diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index c6f0123..7031488 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -3,8 +3,10 @@ name: CI on: push: branches: - - main - pull_request: {} + - master + pull_request: + branches: + - '*' jobs: tests: @@ -23,20 +25,17 @@ jobs: steps: - uses: actions/checkout@v4 - - name: Install poetry - run: pipx install poetry - - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v5 + - name: Install the latest version of uv + uses: astral-sh/setup-uv@v6 with: + enable-cache: true python-version: ${{ matrix.python-version }} - cache: poetry - name: Install dependencies - run: poetry install + run: uv sync --all-extras - name: Lint with pysen run: make lint - name: Test with pytest - run: make test + run: make test diff --git a/.github/workflows/pypi-publish.yml b/.github/workflows/pypi-publish.yml index d84c543..53f00b4 100644 --- a/.github/workflows/pypi-publish.yml +++ b/.github/workflows/pypi-publish.yml @@ -1,4 +1,4 @@ -name: deploy +name: publish on: release: @@ -11,7 +11,9 @@ jobs: if: github.event_name == 'release' steps: - uses: actions/checkout@v4 + + - name: Install the latest version of uv + uses: astral-sh/setup-uv@v6 + - name: Build and publish to pypi - uses: JRubics/poetry-publish@v2.1 - with: - pypi_token: ${{ secrets.PYPI_TOKEN }} + run: uv build && uv publish --token ${{ secrets.PYPI_TOKEN }} diff --git a/Makefile b/Makefile index 19b73e0..b58e2ec 100644 --- a/Makefile +++ b/Makefile @@ -1,7 +1,8 @@ PWD := $(shell pwd) -PYTHON := poetry run python -PYTEST := poetry run pytest -PYSEN := poetry run pysen +PYTHON := uv run python +PYTEST := uv run pytest +PYRIGHT := uv run pyright +RUFF := uv run ruff MODULE := collatable .PHONY: all @@ -13,11 +14,13 @@ test: .PHONY: lint lint: - PYTHONPATH=$(PWD) $(PYSEN) run lint + PYTHONPATH=$(PWD) $(RUFF) check + PYTHONPATH=$(PWD) $(PYRIGHT) .PHONY: format format: - PYTHONPATH=$(PWD) $(PYSEN) run format + PYTHONPATH=$(PWD) $(RUFF) check --select I --fix + PYTHONPATH=$(PWD) $(RUFF) format .PHONY: clean clean: clean-pyc clean-build diff --git a/collatable/extras/__init__.py b/collatable/extras/__init__.py deleted file mode 100644 index 4750f3f..0000000 --- a/collatable/extras/__init__.py +++ /dev/null @@ -1,10 +0,0 @@ -from collatable.extras.dataloader import DataLoader, DefaultBatchSampler # noqa: F401 -from collatable.extras.datamodule import ( # noqa: F401 - DataModule, - FieldConfig, - FieldTransform, - LabelFieldTransform, - TextFieldTransform, -) -from collatable.extras.dataset import Dataset # noqa: F401 -from collatable.extras.indexer import Indexer, LabelIndexer, TokenIndexer # noqa: F401 diff --git a/collatable/fields/__init__.py b/collatable/fields/__init__.py deleted file mode 100644 index 3f1e717..0000000 --- a/collatable/fields/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -from collatable.fields.adjacency_field import AdjacencyField # noqa: F401 -from collatable.fields.field import Field # noqa: F401 -from collatable.fields.index_field import IndexField # noqa: F401 -from collatable.fields.label_field import LabelField # noqa: F401 -from collatable.fields.list_field import ListField # noqa: F401 -from collatable.fields.mapping_field import MappingField # noqa: F401 -from collatable.fields.metadata_field import MetadataField # noqa: F401 -from collatable.fields.scalar_field import ScalarField # noqa: F401 -from collatable.fields.sequence_field import SequenceField # noqa: F401 -from collatable.fields.sequence_label_field import SequenceLabelField # noqa: F401 -from collatable.fields.span_field import SpanField # noqa: F401 -from collatable.fields.tensor_field import TensorField # noqa: F401 -from collatable.fields.text_field import TextField # noqa: F401 diff --git a/collatable/fields/mapping_field.py b/collatable/fields/mapping_field.py deleted file mode 100644 index f87d306..0000000 --- a/collatable/fields/mapping_field.py +++ /dev/null @@ -1,49 +0,0 @@ -from typing import Any, Dict, Iterator, Mapping, Sequence, Tuple, Type - -from collatable.fields.field import Field -from collatable.types import DataArray - - -class MappingField(Field[Dict[str, Any]], Mapping[str, Field]): - def __init__(self, mapping: Mapping[str, Field]) -> None: - super().