Coverage for bioimageio/core/cli.py: 83%

1"""bioimageio CLI 

2 

3Note: Some docstrings use a hair space ' ' 

4 to place the added '(default: ...)' on a new line. 

5""" 

6 

7import json 

8import shutil 

9import subprocess 

10import sys 

11from abc import ABC 

12from argparse import RawTextHelpFormatter 

13from difflib import SequenceMatcher 

14from functools import cached_property 

15from io import StringIO 

16from pathlib import Path 

17from pprint import pformat, pprint 

18from typing import ( 

19 Any, 

20 Dict, 

21 Iterable, 

22 List, 

23 Literal, 

24 Mapping, 

25 Optional, 

26 Sequence, 

27 Set, 

28 Tuple, 

29 Type, 

30 Union, 

31) 

32 

33import rich.markdown 

34from loguru import logger 

35from pydantic import AliasChoices, BaseModel, Field, model_validator 

36from pydantic_settings import ( 

37 BaseSettings, 

38 CliPositionalArg, 

39 CliSettingsSource, 

40 CliSubCommand, 

41 JsonConfigSettingsSource, 

42 PydanticBaseSettingsSource, 

43 SettingsConfigDict, 

44 YamlConfigSettingsSource, 

45) 

46from tqdm import tqdm 

47from typing_extensions import assert_never 

48 

49import bioimageio.spec 

50from bioimageio.spec import ( 

51 AnyModelDescr, 

52 InvalidDescr, 

53 ResourceDescr, 

54 load_description, 

55 save_bioimageio_yaml_only, 

56 settings, 

57 update_format, 

58 update_hashes, 

59) 

60from bioimageio.spec._internal.io import is_yaml_value 

61from bioimageio.spec._internal.io_utils import open_bioimageio_yaml 

62from bioimageio.spec._internal.types import FormatVersionPlaceholder, NotEmpty 

63from bioimageio.spec.dataset import DatasetDescr 

64from bioimageio.spec.model import ModelDescr, v0_4, v0_5 

65from bioimageio.spec.notebook import NotebookDescr 

66from bioimageio.spec.utils import ensure_description_is_model, get_reader, write_yaml 

67 

68from .commands import WeightFormatArgAll, WeightFormatArgAny, package, test 

69from .common import MemberId, SampleId, SupportedWeightsFormat 

70from .digest_spec import get_member_ids, load_sample_for_model 

71from .io import load_dataset_stat, save_dataset_stat, save_sample 

72from .prediction import create_prediction_pipeline 

73from .proc_setup import ( 

74 DatasetMeasure, 

75 Measure, 

76 MeasureValue, 

77 StatsCalculator, 

78 get_required_dataset_measures, 

79) 

80from .sample import Sample 

81from .stat_measures import Stat 

82from .utils import VERSION, compare 

83from .weight_converters._add_weights import add_weights 

84 

85WEIGHT_FORMAT_ALIASES = AliasChoices( 

86 "weight-format", 

87 "weights-format", 

88 "weight_format", 

89 "weights_format", 

90) 

91 

92 

93class CmdBase(BaseModel, use_attribute_docstrings=True, cli_implicit_flags=True): 

94 pass 

95 

96 

97class ArgMixin(BaseModel, use_attribute_docstrings=True, cli_implicit_flags=True): 

98 pass 

99 

100 

101class WithSummaryLogging(ArgMixin): 

102 summary: Sequence[Union[Literal["display"], Path]] = Field( 

103 ("display",), 

104 examples=[ 

105 "display", 

106 Path("summary.md"), 

107 Path("bioimageio_summaries/"), 

108 ["display", Path("summary.md")], 

109 ], 

110 ) 

111 """Display the validation summary or save it as JSON, Markdown or HTML. 

