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f0652e2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 | #!/usr/bin/env python3
"""Validate the standardized DeepMind CylinderFlow dataset package."""
from __future__ import annotations
import argparse
import hashlib
import json
from pathlib import Path
EXPECTED_SPLITS = ["train", "valid", "test"]
EXPECTED_REQUIRED = {
"data/cylinder_flow/meta.json",
"data/cylinder_flow/train.tfrecord",
"data/cylinder_flow/valid.tfrecord",
"data/cylinder_flow/test.tfrecord",
"data/cylinder_flow/stats/edge_stats.json",
"data/cylinder_flow/stats/node_stats.json",
}
def fail(message: str) -> None:
raise SystemExit(f"[FAIL] {message}")
def sha256_file(path: Path) -> str:
digest = hashlib.sha256()
with path.open("rb") as f:
for chunk in iter(lambda: f.read(1024 * 1024), b""):
digest.update(chunk)
return digest.hexdigest()
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument("--dataset-root", default=".", help="dataset package root")
parser.add_argument(
"--verify-sha256",
action="store_true",
help="recompute and verify SHA256 values from files_sha256.jsonl",
)
parser.add_argument(
"--skip-tfrecord-read",
action="store_true",
help="skip optional TensorFlow first-record readability check",
)
return parser.parse_args()
def check_files(dataset_root: Path) -> dict:
sizes = {}
for rel_path in sorted(EXPECTED_REQUIRED):
path = dataset_root / rel_path
if not path.is_file():
fail(f"missing required file: {rel_path}")
if path.stat().st_size <= 0:
fail(f"empty required file: {rel_path}")
sizes[rel_path] = path.stat().st_size
return sizes
def check_metadata(data_dir: Path) -> dict:
meta = json.loads((data_dir / "meta.json").read_text(encoding="utf-8"))
if meta.get("simulator") != "comsol":
fail("meta.json simulator must be comsol")
if meta.get("trajectory_length") != 600:
fail("meta.json trajectory_length must be 600")
expected_fields = ["cells", "mesh_pos", "node_type", "velocity", "pressure"]
if meta.get("field_names") != expected_fields:
fail("meta.json field_names mismatch")
expected_shapes = {
"cells": [1, -1, 3],
"mesh_pos": [1, -1, 2],
"node_type": [1, -1, 1],
"velocity": [600, -1, 2],
"pressure": [600, -1, 1],
}
expected_dtypes = {
"cells": "int32",
"mesh_pos": "float32",
"node_type": "int32",
"velocity": "float32",
"pressure": "float32",
}
for key in expected_fields:
feature = meta.get("features", {}).get(key)
if not feature:
fail(f"meta.json missing feature {key}")
if feature.get("shape") != expected_shapes[key]:
fail(f"meta.json feature {key} shape mismatch")
if feature.get("dtype") != expected_dtypes[key]:
fail(f"meta.json feature {key} dtype mismatch")
return meta
def check_stats(stats_dir: Path) -> None:
edge = json.loads((stats_dir / "edge_stats.json").read_text(encoding="utf-8"))
node = json.loads((stats_dir / "node_stats.json").read_text(encoding="utf-8"))
for key in ["edge_mean", "edge_std"]:
if not isinstance(edge.get(key), list) or len(edge[key]) != 3:
fail(f"edge_stats.json {key} must be length 3")
for key in ["velocity_mean", "velocity_std", "velocity_diff_mean", "velocity_diff_std"]:
if not isinstance(node.get(key), list) or len(node[key]) != 2:
fail(f"node_stats.json {key} must be length 2")
for key in ["pressure_mean", "pressure_std"]:
if not isinstance(node.get(key), list) or len(node[key]) != 1:
fail(f"node_stats.json {key} must be length 1")
def verify_inventory(dataset_root: Path, sizes: dict, verify_sha256: bool) -> None:
inventory_path = dataset_root / "files_sha256.jsonl"
if not inventory_path.is_file():
fail("missing files_sha256.jsonl")
seen = {}
for line in inventory_path.read_text(encoding="utf-8").splitlines():
if not line.strip():
continue
item = json.loads(line)
rel_path = item["path"]
path = dataset_root / rel_path
if not path.is_file():
fail(f"inventory path missing on disk: {rel_path}")
if path.stat().st_size != item["size"]:
fail(f"size mismatch for {rel_path}")
if rel_path in sizes and sizes[rel_path] != item["size"]:
fail(f"required file size mismatch for {rel_path}")
if verify_sha256 and sha256_file(path) != item["sha256"]:
fail(f"sha256 mismatch for {rel_path}")
seen[rel_path] = item
missing = sorted(EXPECTED_REQUIRED - set(seen))
if missing:
fail(f"inventory missing required files: {missing}")
def check_tfrecord_first_record(data_dir: Path, meta: dict) -> None:
try:
import numpy as np
import tensorflow.compat.v1 as tf
except Exception as exc: # pragma: no cover - optional runtime dependency
print(f"[WARN] TensorFlow first-record check skipped: {exc}")
return
feature_dict = {k: tf.io.VarLenFeature(tf.string) for k in meta["field_names"]}
for split in EXPECTED_SPLITS:
record_iter = iter(tf.data.TFRecordDataset(str(data_dir / f"{split}.tfrecord")).take(1))
try:
raw = next(record_iter)
except StopIteration:
fail(f"{split}.tfrecord contains no records")
features = tf.io.parse_single_example(raw, feature_dict)
velocity = np.frombuffer(features["velocity"].values[0].numpy(), dtype=np.float32)
pressure = np.frombuffer(features["pressure"].values[0].numpy(), dtype=np.float32)
mesh_pos = np.frombuffer(features["mesh_pos"].values[0].numpy(), dtype=np.float32)
cells = np.frombuffer(features["cells"].values[0].numpy(), dtype=np.int32)
if velocity.size % (meta["trajectory_length"] * 2) != 0:
fail(f"{split}.tfrecord velocity shape incompatible with metadata")
nodes = velocity.size // (meta["trajectory_length"] * 2)
if pressure.size != meta["trajectory_length"] * nodes:
fail(f"{split}.tfrecord pressure node count mismatch")
if mesh_pos.size != nodes * 2:
fail(f"{split}.tfrecord mesh_pos node count mismatch")
if cells.size % 3 != 0:
fail(f"{split}.tfrecord cells are not triangular")
print(f"[OK] {split}.tfrecord first record: nodes={nodes}, cells={cells.size // 3}")
def main() -> None:
args = parse_args()
dataset_root = Path(args.dataset_root).resolve()
data_dir = dataset_root / "data" / "cylinder_flow"
sizes = check_files(dataset_root)
meta = check_metadata(data_dir)
check_stats(data_dir / "stats")
verify_inventory(dataset_root, sizes, args.verify_sha256)
if not args.skip_tfrecord_read:
check_tfrecord_first_record(data_dir, meta)
print("[OK] CylinderFlow dataset validation passed")
if __name__ == "__main__":
main()
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