__init__() - self._mapping = mapping - - def __len__(self) -> int: - return len(self._mapping) - - def __iter__(self) -> Iterator[str]: - return iter(self._mapping) - - def __getitem__(self, key: str) -> Field: - return self._mapping[key] - - def __contains__(self, key: object) -> bool: - return key in self._mapping - - def __str__(self) -> str: - return str(self._mapping) - - def __repr__(self) -> str: - return f"MappingField({self._mapping})" - - def as_array(self) -> Dict[str, Any]: - return {key: field.as_array() for key, field in self._mapping.items()} - - @classmethod - def from_array( # type: ignore[override] - cls, - array: Mapping[str, DataArray], - *, - fields: Mapping[str, Tuple[Type[Field], Mapping[str, Any]]], - ) -> "MappingField": - return cls({key: field.from_array(array[key], **params) for key, (field, params) in fields.items()}) - 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library." -optional = false -python-versions = "*" -files = [ - {file = "unidiff-0.7.5-py2.py3-none-any.whl", hash = "sha256:c93bf2265cc1ba2a520e415ab05da587370bc2a3ae9e0414329f54f0c2fc09e8"}, - {file = "unidiff-0.7.5.tar.gz", hash = "sha256:2e5f0162052248946b9f0970a40e9e124236bf86c82b70821143a6fc1dea2574"}, -] - -[metadata] -lock-version = "2.0" -python-versions = ">=3.8,<4.0" -content-hash = "0183128a83748aa50d29c29953bd38256b38b6cefdaee6a4d9860c9aff74d772" diff --git a/pyproject.toml b/pyproject.toml index beeff68..d38b824 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,78 +1,30 @@ -[tool.poetry] +[project] name = "collatable" version = "0.5.0" description = "Constructing batched tensors for any machine learning tasks" -authors = ["altescy "] -license = "MIT License" +authors = [ + {name="altescy", email="me@altescy.jp"}, +] +license = "MIT" readme = "README.md" -homepage = "https://github.com/altescy/collatable" keywords = ["python", "machine learning"] -packages = [ - { include = "collatable" }, -] - -[tool.poetry.dependencies] -python = ">=3.8,<4.0" -numpy = [ - {version=">=1.26.4", python=">=3.9,<4.0"}, - {version=">=1.0.0,<1.26.4", python=">=3.8,<3.9"}, +requires-python = ">=3.8,<4.0" +dependencies = [ + "numpy>=1.0.0,<1.26.4; python_version < '3.9'", + "numpy>=1.26.4; python_version >= '3.9'", ] -[tool.poetry.group.dev.dependencies] -pytest = "^8.3.3" -pysen = "^0.11.0" -black = "^24.8.0" -isort = "^5.13.2" -flake8 = "^5.0.4" -mypy = "^1.11.2" - -[tool.poetry.group.lsp] -optional = true - -[tool.poetry.group.lsp.dependencies] -python-lsp-server = { version="^1.0.0", extras=["flake8"] } -pylsp-mypy = "^0.6.9" -python-lsp-isort = "^0.2.0" -python-lsp-black = "^2.0.0" - -[tool.pysen] -version = "0.11" +[project.urls] +Homepage = "https://github.com/altescy/collatable" +Issues = "https://github.com/altescy/collatable/issues" -[tool.pysen-cli] -settings_dir = "." - -[tool.pysen.lint] -enable_black = true -enable_flake8 = true -enable_isort = true -enable_mypy = true -mypy_preset = "strict" -line_length = 120 -py_version = "py38" - -[[tool.pysen.lint.mypy_targets]] - paths = ["."] - -[tool.pysen.lint.source] - includes = ["."] - excludes = [".venv/"] - - -[tool.black] # automatically generated by pysen -# pysen ignores and overwrites any modifications -line-length = 120 -target-version = ["py38"] +[dependency-groups] +dev = [ + "pyright>=1.1.394", + "pytest>=8.3.4", + "ruff>=0.9.6", +] -[tool.isort] # automatically generated by pysen -# pysen ignores and overwrites any modifications -default_section = "THIRDPARTY" -ensure_newline_before_comments = true -force_grid_wrap = 0 -force_single_line = false -include_trailing_comma = true -line_length = 120 -multi_line_output = 3 -use_parentheses = true [build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" +requires = ["uv_build>=0.7.19,<0.9.0"] +build-backend = "uv_build" diff --git a/setup.cfg b/setup.cfg deleted file mode 100644 index 84fc9e9..0000000 --- a/setup.cfg +++ /dev/null @@ -1,38 +0,0 @@ -[flake8] -# automatically generated by pysen -# pysen ignores and overwrites any modifications -# e203: black treats : as a binary operator -# e231: black doesn't put a space after , -# e501: black may exceed the line-length to follow other style rules -# e701: black will collapse ... only functions etc. to a single line -# e704: black will collapse ... only functions etc. to a single line -# w503 or w504: either one needs to be disabled to select w error codes -ignore = E203,E231,E501,E701,E704,W503 -max-line-length = 120 -select = B,B950,C,E,F,W - -[mypy] -# automatically generated by pysen -# pysen ignores and overwrites any modifications -check_untyped_defs = True -disallow_any_decorated = False -disallow_any_generics = False -disallow_any_unimported = False -disallow_incomplete_defs = True -disallow_subclassing_any = True -disallow_untyped_calls = True -disallow_untyped_decorators = False -disallow_untyped_defs = True -ignore_errors = False -ignore_missing_imports = True -no_implicit_optional = True -python_version = 3.8 -show_error_codes = True -strict_equality = True -strict_optional = True -warn_redundant_casts = True -warn_return_any = True -warn_unreachable = True -warn_unused_configs = True -warn_unused_ignores = False - diff --git a/collatable/__init__.py b/src/collatable/__init__.py similarity index 79% rename from collatable/__init__.py rename to src/collatable/__init__.py index b7b0c6f..50ae8a0 100644 --- a/collatable/__init__.py +++ b/src/collatable/__init__.py @@ -1,7 +1,7 @@ from importlib.metadata import version -from collatable.collator import Collator, collate # noqa: F401 -from collatable.fields import ( # noqa: F401 +from collatable.collator import Collator, collate +from collatable.fields import ( AdjacencyField, Field, IndexField, @@ -24,8 +24,10 @@ "IndexField", "LabelField", "ListField", + "MetadataField", "ScalarField", "SequenceField", + "SequenceLabelField", "SpanField", "TensorField", "TextField", diff --git a/collatable/collator.py b/src/collatable/collator.py similarity index 76% rename from collatable/collator.py rename to src/collatable/collator.py index 7b1af10..937e2bf 100644 --- a/collatable/collator.py +++ b/src/collatable/collator.py @@ -16,18 +16,26 @@ def _extract_fields(self, instance: Any) -> Mapping[str, Field]: getattr( instance, "__slots__", - [key for key in members if not key.startswith("_") or key in (self._field_names or [])], + [ + key + for key in members + if not key.startswith("_") + or key in (self._field_names or []) + ], ) ) if self._field_names is not None and not (self._field_names <= slots): - raise ValueError(f"Field names {self._field_names - slots} not found") + raise ValueError( + f"Field names {self._field_names - slots} not found" + ) instance = {slot: members[slot] for slot in slots if slot in members} elif isinstance(instance, INamedTuple): instance = instance._asdict() return { key: value for key, value in instance.items() - if isinstance(value, Field) and (self._field_names is None or key in self._field_names) + if isinstance(value, Field) + and (self._field_names is None or key in self._field_names) } def __call__(self, instances: Sequence[Any]) -> Dict[str, DataArray]: diff --git a/src/collatable/extras/__init__.py b/src/collatable/extras/__init__.py new file mode 100644 index 0000000..ea5fa88 --- /dev/null +++ b/src/collatable/extras/__init__.py @@ -0,0 +1,24 @@ +from collatable.extras.dataloader import DataLoader, DefaultBatchSampler +from collatable.extras.datamodule import ( + DataModule, + FieldConfig, + FieldTransform, + LabelFieldTransform, + TextFieldTransform, +) +from collatable.extras.dataset import Dataset +from collatable.extras.indexer import Indexer, LabelIndexer, TokenIndexer + +__all__ = [ + "DataLoader", + "DefaultBatchSampler", + "DataModule", + "Dataset", + "Indexer", + "LabelIndexer", + "TokenIndexer", + "FieldConfig", + "FieldTransform", + "LabelFieldTransform", + "TextFieldTransform", +] diff --git a/collatable/extras/dataloader.py b/src/collatable/extras/dataloader.py similarity index 85% rename from collatable/extras/dataloader.py rename to src/collatable/extras/dataloader.py index 4442d2b..53f6268 100644 --- a/collatable/extras/dataloader.py +++ b/src/collatable/extras/dataloader.py @@ -1,6 +1,15 @@ import math import random -from typing import Dict, Iterable, Iterator, Mapping, Optional, Protocol, Sequence, TypeVar +from typing import ( + Dict, + Iterable, + Iterator, + Mapping, + Optional, + Protocol, + Sequence, + TypeVar, +) from collatable.collator import Collator from collatable.fields import Field @@ -59,7 +68,9 @@ def __init__( def __call__(self, dataset: Sequence) -> BatchIterator: num_batches = ( - len(dataset) // self._batch_size if self._drop_last else math.ceil(len(dataset) / self._batch_size) + len(dataset) // self._batch_size + if self._drop_last + else math.ceil(len(dataset) / self._batch_size) ) indices = list(range(len(dataset))) if self._shuffle: @@ -83,5 +94,7 @@ def __init__( self._sampler = sampler or DefaultBatchSampler() self._collator = collator or Collator() - def __call__(self, dataset: Sequence[Mapping[str, Field]]) -> SizedIterator[Mapping[str, DataArray]]: + def __call__( + self, dataset: Sequence[Mapping[str, Field]] + ) -> SizedIterator[Mapping[str, DataArray]]: return self._sampler(dataset) diff --git a/collatable/extras/datamodule.py b/src/collatable/extras/datamodule.py similarity index 83% rename from collatable/extras/datamodule.py rename to src/collatable/extras/datamodule.py index c68ad47..2442ef8 100644 --- a/collatable/extras/datamodule.py +++ b/src/collatable/extras/datamodule.py @@ -77,11 +77,19 @@ def build(self, dataset: Iterable[S]) -> None: pass def indexers(self) -> Mapping[str, IIndexer]: - return dict((attribute, value) for attribute, value in self.