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cli.py
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314 lines (269 loc) · 8.98 KB
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"""Command-line interface for HyperView."""
from __future__ import annotations
import argparse
from hyperview import Dataset, launch
def _build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(
prog="hyperview",
description="HyperView - Dataset visualization with hyperbolic embeddings",
)
parser.add_argument(
"--dataset",
type=str,
default=None,
help=(
"Dataset name in persistent storage. Required unless "
"--dataset-json is provided."
),
)
parser.add_argument(
"--dataset-json",
type=str,
help="Path to exported dataset JSON file (loads samples into memory)",
)
parser.add_argument(
"--hf-dataset",
type=str,
help="HuggingFace dataset ID to ingest before launch (e.g. uoft-cs/cifar10)",
)
parser.add_argument(
"--split",
type=str,
default=None,
help="HuggingFace split to use (required with --hf-dataset)",
)
parser.add_argument(
"--image-key",
type=str,
default=None,
help="Image column key for HuggingFace ingestion (required with --hf-dataset)",
)
parser.add_argument(
"--label-key",
type=str,
default=None,
help="Label column key for HuggingFace ingestion (optional)",
)
parser.add_argument(
"--label-names-key",
type=str,
default=None,
help="Optional dataset info key containing label names",
)
parser.add_argument(
"--images-dir",
type=str,
help="Local directory of images to ingest before launch",
)
parser.add_argument(
"--label-from-folder",
action="store_true",
help="When using --images-dir, derive label from parent folder name",
)
parser.add_argument(
"--samples",
type=int,
default=None,
help="Maximum number of ingested samples (omit to load all)",
)
parser.add_argument(
"--shuffle",
action="store_true",
help="Shuffle HuggingFace dataset before sampling",
)
parser.add_argument(
"--seed",
type=int,
default=42,
help="Random seed used when --shuffle is enabled (default: 42)",
)
parser.add_argument(
"--model",
type=str,
default=None,
help=(
"Embedding model to compute before launch (e.g. openai/clip-vit-base-patch32). "
"If omitted, existing embedding spaces are reused."
),
)
parser.add_argument(
"--method",
choices=["umap"],
default="umap",
help="Projection method (currently only 'umap')",
)
parser.add_argument(
"--geometry",
choices=["auto", "euclidean", "poincare", "both"],
default="both",
help=(
"Layout geometry to compute when embeddings are computed. "
"auto chooses based on embedding geometry; both computes both layouts."
),
)
parser.add_argument(
"--n-neighbors",
type=int,
default=15,
help="UMAP n_neighbors (default: 15)",
)
parser.add_argument(
"--min-dist",
type=float,
default=0.1,
help="UMAP min_dist (default: 0.1)",
)
parser.add_argument(
"--metric",
type=str,
default="cosine",
help="UMAP metric (default: cosine)",
)
parser.add_argument(
"--force-layout",
action="store_true",
help="Force layout recomputation even if projection already exists",
)
parser.add_argument(
"--port",
type=int,
default=6262,
help="Port to run the server on (default: 6262)",
)
parser.add_argument(
"--host",
type=str,
default="127.0.0.1",
help="Host to bind the server to (default: 127.0.0.1)",
)
parser.add_argument(
"--no-browser",
action="store_true",
help="Do not open a browser window automatically",
)
parser.add_argument(
"--reuse-server",
action="store_true",
help=(
"If the port is already serving HyperView, attach instead of failing. "
"For safety, this only attaches when the existing server reports the same dataset name."
),
)
return parser
def _validate_args(parser: argparse.ArgumentParser, args: argparse.Namespace) -> None:
if args.hf_dataset and args.images_dir:
parser.error("Use either --hf-dataset or --images-dir, not both.")
if args.dataset_json and (args.hf_dataset or args.images_dir):
parser.error("--dataset-json cannot be combined with --hf-dataset or --images-dir.")
if args.dataset_json and args.dataset:
parser.error("Use either --dataset or --dataset-json, not both.")
if not args.dataset and not args.dataset_json:
parser.error(
"Provide --dataset (persistent dataset) or --dataset-json (exported dataset file)."
