding="utf-8")
raw_poses.append(
{
"pdb_id": system_id,
"protein": str(protein),
"ligand_native": str(native),
"ligand_pred": str(pose),
}
)
def graph_builder(**kwargs):
pose_path = Path(kwargs["ligand_pred_pdb"])
system_id = pose_path.parent.name
pose_number = int(pose_path.stem.rsplit("_", 1)[1])
return _synthetic_graph(
system_id,
pose_number,
split_static=system_id == "sys_b",
)
def first_attempt_builder(**kwargs):
if Path(kwargs["ligand_pred_pdb"]).parent.name == "sys_b":
raise RuntimeError("intentional interruption")
return graph_builder(**kwargs)
config = direct.BuildConfig(
data_dir=data_dir.resolve(),
output_dir=output_dir.resolve(),
method="protenix",
target_shard_mib=1,
num_workers=1,
)
with mock.patch.object(direct, "find_docking_poses", return_value=raw_poses):
with self.assertRaisesRegex(RuntimeError, "intentional interruption"):
direct.run(config, graph_builder=first_attempt_builder)
progress_path = (
output_dir.with_name(".compact.building")
/ ".build_state"
/ "progress.json"
)
with progress_path.open("r", encoding="utf-8") as handle:
progress = json.load(handle)
self.assertEqual(progress["next_system_index"], 1)
self.assertEqual(progress["successful_source_systems"], 1)
resumed = direct.BuildConfig(
**{**config.__dict__, "resume": True}
)
manifest = direct.run(resumed, graph_builder=graph_builder)
self.assertTrue((output_dir / "manifest.json").is_file())
self.assertFalse(output_dir.with_name(".compact.building").exists())
self.assertFalse((output_dir / ".build_state").exists())
self.assertEqual(manifest["n_graphs"], 4)
self.assertEqual(manifest["n_source_systems"], 2)
# sys_b is intentionally split into two exact-content storage groups.
self.assertEqual(manifest["n_systems"], 3)
with (output_dir / "system_index.json").open(
"r", encoding="utf-8"
) as handle:
system_index = json.load(handle)
self.assertEqual(
system_index["graph_to_system"],
["sys_a", "sys_a", "sys_b", "sys_b"],
)
self.assertEqual(system_index["n_systems"], 2)
dataset = CompactGraphDataset(output_dir)
self.assertEqual(len(dataset), 4)
expected = [
_synthetic_graph("sys_a", 1),
_synthetic_graph("sys_a", 2),
_synthetic_graph("sys_b", 1, split_static=True),
_synthetic_graph("sys_b", 2, split_static=True),
]
for actual, reference in zip(dataset, expected):
for name in (
"x",
"edge_index",
"edge_attr",
"pos",
"is_protein",
"y_true",
"y_pred",
"y_grt",
):
self.assertTrue(
torch.allclose(
getattr(actual, name),
getattr(reference, name),
rtol=1e-6,
atol=1e-6,
),
msg=name,
)
def test_parallel_system_build_matches_serial_order(self) -> None:
"""Out-of-order worker completion must not change source graph order."""
with tempfile.TemporaryDirectory(prefix="direct_compact_parallel_") as temp:
root = Path(temp)
data_dir = root / "docking"
raw_poses = []
for system_id in ("sys_a", "sys_b", "sys_c"):
system_dir = data_dir / system_id
system_dir.mkdir(parents=True)
protein = system_dir / "protein.pdb"
native = system_dir / "ligand_native.pdb"
protein.write_text("test\n", encoding="utf-8")
native.write_text("test\n", encoding="utf-8")
for pose_number in (1, 2):
pose = system_dir / f"{system_id}_pose_{pose_number}.pdb"
pose.write_text("test\n", encoding="utf-8")
raw_poses.append(
{
"pdb_id": system_id,
"protein": str(protein),
"ligand_native": str(native),
"ligand_pred": str(pose),
}
)
def graph_builder(**kwargs):
pose_path = Path(kwargs["ligand_pred_pdb"])