__dict__.items() if isinstance(value, IIndexer)) + return dict( + (attribute, value) + for attribute, value in self.__dict__.items() + if isinstance(value, IIndexer) + ) -class TextFieldTransform(Generic[HashableT], FieldTransform[Union[str, Sequence[HashableT]]]): - _DEFAULT_TOKENIZER_PATTERN = re.compile(r"[^\s.,!?:;/]+(?:[-']\[^\s.,!?:;/]+)*|[.,!?:;/]") +class TextFieldTransform( + Generic[HashableT], FieldTransform[Union[str, Sequence[HashableT]]] +): + _DEFAULT_TOKENIZER_PATTERN = re.compile( + r"[^\s.,!?:;/]+(?:[-']\[^\s.,!?:;/]+)*|[.,!?:;/]" + ) def __init__( self, @@ -93,7 +101,9 @@ def __init__( ) -> None: from .indexer import TokenIndexer - self._tokenizer = tokenizer or (lambda text: self._DEFAULT_TOKENIZER_PATTERN.findall(text)) + self._tokenizer = tokenizer or ( + lambda text: self._DEFAULT_TOKENIZER_PATTERN.findall(text) + ) self._indexer: ISequenceIndexer[HashableT, Mapping[str, Tensor]] = ( indexer if indexer is not None else TokenIndexer[HashableT]() ) @@ -110,7 +120,9 @@ def __call__(self, obj: Union[str, Sequence[HashableT]]) -> TextField: return TextField( obj, indexer=self._indexer.encode, - padding_value=self._indexer[self._pad_token] if self._pad_token is not None else 0, + padding_value=self._indexer[self._pad_token] + if self._pad_token is not None + else 0, ) def reconstruct(self, array: DataArray) -> Sequence[HashableT]: @@ -118,7 +130,9 @@ def reconstruct(self, array: DataArray) -> Sequence[HashableT]: field = TextField[HashableT].from_array( array, indexer=self._indexer, - padding_value=self._indexer[self._pad_token] if self._pad_token is not None else 0, + padding_value=self._indexer[self._pad_token] + if self._pad_token is not None + else 0, ) return field.tokens @@ -141,7 +155,9 @@ def __init__( ) -> None: from .indexer import LabelIndexer - self._indexer: IIndexer[HashableT, int] = indexer if indexer is not None else LabelIndexer[HashableT]() + self._indexer: IIndexer[HashableT, int] = ( + indexer if indexer is not None else LabelIndexer[HashableT]() + ) def __call__(self, obj: HashableT) -> LabelField: return LabelField(obj, indexer=self._indexer.encode) @@ -193,7 +209,12 @@ def build(self, dataset: Iterable[T]) -> None: def __call__(self, dataset: Iterable[T]) -> Iterable[Dict[str, Field]]: for obj in dataset: - yield {name: field.transform(field.accessor(obj)) for name, field in self._fields.items()} + yield { + name: field.transform(field.accessor(obj)) + for name, field in self._fields.items() + } def reconstruct(self, array: Mapping[str, DataArray]) -> Mapping[str, Any]: - return {name: field.reconstruct(array[name]) for name, field in self._fields.items()} + return { + name: field.reconstruct(array[name]) for name, field in self._fields.items() + } diff --git a/collatable/extras/dataset.py b/src/collatable/extras/dataset.py similarity index 96% rename from collatable/extras/dataset.py rename to src/collatable/extras/dataset.py index 5630cd2..b7c59a8 100644 --- a/collatable/extras/dataset.py +++ b/src/collatable/extras/dataset.py @@ -33,7 +33,11 @@ class Index(NamedTuple): length: int def to_bytes(self) -> bytes: - return self.page.to_bytes(4, "little") + self.offset.to_bytes(4, "little") + self.length.to_bytes(4, "little") + return ( + self.page.to_bytes(4, "little") + + self.offset.to_bytes(4, "little") + + self.length.to_bytes(4, "little") + ) @classmethod def from_binaryio(cls, f: BinaryIO) -> "Index": @@ -186,9 +190,9 @@ def __len__(self) -> int: def __getitem__(self, index: int) -> T: ... @overload - def __getitem__(self, index: slice) -> "List[T]": ... + def __getitem__(self, index: slice) -> List[T]: ... - def __getitem__(self, key: Union[int, slice]) -> Union[T, List[T]]: + def __getitem__(self, key: Union[int, slice]) -> Union[T, List[T]]: # type: ignore[override] if isinstance(key, slice): return [self[i] for i in range(*key.indices(len(self)))] elif isinstance(key, int): diff --git a/collatable/extras/indexer.py b/src/collatable/extras/indexer.py similarity index 88% rename from collatable/extras/indexer.py rename to src/collatable/extras/indexer.py index 4b753b6..be67ffb 