112 The format is chosen based on the suffix: `.json`, `.md`, `.html`. 

113 If a folder is given (path w/o suffix) the summary is saved in all formats. 

114 Choose/add `"display"` to render the validation summary to the terminal. 

115 """ 

116 

117 def log(self, descr: Union[ResourceDescr, InvalidDescr]): 

118 _ = descr.validation_summary.log(self.summary) 

119 

120 

121class WithSource(ArgMixin): 

122 source: CliPositionalArg[str] 

123 """Url/path to a (folder with a) bioimageio.yaml/rdf.yaml file 

124 or a bioimage.io resource identifier, e.g. 'affable-shark'""" 

125 

126 @cached_property 

127 def descr(self): 

128 return load_description(self.source) 

129 

130 @property 

131 def descr_id(self) -> str: 

132 """a more user-friendly description id 

133 (replacing legacy ids with their nicknames) 

134 """ 

135 if isinstance(self.descr, InvalidDescr): 

136 return str(getattr(self.descr, "id", getattr(self.descr, "name"))) 

137 

138 nickname = None 

139 if ( 

140 isinstance(self.descr.config, v0_5.Config) 

141 and (bio_config := self.descr.config.bioimageio) 

142 and bio_config.model_extra is not None 

143 ): 

144 nickname = bio_config.model_extra.get("nickname") 

145 

146 return str(nickname or self.descr.id or self.descr.name) 

147 

148 

149class ValidateFormatCmd(CmdBase, WithSource, WithSummaryLogging): 

150 """Validate the meta data format of a bioimageio resource.""" 

151 

152 perform_io_checks: bool = Field( 

153 settings.perform_io_checks, alias="perform-io-checks" 

154 ) 

155 """Wether or not to perform validations that requires downloading remote files. 

156 Note: Default value is set by `BIOIMAGEIO_PERFORM_IO_CHECKS` environment variable. 

157 """ 

158 

159 @cached_property 

160 def descr(self): 

161 return load_description(self.source, perform_io_checks=self.perform_io_checks) 

162 

163 def run(self): 

164 self.log(self.descr) 

165 sys.exit( 

166 0 

167 if self.descr.validation_summary.status in ("valid-format", "passed") 

168 else 1 

169 ) 

170 

171 

172class TestCmd(CmdBase, WithSource, WithSummaryLogging): 

173 """Test a bioimageio resource (beyond meta data formatting).""" 

174 

175 weight_format: WeightFormatArgAll = Field( 

176 "all", 

177 alias="weight-format", 

178 validation_alias=WEIGHT_FORMAT_ALIASES, 

179 ) 

180 """The weight format to limit testing to. 

181 

182 (only relevant for model resources)""" 

183 

184 devices: Optional[Union[str, Sequence[str]]] = None 

185 """Device(s) to use for testing""" 

186 

187 runtime_env: Union[Literal["currently-active", "as-described"], Path] = Field( 

188 "currently-active", alias="runtime-env" 

189 ) 

190 """The python environment to run the tests in 

191 - `"currently-active"`: use active Python interpreter 

192 - `"as-described"`: generate a conda environment YAML file based on the model 

193 weights description. 

194 - A path to a conda environment YAML. 

195 Note: The `bioimageio.core` dependency will be added automatically if not present. 

196 """ 

197 

198 determinism: Literal["seed_only", "full"] = "seed_only" 

199 """Modes to improve reproducibility of test outputs.""" 

200 

201 stop_early: bool = Field( 

202 False, alias="stop-early", validation_alias=AliasChoices("stop-early", "x") 

203 ) 

204 """Do not run further subtests after a failed one.""" 

205 

206 format_version: Union[FormatVersionPlaceholder, str] = Field( 

207 "discover", alias="format-version" 

208 ) 

209 """The format version to use for testing. 

210 - 'latest': Use the latest implemented format version for the given resource type (may trigger auto updating) 

211 - 'discover': Use the format version as described in the resource description 

212 - '0.4', '0.5', ...: Use the specified format version (may trigger auto updating) 

213 """ 

214 

215 def run(self): 

216 sys.exit( 

217 test( 

218 self.descr, 

219 weight_format=self.weight_format, 

220 devices=self.devices, 

221 summary=self.summary, 

222 runtime_env=self.runtime_env, 

223 determinism=self.determinism, 

224 format_version=self.format_version, 

225 ) 

226 ) 

227 

228 

229class PackageCmd(CmdBase, WithSource, WithSummaryLogging): 

230 """Save a resource's metadata with its associated files.""" 

231 

232 path: CliPositionalArg[Path] 

233 """The path to write the (zipped) package to. 