system_id = pose_path.parent.name
# sys_a is deliberately slower so workers complete out of order.
if system_id == "sys_a":
time.sleep(0.15)
pose_number = int(pose_path.stem.rsplit("_", 1)[1])
return _synthetic_graph(system_id, pose_number)
serial_output = root / "serial"
parallel_output = root / "parallel"
serial_config = direct.BuildConfig(
data_dir=data_dir.resolve(),
output_dir=serial_output.resolve(),
method="protenix",
target_shard_mib=1,
num_workers=1,
)
parallel_config = direct.BuildConfig(
data_dir=data_dir.resolve(),
output_dir=parallel_output.resolve(),
method="protenix",
target_shard_mib=1,
num_workers=1,
system_workers=2,
memory_budget_gib=8.0,
)
with mock.patch.object(direct, "find_docking_poses", return_value=raw_poses):
serial_manifest = direct.run(serial_config, graph_builder=graph_builder)
parallel_manifest = direct.run(parallel_config, graph_builder=graph_builder)
self.assertEqual(serial_manifest["n_graphs"], parallel_manifest["n_graphs"])
self.assertEqual(serial_manifest["graph_map"], parallel_manifest["graph_map"])
self.assertEqual(serial_manifest["shards"], parallel_manifest["shards"])
with (serial_output / "system_index.json").open("r", encoding="utf-8") as handle:
serial_index = json.load(handle)
with (parallel_output / "system_index.json").open("r", encoding="utf-8") as handle:
parallel_index = json.load(handle)
self.assertEqual(serial_index, parallel_index)
def test_parallel_ready_checkpoint_resumes_in_source_order(self) -> None:
"""A later ready system survives interruption before the earlier system."""
with tempfile.TemporaryDirectory(prefix="direct_compact_parallel_resume_") as temp:
root = Path(temp)
data_dir = root / "docking"
output_dir = root / "compact"
raw_poses = []
for system_id in ("sys_a", "sys_b"):
system_dir = data_dir / system_id
system_dir.mkdir(parents=True)
protein = system_dir / "protein.pdb"
native = system_dir / "ligand_native.pdb"
protein.write_text("test\n", encoding="utf-8")
native.write_text("test\n", encoding="utf-8")
for pose_number in (1, 2):
pose = system_dir / f"{system_id}_pose_{pose_number}.pdb"
pose.write_text("test\n", encoding="utf-8")
raw_poses.append(
{
"pdb_id": system_id,
"protein": str(protein),
"ligand_native": str(native),
"ligand_pred": str(pose),
}
)
def graph_builder(**kwargs):
pose_path = Path(kwargs["ligand_pred_pdb"])
system_id = pose_path.parent.name
pose_number = int(pose_path.stem.rsplit("_", 1)[1])
return _synthetic_graph(system_id, pose_number)
def interrupted_builder(**kwargs):
pose_path = Path(kwargs["ligand_pred_pdb"])
if pose_path.parent.name == "sys_a":
time.sleep(0.35)
raise RuntimeError("intentional parallel interruption")
return graph_builder(**kwargs)
config = direct.BuildConfig(
data_dir=data_dir.resolve(),
output_dir=output_dir.resolve(),
method="protenix",
target_shard_mib=1,
num_workers=1,
system_workers=2,
memory_budget_gib=8.0,
)
with mock.patch.object(direct, "find_docking_poses", return_value=raw_poses):
with self.assertRaisesRegex(RuntimeError, "parallel worker.*sys_a"):
direct.run(config, graph_builder=interrupted_builder)
stage_dir = output_dir.with_name(".compact.building")
progress_path = stage_dir / ".build_state" / "progress.json"
with progress_path.open("r", encoding="utf-8") as handle:
progress = json.load(handle)
self.assertEqual(progress["next_system_index"], 0)
self.assertTrue(
(stage_dir / ".build_state" / "ready" / "system_00000001.pt").is_file()
)
resumed = direct.BuildConfig(**{**config.__dict__, "resume": True})
manifest = direct.run(resumed, graph_builder=graph_builder)
self.assertEqual(manifest["n_graphs"], 4)
with (output_dir / "system_index.json").open("r", encoding="utf-8") as handle:
system_index = json.load(handle)
self.assertEqual(
system_index["graph_to_system"], ["sys_a", "sys_a", "sys_b", "sys_b"]
)
if __name__ == "__main__":
unittest.main()
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