100644 --- a/collatable/extras/indexer.py +++ b/src/collatable/extras/indexer.py @@ -41,11 +41,13 @@ def __init__( raise ValueError("default value must be in specials") self._index_to_value: List[ValueT] = list(specials) - self._value_to_index: Dict[ValueT, int] = {value: index for index, value in enumerate(specials)} + self._value_to_index: Dict[ValueT, int] = { + value: index for index, value in enumerate(specials) + } self._ignores: Set[ValueT] = set(ignores) - self._bos_value = bos - self._eos_value = eos - self._default_value = default + self._bos_value = cast(ValueT, bos) + self._eos_value = cast(ValueT, eos) + self._default_value = cast(ValueT, default) self._training = False def __len__(self) -> int: @@ -103,7 +105,9 @@ def from_iterable( eos: Optional[ValueT] = None, default: Optional[ValueT] = None, ) -> "Indexer[ValueT]": - indexer = cls(ignores=ignores, specials=specials, bos=bos, eos=eos, default=default) + indexer = cls( + ignores=ignores, specials=specials, bos=bos, eos=eos, default=default + ) with indexer.context(train=True): for value in iterable: indexer[value] @@ -155,7 +159,9 @@ def from_documents( min_df = int(min_df) if isinstance(min_df, int) else int(min_df * num_documents) max_df = int(max_df) if isinstance(max_df, int) else int(max_df * num_documents) - indexer = cls(ignores=ignores, specials=specials, bos=bos, eos=eos, default=default) + indexer = cls( + ignores=ignores, specials=specials, bos=bos, eos=eos, default=default + ) with indexer.context(train=True): for token, df in list(value_to_df.items()): if min_df <= df <= max_df: @@ -171,12 +177,19 @@ def encode(self, tokens: Sequence[ValueT]) -> Mapping[str, Tensor]: token_ids = [self._value_to_index[self._bos_value]] + token_ids if self._eos_value is not None: token_ids = token_ids + [self._value_to_index[self._eos_value]] - return {"token_ids": numpy.array(token_ids, dtype=numpy.int64), "mask": numpy.ones(len(token_ids), dtype=bool)} + return { + "token_ids": numpy.array(token_ids, dtype=numpy.int64), + "mask": numpy.ones(len(token_ids), dtype=bool), + } def decode(self, index: Mapping[str, Tensor]) -> Sequence[ValueT]: token_ids = index["token_ids"] mask = index["mask"] - return [self.get_value_by_index(token_id) for token_id, m in zip(token_ids, mask) if m] + return [ + self.get_value_by_index(token_id) + for token_id, m in zip(token_ids, mask) + if m + ] def __call__(self, tokens: Sequence[ValueT]) -> Mapping[str, Tensor]: return self.encode(tokens) diff --git a/src/collatable/fields/__init__.py b/src/collatable/fields/__init__.py new file mode 100644 index 0000000..03a5415 --- /dev/null +++ b/src/collatable/fields/__init__.py @@ -0,0 +1,29 @@ +from collatable.fields.adjacency_field import AdjacencyField +from collatable.fields.field import Field +from collatable.fields.index_field import IndexField +from collatable.fields.label_field import LabelField +from collatable.fields.list_field import ListField +from collatable.fields.mapping_field import MappingField +from collatable.fields.metadata_field import MetadataField +from collatable.fields.scalar_field import ScalarField +from collatable.fields.sequence_field import SequenceField +from collatable.fields.sequence_label_field import SequenceLabelField +from collatable.fields.span_field import SpanField +from collatable.fields.tensor_field import TensorField +from collatable.fields.text_field import TextField + +__all__ = [ + "AdjacencyField", + "Field", + "IndexField", + "LabelField", + "ListField", + "MappingField", + "MetadataField", + "ScalarField", + "SequenceField", + "SequenceLabelField", + "SpanField", + "TensorField", + "TextField", +] diff --git a/collatable/fields/adjacency_field.py b/src/collatable/fields/adjacency_field.py similarity index 73% rename from collatable/fields/adjacency_field.py rename to src/collatable/fields/adjacency_field.py index f037eba..4f8e6a1 100644 --- a/collatable/fields/adjacency_field.py +++ b/src/collatable/fields/adjacency_field.py @@ -1,4 +1,16 @@ -from typing import Callable, Generic, Hashable, List, Mapping, Optional, Protocol, Sequence, Tuple, TypeVar, Union, cast +from typing import ( + Callable, + Generic, + Hashable, + List, + Mapping, + Optional, + Protocol, + Sequence, + Tuple, + TypeVar, + cast, +) import numpy @@ -17,14 +29,20 @@ def decode(self, index: int) -> LabelT: ... class AdjacencyField(Generic[LabelT], Field[IntTensor]): - __slots__ = ["_indices", "_labels", "_indexed_labels", "_sequence_length", "_padding_value"] + __slots__ = [ + "_indices", + "_labels", + "_indexed_labels", + "_sequence_length", + "_padding_value", + ] def __init__( self, indices: Sequence[Tuple[int, int]], sequence_field: SequenceField, *, - labels: Optional[Union[Sequence[LabelT]]] = None, + labels: Optional[Sequence[LabelT]] = None, vocab: Optional[Mapping[LabelT, int]] = None, indexer: Optional[Callable[[LabelT], int]] = None, padding_value: PaddingValue = -1, @@ -33,13 +51,23 @@ def __init__( raise ValueError("AdjacencyField requires at least one index.") if labels is not None and len(indices) != len(labels): raise ValueError("AdjacencyField requires a label for every index.") - if labels is not None and (vocab is None is indexer) or (vocab is not None and indexer is not None): + if ( + labels is not None + and (vocab is None is indexer) + or (vocab is not None and indexer is not None) + ): raise ValueError("Must specify either vocab or indexer.") - if labels is not None and isinstance(labels[0], str) and (vocab or indexer) is None: + if ( + labels is not None + and isinstance(labels[0], str) + and (vocab or indexer) is None + ): raise ValueError("Vocab or indexer must be specified if label is a string.") if labels is not None and isinstance(labels[0], str) and vocab is not None: indexer = self._make_indexer(vocab) - if not all(0 <= index < len(sequence_field) for pair in indices for index in pair): + if not all( + 0 <= index < len(sequence_field) for pair in indices for index in pair + ): raise ValueError("Indices must be within the bounds of the sequence.") super().__init__(padding_value=padding_value) @@ -72,9 +100,13 @@ def as_array(self) -> IntTensor: array: IntTensor = numpy.full( (self._sequence_length, self._sequence_length), self.padding_value[""], - dtype=numpy.int32, + dtype=numpy.int_, + ) + labels = ( + self._indexed_labels + if self._labels is not None + else [1] * len(self._indices) ) - labels = self._indexed_labels if self._labels is not None else [1] * len(self._indices) assert labels is not None for (i, j), label in zip(self._indices, labels): array[i, j] = label @@ -90,7 +122,9 @@ def from_array( # type: ignore[override] padding_value: PaddingValue = -1, ) -> "AdjacencyField[LabelT]": if array.ndim != 2: - raise ValueError(f"AdjacencyField expects a 2-dimensional array, but got shape {array.shape}") + raise ValueError( + f"AdjacencyField expects a 2-dimensional array, but got shape {array.shape}" + ) indices = [] indexed_labels: List[LabelT] = [] for i, row in enumerate(array): @@ -100,4 +134,6 @@ def from_array( # type: ignore[override] if indexer is not None: indexed_labels.append(indexer.decode(label)) - return cls(indices, sequence_field, labels=indexed_labels, padding_value=padding_value) + return cls( + indices, sequence_field, labels=indexed_labels, padding_value=padding_value + ) diff --git a/collatable/fields/field.py b/src/collatable/fields/field.py similarity index 86% rename from collatable/fields/field.py rename to src/collatable/fields/field.py index 8262e5b..575b16d 100644 --- a/collatable/fields/field.py +++ b/src/collatable/fields/field.py @@ -20,7 +20,7 @@ def __init__(self, padding_value: PaddingValue = 0) -> None: self._padding_value = padding_value - def __eq__(self: Self, other: object) -> bool: + def __eq__(self, other: object) -> bool: if isinstance(self, other.__class__): for cls in self.__class__.mro(): for attr in getattr(cls, "__slots__", []): @@ -35,14 +35,19 @@ def __eq__(self: Self, other: object) -> bool: def padding_value(self) -> Dict[str, ArrayLike]: return self._padding_value - def collate(self: Self, arrays: Union[Sequence[DataArrayT], Sequence[Self]]) -> DataArrayT: + def collate( + self: Self, arrays: Union[Sequence[DataArrayT], Sequence[Self]] + ) -> DataArrayT: if isinstance(arrays[0], Field): arrays = [cast(Self, array).as_array() for array in arrays] arrays = cast(Sequence[DataArrayT], arrays) if isinstance(arrays[0], numpy.ndarray): return cast( DataArrayT, - stack_with_padding(cast(Sequence[numpy.ndarray], arrays), padding_value=self.padding_value[""]), + stack_with_padding( + cast(Sequence[numpy.ndarray], arrays), + padding_value=self.padding_value[""], + ), ) if isinstance(arrays[0], list): return cast(DataArrayT, list(arrays)) diff --git a/collatable/fields/index_field.py b/src/collatable/fields/index_field.py similarity index 77% rename from collatable/fields/index_field.py rename to src/collatable/fields/index_field.py index 3ee443b..0249a11 100644 --- a/collatable/fields/index_field.py +++ b/src/collatable/fields/index_field.py @@ -10,7 +10,9 @@ class IndexField(Field[IntTensor]): def __init__(self, index: int, sequence: SequenceField) -> None: if index < 0 or index >= len(sequence): - raise ValueError(f"Index {index} is out of range for sequence of length {len(sequence)}") + raise ValueError( + f"Index {index} is out of range for sequence of length {len(sequence)}" + ) super().