234 If it does not have a `.zip` suffix 

235 this command will save the package as an unzipped folder instead.""" 

236 

237 weight_format: WeightFormatArgAll = Field( 

238 "all", 

239 alias="weight-format", 

240 validation_alias=WEIGHT_FORMAT_ALIASES, 

241 ) 

242 """The weight format to include in the package (for model descriptions only).""" 

243 

244 def run(self): 

245 if isinstance(self.descr, InvalidDescr): 

246 self.log(self.descr) 

247 raise ValueError(f"Invalid {self.descr.type} description.") 

248 

249 sys.exit( 

250 package( 

251 self.descr, 

252 self.path, 

253 weight_format=self.weight_format, 

254 ) 

255 ) 

256 

257 

258def _get_stat( 

259 model_descr: AnyModelDescr, 

260 dataset: Iterable[Sample], 

261 dataset_length: int, 

262 stats_path: Path, 

263) -> Mapping[DatasetMeasure, MeasureValue]: 

264 req_dataset_meas, _ = get_required_dataset_measures(model_descr) 

265 if not req_dataset_meas: 

266 return {} 

267 

268 req_dataset_meas, _ = get_required_dataset_measures(model_descr) 

269 

270 if stats_path.exists(): 

271 logger.info("loading precomputed dataset measures from {}", stats_path) 

272 stat = load_dataset_stat(stats_path) 

273 for m in req_dataset_meas: 

274 if m not in stat: 

275 raise ValueError(f"Missing {m} in {stats_path}") 

276 

277 return stat 

278 

279 stats_calc = StatsCalculator(req_dataset_meas) 

280 

281 for sample in tqdm( 

282 dataset, total=dataset_length, desc="precomputing dataset stats", unit="sample" 

283 ): 

284 stats_calc.update(sample) 

285 

286 stat = stats_calc.finalize() 

287 save_dataset_stat(stat, stats_path) 

288 

289 return stat 

290 

291 

292class UpdateCmdBase(CmdBase, WithSource, ABC): 

293 output: Union[Literal["display", "stdout"], Path] = "display" 

294 """Output updated bioimageio.yaml to the terminal or write to a file. 

295 Notes: 

296 - `"display"`: Render to the terminal with syntax highlighting. 

297 - `"stdout"`: Write to sys.stdout without syntax highligthing. 

298 (More convenient for copying the updated bioimageio.yaml from the terminal.) 

299 """ 

300 

301 diff: Union[bool, Path] = Field(True, alias="diff") 

302 """Output a diff of original and updated bioimageio.yaml. 

303 If a given path has an `.html` extension, a standalone HTML file is written, 

304 otherwise the diff is saved in unified diff format (pure text). 

305 """ 

306 

307 exclude_unset: bool = Field(True, alias="exclude-unset") 

308 """Exclude fields that have not explicitly be set.""" 

309 

310 exclude_defaults: bool = Field(False, alias="exclude-defaults") 

311 """Exclude fields that have the default value (even if set explicitly).""" 

312 

313 @cached_property 

314 def updated(self) -> Union[ResourceDescr, InvalidDescr]: 

315 raise NotImplementedError 

316 

317 def run(self): 

318 original_yaml = open_bioimageio_yaml(self.source).unparsed_content 

319 assert isinstance(original_yaml, str) 

320 stream = StringIO() 

321 

322 save_bioimageio_yaml_only( 

323 self.updated, 

324 stream, 

325 exclude_unset=self.exclude_unset, 

326 exclude_defaults=self.exclude_defaults, 

327 ) 

328 updated_yaml = stream.getvalue() 

329 

330 diff = compare( 

331 original_yaml.split("\n"), 

332 updated_yaml.split("\n"), 

333 diff_format=( 

334 "html" 

335 if isinstance(self.diff, Path) and self.diff.suffix == ".html" 

336 else "unified" 

337 ), 

338 ) 

339 

340 if isinstance(self.diff, Path): 

341 _ = self.diff.write_text(diff, encoding="utf-8") 

342 elif self.diff: 

343 console = rich.console.Console() 

344 diff_md = f"## Diff\n\n````````diff\n{diff}\n````````" 

345 console.print(rich.markdown.Markdown(diff_md)) 