)
if args.hf_dataset:
if not args.split:
parser.error("--split is required when using --hf-dataset.")
if not args.image_key:
parser.error("--image-key is required when using --hf-dataset.")
def _print_ingestion_result(added: int, skipped: int) -> None:
if skipped > 0:
print(f"Loaded {added} samples ({skipped} already present)")
else:
print(f"Loaded {added} samples")
def _ingest_huggingface(dataset: Dataset, args: argparse.Namespace, dataset_name: str) -> None:
print(f"Loading HuggingFace dataset {dataset_name}...")
added, skipped = dataset.add_from_huggingface(
dataset_name,
split=args.split,
image_key=args.image_key,
label_key=args.label_key,
label_names_key=args.label_names_key,
max_samples=args.samples,
shuffle=args.shuffle,
seed=args.seed,
)
_print_ingestion_result(added, skipped)
def _prepare_dataset(args: argparse.Namespace) -> Dataset:
if args.dataset_json:
print(f"Loading dataset from {args.dataset_json}...")
dataset = Dataset.load(args.dataset_json)
print(f"Loaded {len(dataset)} samples")
return dataset
dataset = Dataset(args.dataset)
print(f"Using dataset '{dataset.name}' ({len(dataset)} samples)")
if args.hf_dataset:
_ingest_huggingface(dataset, args, args.hf_dataset)
elif args.images_dir:
print(f"Loading images from {args.images_dir}...")
added, skipped = dataset.add_images_dir(
args.images_dir,
label_from_folder=args.label_from_folder,
)
_print_ingestion_result(added, skipped)
return dataset
def _resolve_geometry_targets(
dataset: Dataset,
geometry: str,
space_key: str | None,
) -> list[str]:
if geometry == "both":
return ["euclidean", "poincare"]
if geometry in ("euclidean", "poincare"):
return [geometry]
if space_key is None:
return ["euclidean"]
spaces = dataset.list_spaces()
selected = next((space for space in spaces if space.space_key == space_key), None)
if selected is not None and selected.geometry == "hyperboloid":
return ["poincare"]
return ["euclidean"]
def _compute_layouts(dataset: Dataset, args: argparse.Namespace, space_key: str | None) -> None:
targets = _resolve_geometry_targets(dataset, args.geometry, space_key)
print("Computing visualizations...")
for target_geometry in targets:
dataset.compute_visualization(
space_key=space_key,
method=args.method,
geometry=target_geometry,
n_neighbors=args.n_neighbors,
min_dist=args.min_dist,
metric=args.metric,
force=args.force_layout,
)
print("Visualizations ready")
def _prepare_embeddings_and_layouts(dataset: Dataset, args: argparse.Namespace) -> None:
has_spaces = len(dataset.list_spaces()) > 0
if args.model is not None:
print(f"Computing embeddings with {args.model}...")
space_key = dataset.compute_embeddings(model=args.model, show_progress=True)
print("Embeddings computed")
_compute_layouts(dataset, args, space_key)
return
if args.force_layout:
if not has_spaces:
raise ValueError(
"No embedding spaces found. Provide --model to compute embeddings first."
)
_compute_layouts(dataset, args, space_key=None)
return
if not has_spaces:
raise ValueError(
"No embedding spaces found. Provide --model to compute embeddings first."
)
def main():
"""Main CLI entry point."""
parser = _build_parser()
args = parser.parse_args()
_validate_args(parser, args)
dataset = _prepare_dataset(args)
_prepare_embeddings_and_layouts(dataset, args)
launch(
dataset,
port=args.port,
host=args.host,
open_browser=not args.no_browser,
reuse_server=args.reuse_server,
)
if __name__ == "__main__":
main()