346 

347 if isinstance(self.output, Path): 

348 _ = self.output.write_text(updated_yaml, encoding="utf-8") 

349 logger.info(f"written updated description to {self.output}") 

350 elif self.output == "display": 

351 updated_md = f"## Updated bioimageio.yaml\n\n```yaml\n{updated_yaml}\n```" 

352 rich.console.Console().print(rich.markdown.Markdown(updated_md)) 

353 elif self.output == "stdout": 

354 print(updated_yaml) 

355 else: 

356 assert_never(self.output) 

357 

358 if isinstance(self.updated, InvalidDescr): 

359 logger.warning("Update resulted in invalid description") 

360 _ = self.updated.validation_summary.display() 

361 

362 

363class UpdateFormatCmd(UpdateCmdBase): 

364 """Update the metadata format to the latest format version.""" 

365 

366 exclude_defaults: bool = Field(True, alias="exclude-defaults") 

367 """Exclude fields that have the default value (even if set explicitly). 

368 

369 Note: 

370 The update process sets most unset fields explicitly with their default value. 

371 """ 

372 

373 perform_io_checks: bool = Field( 

374 settings.perform_io_checks, alias="perform-io-checks" 

375 ) 

376 """Wether or not to attempt validation that may require file download. 

377 If `True` file hash values are added if not present.""" 

378 

379 @cached_property 

380 def updated(self): 

381 return update_format( 

382 self.source, 

383 exclude_defaults=self.exclude_defaults, 

384 perform_io_checks=self.perform_io_checks, 

385 ) 

386 

387 

388class UpdateHashesCmd(UpdateCmdBase): 

389 """Create a bioimageio.yaml description with updated file hashes.""" 

390 

391 @cached_property 

392 def updated(self): 

393 return update_hashes(self.source) 

394 

395 

396class PredictCmd(CmdBase, WithSource): 

397 """Run inference on your data with a bioimage.io model.""" 

398 

399 inputs: NotEmpty[Sequence[Union[str, NotEmpty[Tuple[str, ...]]]]] = ( 

400 "{input_id}/001.tif", 

401 ) 

402 """Model input sample paths (for each input tensor) 

403 

404 The input paths are expected to have shape... 

405 - (n_samples,) or (n_samples,1) for models expecting a single input tensor 

406 - (n_samples,) containing the substring '{input_id}', or 

407 - (n_samples, n_model_inputs) to provide each input tensor path explicitly. 

408 

409 All substrings that are replaced by metadata from the model description: 

410 - '{model_id}' 

411 - '{input_id}' 

412 

413 Example inputs to process sample 'a' and 'b' 

414 for a model expecting a 'raw' and a 'mask' input tensor: 

415 --inputs="[[\\"a_raw.tif\\",\\"a_mask.tif\\"],[\\"b_raw.tif\\",\\"b_mask.tif\\"]]" 

416 (Note that JSON double quotes need to be escaped.) 

417 

418 Alternatively a `bioimageio-cli.yaml` (or `bioimageio-cli.json`) file 

419 may provide the arguments, e.g.: 

420 ```yaml 

421 inputs: 

422 - [a_raw.tif, a_mask.tif] 

423 - [b_raw.tif, b_mask.tif] 

424 ``` 

425 

426 `.npy` and any file extension supported by imageio are supported. 

427 Aavailable formats are listed at 

428 https://imageio.readthedocs.io/en/stable/formats/index.html#all-formats. 

429 Some formats have additional dependencies. 

430 

431   

432 """ 

433 

434 outputs: Union[str, NotEmpty[Tuple[str, ...]]] = ( 

435 "outputs_{model_id}/{output_id}/{sample_id}.tif" 

436 ) 

437 """Model output path pattern (per output tensor) 

438 

439 All substrings that are replaced: 

440 - '{model_id}' (from model description) 

441 - '{output_id}' (from model description) 

442 - '{sample_id}' (extracted from input paths) 

443 

444   

445 """ 

446 

447 overwrite: bool = False 

448 """allow overwriting existing output files""" 

449 

450 blockwise: bool = False 

451 """process inputs blockwise""" 

452 

453 stats: Path = Path("dataset_statistics.json") 

454 """path to dataset statistics 

455 (will be written if it does not exist, 

456 but the model requires statistical dataset measures) 

457  """ 

458 

459 preview: bool = False 

460 """preview which files would be processed 

461 and what outputs would be generated.""" 

462 

463 weight_format: WeightFormatArgAny = Field( 

464 "any", 

465 alias="weight-format", 

466 validation_alias=WEIGHT_FORMAT_ALIASES, 

467 ) 

468 """The weight format to use.""" 

469 

470 example: bool = False 

471 """generate and run an example 

472 

473 1. downloads example model inputs 

474 2. creates a `{model_id}_example` folder 

475 3. writes input arguments to `{model_id}_example/bioimageio-cli.yaml` 

476 4. executes a preview dry-run 

477 5. executes prediction with example input 

478 

479   

480 """ 

481 

482 def _example(self): 

483 model_descr = ensure_description_is_model(self.descr) 

484 input_ids = get_member_ids(model_descr.inputs) 

485 example_inputs = ( 

486 model_descr.sample_inputs 

487 if isinstance(model_descr, v0_4.ModelDescr) 

488 else [ipt.sample_tensor or ipt.test_tensor for ipt in model_descr.inputs] 

489 ) 

490 if not example_inputs: 

491 raise ValueError(f"{self.descr_id} does not specify any example inputs.") 

492 

493 inputs001: List[str] = [] 

494 example_path = Path(f"{self.descr_id}_example") 

495 example_path.mkdir(exist_ok=True) 

496 

497 for t, src in zip(input_ids, example_inputs): 

498 reader = get_reader(src) 

499 dst = Path(f"{example_path}/{t}/001{reader.suffix}") 

500 dst.parent.mkdir(parents=True, exist_ok=True) 

501 inputs001.append(dst.as_posix()) 

502 with dst.open("wb") as f: 

503 shutil.copyfileobj(reader, f) 

504 

505 inputs = [inputs001] 

506 output_pattern = f"{example_path}/outputs/{{output_id}}/{{sample_id}}.tif" 

507 

508 bioimageio_cli_path = example_path / YAML_FILE 

509 stats_file = "dataset_statistics.json" 

510 stats = (example_path / stats_file).as_posix() 

511 cli_example_args = dict( 

512 inputs=inputs, 

513 outputs=output_pattern, 

514 stats=stats_file, 

515 blockwise=self.blockwise, 

516 ) 

517 assert is_yaml_value(cli_example_args), cli_example_args 

518 write_yaml( 

519 cli_example_args, 

520 bioimageio_cli_path, 

521 ) 

522 

523 yaml_file_content = None 

524 

525 # escaped double quotes 

526 inputs_json = json.dumps(inputs) 

527 inputs_escaped = inputs_json.replace('"', r"\"") 

528 source_escaped = self.source.replace('"', r"\"") 

529 

530 def get_example_command(preview: bool, escape: bool = False): 

531 q: str = '"' if escape else "" 

532 

533 return [ 

534 "bioimageio", 

535 "predict", 

536 # --no-preview not supported for py=3.8 

537 *(["--preview"] if preview else []), 

538 "--overwrite", 

539 *(["--blockwise"] if self.blockwise else []), 

540 f"--stats={q}{stats}{q}", 

541 f"--inputs={q}{inputs_escaped if escape else inputs_json}{q}", 

542 f"--outputs={q}{output_pattern}{q}", 

543 f"{q}{source_escaped if escape else self.source}{q}", 

544 ] 

545 

546 if Path(YAML_FILE).exists(): 

547 logger.info( 

548 "temporarily removing '{}' to execute example prediction", YAML_FILE 

549 ) 

550 yaml_file_content = Path(YAML_FILE).read_bytes() 

551 Path(YAML_FILE).unlink() 

552 

553 try: 

554 _ = subprocess.run(get_example_command(True), check=True) 

555 _ = subprocess.run(get_example_command(False), check=True) 

556 finally: 

557 if yaml_file_content is not None: 

558 _ = Path(YAML_FILE).write_bytes(yaml_file_content) 

559 logger.debug("restored '{}'", YAML_FILE) 

560 

561 print( 

562 "🎉 Sucessfully ran example prediction!\n" 

563 + "To predict the example input using the CLI example config file" 

564 + f" {example_path/YAML_FILE}, execute `bioimageio predict` from {example_path}:\n" 

565 + f"$ cd {str(example_path)}\n" 

566 + f'$ bioimageio predict "{source_escaped}"\n\n' 

567 + "Alternatively run the following command" 

568 + " in the current workind directory, not the example folder:\n$ " 

569 + " ".join(get_example_command(False, escape=True)) 

570 + f"\n(note that a local '{JSON_FILE}' or '{YAML_FILE}' may interfere with this)" 

571 ) 

572 

573 def run(self): 

574 if self.example: 

575 return self._example() 

576 

577 model_descr = ensure_description_is_model(self.descr) 

578 

579 input_ids = get_member_ids(model_descr.inputs) 

580 output_ids = get_member_ids(model_descr.outputs) 

581 

582 minimum_input_ids = tuple( 

583 str(ipt.id) if isinstance(ipt, v0_5.InputTensorDescr) else str(ipt.name) 

584 for ipt in model_descr.inputs 

585 if not isinstance(ipt, v0_5.InputTensorDescr) or not ipt.optional 

586 ) 

587 maximum_input_ids = tuple( 

588 str(ipt.id) if isinstance(ipt, v0_5.InputTensorDescr) else str(ipt.name) 

589 for ipt in model_descr.inputs 

590 ) 

591 

592 def expand_inputs(i: int, ipt: Union[str, Tuple[str, ...]]) -> Tuple[str, ...]: 

593 if isinstance(ipt, str): 

594 ipts = tuple( 

595 ipt.format(model_id=self.descr_id, input_id=t) for t in input_ids 

596 ) 

597 else: 

598 ipts = tuple( 

599 p.format(model_id=self.descr_id, input_id=t) 

600 for t, p in zip(input_ids, ipt) 

601 ) 

602 

603 if len(set(ipts)) < len(ipts): 

604 if len(minimum_input_ids) == len(maximum_input_ids): 

605 n = len(minimum_input_ids) 

606 else: 

607 n = f"{len(minimum_input_ids)}-{len(maximum_input_ids)}" 

608 

609 raise ValueError( 

610 f"[input sample #{i}] Include '{{input_id}}' in path pattern or explicitly specify {n} distinct input paths (got {ipt})" 

611 ) 

612 

613 if len(ipts) < len(minimum_input_ids): 

614 raise ValueError( 

615 f"[input sample #{i}] Expected at least {len(minimum_input_ids)} inputs {minimum_input_ids}, got {ipts}" 

616 ) 

617 

618 if len(ipts) > len(maximum_input_ids): 

619 raise ValueError( 

620 f"Expected at most {len(maximum_input_ids)} inputs {maximum_input_ids}, got {ipts}" 

621 ) 

622 

623 return ipts 

624 

625 inputs = [expand_inputs(i, ipt) for i, ipt in enumerate(self.inputs, start=1)] 

626 

627 sample_paths_in = [ 

628 {t: Path(p) for t, p in zip(input_ids, ipts)} for ipts in inputs 

629 ] 

630 

631 sample_ids = _get_sample_ids(sample_paths_in) 

632 

633 def expand_outputs(): 

634 if isinstance(self.outputs, str): 

635 outputs = [ 

636 tuple( 

637 Path( 

638 self.outputs.format( 

639 model_id=self.descr_id, output_id=t, sample_id=s 

640 ) 

641 ) 

642 for t in output_ids 

643 ) 

644 for s in sample_ids 

645 ] 

646 else: 

647 outputs = [ 

648 tuple( 

649 Path(p.format(model_id=self.descr_id, output_id=t, sample_id=s)) 

650 for t, p in zip(output_ids, self.outputs) 

651 ) 

652 for s in sample_ids 

653 ] 

654 

655 for i, out in enumerate(outputs, start=1): 

656 if len(set(out)) < len(out): 

657 raise ValueError( 

658 f"[output sample #{i}] Include '{{output_id}}' in path pattern or explicitly specify {len(output_ids)} distinct output paths (got {out})" 

659 ) 

660 

661 if len(out) != len(output_ids): 

662 raise ValueError( 

663 f"[output sample #{i}] Expected {len(output_ids)} outputs {output_ids}, got {out}" 

664 ) 

665 

666 return outputs 

667 

668 outputs = expand_outputs() 

669 

670 sample_paths_out = [ 

671 {MemberId(t): Path(p) for t, p in zip(output_ids, out)} for out in outputs 

672 ] 

673 

674 if not self.overwrite: 

675 for sample_paths in sample_paths_out: 

676 for p in sample_paths.values(): 

677 if p.exists(): 

678 raise FileExistsError( 

679 f"{p} already exists. use --overwrite to (re-)write outputs anyway." 

680 ) 

681 if self.preview: 

682 print("🛈 bioimageio prediction preview structure:") 

683 pprint( 

684 { 

685 "{sample_id}": dict( 

686 inputs={"{input_id}": "<input path>"}, 

687 outputs={"{output_id}": "<output path>"}, 

688 ) 

689 } 

690 ) 

691 print("🔎 bioimageio prediction preview output:") 

692 pprint( 

693 { 

694 s: dict( 

695 inputs={t: p.as_posix() for t, p in sp_in.items()}, 

696 outputs={t: p.as_posix() for t, p in sp_out.items()}, 

697 ) 

698 for s, sp_in, sp_out in zip( 

699 sample_ids, sample_paths_in, sample_paths_out 

700 ) 

701 } 

702 ) 

703 return 

704 

705 def input_dataset(stat: Stat): 

706 for s, sp_in in zip(sample_ids, sample_paths_in): 

707 yield load_sample_for_model( 

708 model=model_descr, 

709 paths=sp_in, 

710 stat=stat, 

711 sample_id=s, 

712 ) 

713 

714 stat: Dict[Measure, MeasureValue] = dict( 

715 _get_stat( 

716 model_descr, input_dataset({}), len(sample_ids), self.stats 

717 ).items() 

718 ) 

719 

720 pp = create_prediction_pipeline( 

721 model_descr, 

722 weight_format=None if self.weight_format == "any" else self.weight_format, 

723 ) 

724 predict_method = ( 

725 pp.predict_sample_with_blocking 

726 if self.blockwise 

727 else pp.predict_sample_without_blocking 

728 ) 

729 

730 for sample_in, sp_out in tqdm( 

731 zip(input_dataset(dict(stat)), sample_paths_out), 

732 total=len(inputs), 

733 desc=f"predict with {self.descr_id}", 

734 unit="sample", 

735 ): 

736 sample_out = predict_method(sample_in) 

737 save_sample(sp_out, sample_out) 

738 

739 

740class AddWeightsCmd(CmdBase, WithSource, WithSummaryLogging): 

741 output: CliPositionalArg[Path] 

742 """The path to write the updated model package to.""" 

743 

744 source_format: Optional[SupportedWeightsFormat] = Field(None, alias="source-format") 

745 """Exclusively use these weights to convert to other formats.""" 

746 

747 target_format: Optional[SupportedWeightsFormat] = Field(None, alias="target-format") 

748 """Exclusively add this weight format.""" 

749 

750 verbose: bool = False 

751 """Log more (error) output.""" 

752 

753 def run(self): 

754 model_descr = ensure_description_is_model(self.descr) 

755 if isinstance(model_descr, v0_4.ModelDescr): 

756 raise TypeError( 

757 f"model format {model_descr.format_version} not supported." 

758 + " Please update the model first." 

759 ) 

760 updated_model_descr = add_weights( 

761 model_descr, 

762 output_path=self.output, 

763 source_format=self.source_format, 

764 target_format=self.target_format, 

765 verbose=self.verbose, 

766 ) 

767 if updated_model_descr is None: 

768 return 

769 

770 self.log(updated_model_descr) 

771 

772 

773JSON_FILE = "bioimageio-cli.json" 

774YAML_FILE = "bioimageio-cli.yaml" 

775 

776 

777class Bioimageio( 

778 BaseSettings, 

779 cli_implicit_flags=True, 

780 cli_parse_args=True, 

781 cli_prog_name="bioimageio", 

782 cli_use_class_docs_for_groups=True, 

783 use_attribute_docstrings=True, 

784): 

785 """bioimageio - CLI for bioimage.io resources 🦒""" 

786 

787 model_config = SettingsConfigDict( 

788 json_file=JSON_FILE, 

789 yaml_file=YAML_FILE, 

790 ) 

791 

792 validate_format: CliSubCommand[ValidateFormatCmd] = Field(alias="validate-format") 

793 "Check a resource's metadata format" 

794 

795 test: CliSubCommand[TestCmd] 

796 "Test a bioimageio resource (beyond meta data formatting)" 

797 

798 package: CliSubCommand[PackageCmd] 

799 "Package a resource" 

800 

801 predict: CliSubCommand[PredictCmd] 

802 "Predict with a model resource" 

803 

804 update_format: CliSubCommand[UpdateFormatCmd] = Field(alias="update-format") 

805 """Update the metadata format""" 

806 

807 update_hashes: CliSubCommand[UpdateHashesCmd] = Field(alias="update-hashes") 

808 """Create a bioimageio.yaml description with updated file hashes.""" 

809 

810 add_weights: CliSubCommand[AddWeightsCmd] = Field(alias="add-weights") 

811 """Add additional weights to the model descriptions converted from available 

812 formats to improve deployability.""" 

813 

814 @classmethod 

815 def settings_customise_sources( 

816 cls, 

817 settings_cls: Type[BaseSettings], 

818 init_settings: PydanticBaseSettingsSource, 

819 env_settings: PydanticBaseSettingsSource, 

820 dotenv_settings: PydanticBaseSettingsSource, 

821 file_secret_settings: PydanticBaseSettingsSource, 

822 ) -> Tuple[PydanticBaseSettingsSource, ...]: 

823 cli: CliSettingsSource[BaseSettings] = CliSettingsSource( 

824 settings_cls, 

825 cli_parse_args=True, 

826 formatter_class=RawTextHelpFormatter, 

827 ) 

828 sys_args = pformat(sys.argv) 

829 logger.info("starting CLI with arguments:\n{}", sys_args) 

830 return ( 

831 cli, 

832 init_settings, 

833 YamlConfigSettingsSource(settings_cls), 

834 JsonConfigSettingsSource(settings_cls), 

835 ) 

836 

837 @model_validator(mode="before") 

838 @classmethod 

839 def _log(cls, data: Any): 

840 logger.info( 

841 "loaded CLI input:\n{}", 

842 pformat({k: v for k, v in data.items() if v is not None}), 

843 ) 

844 return data 

845 

846 def run(self): 

847 logger.info( 

848 "executing CLI command:\n{}", 

849 pformat({k: v for k, v in self.model_dump().items() if v is not None}), 

850 ) 

851 cmd = ( 

852 self.add_weights 

853 or self.package 

854 or self.predict 

855 or self.test 

856 or self.update_format 

857 or self.update_hashes 

858 or self.validate_format 

859 ) 

860 assert cmd is not None 

861 cmd.run() 

862 

863 

864assert isinstance(Bioimageio.__doc__, str) 

865Bioimageio.__doc__ += f""" 

866 

867library versions: 

868 bioimageio.core {VERSION} 

869 bioimageio.spec {bioimageio.spec.__version__} 

870 

871spec format versions: 

872 model RDF {ModelDescr.implemented_format_version} 

873 dataset RDF {DatasetDescr.implemented_format_version} 

874 notebook RDF {NotebookDescr.implemented_format_version} 

875 

876""" 

877 

878 

879def _get_sample_ids( 

880 input_paths: Sequence[Mapping[MemberId, Path]], 

881) -> Sequence[SampleId]: 

882 """Get sample ids for given input paths, based on the common path per sample. 

883 

884 Falls back to sample01, samle02, etc...""" 

885 

886 matcher = SequenceMatcher() 

887 

888 def get_common_seq(seqs: Sequence[Sequence[str]]) -> Sequence[str]: 

889 """extract a common sequence from multiple sequences 

890 (order sensitive; strips whitespace and slashes) 

891 """ 

892 common = seqs[0] 

893 

894 for seq in seqs[1:]: 

895 if not seq: 

896 continue 

897 matcher.set_seqs(common, seq)