__init__(padding_value=-1) self._index = index @@ -35,5 +37,7 @@ def from_array( # type: ignore[override] sequence: SequenceField, ) -> "IndexField": if array.ndim != 0: - raise ValueError(f"IndexField expects a 0-dimensional array, but got shape {array.shape}") + raise ValueError( + f"IndexField expects a 0-dimensional array, but got shape {array.shape}" + ) return cls(array.item(), sequence) diff --git a/collatable/fields/label_field.py b/src/collatable/fields/label_field.py similarity index 86% rename from collatable/fields/label_field.py rename to src/collatable/fields/label_field.py index 76f5ae7..5b2cb5a 100644 --- a/collatable/fields/label_field.py +++ b/src/collatable/fields/label_field.py @@ -1,4 +1,13 @@ -from typing import Callable, Generic, Hashable, Mapping, Optional, Protocol, TypeVar, cast +from typing import ( + Callable, + Generic, + Hashable, + Mapping, + Optional, + Protocol, + TypeVar, + cast, +) import numpy @@ -53,7 +62,7 @@ def label(self) -> LabelT: return self._label def as_array(self) -> IntTensor: - return numpy.array(self._label_index, dtype=numpy.int32) + return numpy.array(self._label_index, dtype=numpy.int_) @classmethod def from_array( # type: ignore[override] @@ -63,7 +72,9 @@ def from_array( # type: ignore[override] indexer: Optional[IDecotableIndexer[LabelT]] = None, ) -> "LabelField[LabelT]": if array.ndim != 0: - raise ValueError(f"LabelField expects a 0-dimensional array, but got shape {array.shape}") + raise ValueError( + f"LabelField expects a 0-dimensional array, but got shape {array.shape}" + ) label: LabelT = cast(LabelT, array.item()) if indexer is not None: label = indexer.decode(array.item()) diff --git a/collatable/fields/list_field.py b/src/collatable/fields/list_field.py similarity index 83% rename from collatable/fields/list_field.py rename to src/collatable/fields/list_field.py index 2ab973b..f50f25b 100644 --- a/collatable/fields/list_field.py +++ b/src/collatable/fields/list_field.py @@ -13,7 +13,11 @@ def __init__( fields: Sequence[Field[DataArrayT]], padding_value: Optional[PaddingValue] = None, ) -> None: - super().__init__(padding_value=padding_value if padding_value is not None else fields[0].padding_value) + super().__init__( + padding_value=padding_value + if padding_value is not None + else fields[0].padding_value + ) self._fields: Sequence[Field[DataArrayT]] = fields def __len__(self) -> int: @@ -46,4 +50,6 @@ def from_array( # type: ignore[override] item_type: Type[Field], padding_value: Optional[PaddingValue] = None, ) -> "ListField": - return cls([item_type.from_array(item) for item in array], padding_value=padding_value) + return cls( + [item_type.from_array(item) for item in array], padding_value=padding_value + ) diff --git a/src/collatable/fields/mapping_field.py b/src/collatable/fields/mapping_field.py new file mode 100644 index 0000000..641657d --- /dev/null +++ b/src/collatable/fields/mapping_field.py @@ -0,0 +1,78 @@ +from typing import ( + Any, + Dict, + Generic, + Iterator, + Mapping, + Sequence, + Tuple, + Type, + TypeVar, + Union, + cast, +) + +from collatable.fields.field import Field +from collatable.types import DataArray, DataArrayT + +Self = TypeVar("Self", bound="Field") +FieldT = TypeVar("FieldT", bound=Field) + + +class MappingField( + Generic[DataArrayT, FieldT], + Field[Dict[str, DataArrayT]], + Mapping[str, FieldT], +): + def __init__(self, mapping: Mapping[str, FieldT]) -> None: + super().__init__() + self._mapping = mapping + + def __len__(self) -> int: + return len(self._mapping) + + def __iter__(self) -> Iterator[str]: + return iter(self._mapping) + + def __getitem__(self, key: str) -> FieldT: + return self._mapping[key] + + def __contains__(self, key: object) -> bool: + return key in self._mapping + + def __str__(self) -> str: + return str(self._mapping) + + def __repr__(self) -> str: + return f"MappingField({self._mapping})" + + def as_array(self) -> Dict[str, Any]: + return {key: field.as_array() for key, field in self._mapping.items()} + + @classmethod + def from_array( # type: ignore[override] + cls, + array: Mapping[str, DataArray], + *, + fields: Mapping[str, Tuple[Type[FieldT], Mapping[str, Any]]], + ) -> "MappingField": + return cls( + { + key: field.from_array(array[key], **params) + for key, (field, params) in fields.items() + } + ) + + def collate( + self: Self, + arrays: Union[Sequence[Dict[str, DataArrayT]], Sequence[Self]], + ) -> Dict[str, DataArrayT]: + if not isinstance(arrays[0], MappingField): + arrays = cast(Sequence[Dict[str, DataArrayT]], arrays) + return super().collate(arrays) + return { + key: field.collate( + [x[key] for x in (x.as_array() for x in cast(Sequence[Self], arrays))] + ) + for key, field in cast(MappingField, self)._mapping.items() + } diff --git a/collatable/fields/metadata_field.py b/src/collatable/fields/metadata_field.py similarity index 100% rename from collatable/fields/metadata_field.py rename to src/collatable/fields/metadata_field.py diff --git a/collatable/fields/scalar_field.py b/src/collatable/fields/scalar_field.py similarity index 96% rename from collatable/fields/scalar_field.py rename to src/collatable/fields/scalar_field.py index 7036350..a00222f 100644 --- a/collatable/fields/scalar_field.py +++ b/src/collatable/fields/scalar_field.py @@ -18,7 +18,7 @@ def __init__( if padding_value is None: padding_value = get_scalar_default_value(type(value)) super().__init__(padding_value=padding_value) - self._value: ScalarT = value + self._value = value def __str__(self) -> str: return str(self._value) diff --git a/collatable/fields/sequence_field.py b/src/collatable/fields/sequence_field.py similarity index 100% rename from collatable/fields/sequence_field.py rename to src/collatable/fields/sequence_field.py diff --git a/collatable/fields/sequence_label_field.py b/src/collatable/fields/sequence_label_field.py similarity index 85% rename from collatable/fields/sequence_label_field.py rename to src/collatable/fields/sequence_label_field.py index 2e31b04..51b61ff 100644 --- a/collatable/fields/sequence_label_field.py +++ b/src/collatable/fields/sequence_label_field.py @@ -1,4 +1,15 @@ -from typing import Callable, Generic, Hashable, Iterator, Mapping, Optional, Protocol, Sequence, TypeVar, Union, cast +from typing import ( + Callable, + Generic, + Hashable, + Iterator, + Mapping, + Optional, + Protocol, + Sequence, + TypeVar, + cast, +) import numpy @@ -20,7 +31,7 @@ class SequenceLabelField(Generic[LabelT], SequenceField[IntTensor]): def __init__( self, - labels: Union[Sequence[LabelT]], + labels: Sequence[LabelT], sequence_field: SequenceField, *, vocab: Optional[Mapping[LabelT, int]] = None, @@ -28,7 +39,9 @@ def __init__( padding_value: PaddingValue = 0, ) -> None: if len(labels) != len(sequence_field): - raise ValueError("SequenceLabelField requires a label for every token in the sequence.") + raise ValueError( + "SequenceLabelField requires a label for every token in the sequence." + ) if (vocab is None is indexer) or (vocab is not None and indexer is not None): raise ValueError("Must specify either vocab or indexer.") if vocab is not None: @@ -77,7 +90,9 @@ def from_array( # type: ignore[override] indexer: Optional[IDecotableIndexer[LabelT]] = None, ) -> "SequenceLabelField[LabelT]": if array.ndim != 1: - raise ValueError(f"SequenceLabelField expects a 1-dimensional array, but got shape {array.shape}") + raise ValueError( + f"SequenceLabelField expects a 1-dimensional array, but got shape {array.shape}" + ) labels: Sequence[LabelT] = cast(Sequence[LabelT], array.tolist()) if indexer is not None: labels = [indexer.decode(index) for index in array] diff --git a/collatable/fields/span_field.py b/src/collatable/fields/span_field.py similarity index 85% rename from collatable/fields/span_field.py rename to src/collatable/fields/span_field.py index 6ffaa76..a92d014 100644 --- a/collatable/fields/span_field.py +++ b/src/collatable/fields/span_field.py @@ -22,7 +22,9 @@ def __init__( if span_start > span_end: raise ValueError("Span start must be less than or equal to span end.") if span_end > len(sequence_field): - raise ValueError("Span end must be less than or equal to the length of the sequence.") + raise ValueError( + "Span end must be less than or equal to the length of the sequence." + ) super().__init__(padding_value=padding_value) @@ -53,5 +55,7 @@ def from_array( # type: ignore[override] sequence_field: SequenceField, ) -> "SpanField": if array.ndim != 1 or array.shape[0] != 2: - raise ValueError(f"SpanField expects a 1-dimensional array of length 2, but got shape {array.shape}") + raise ValueError( + f"SpanField expects a 1-dimensional array of length 2, but got shape {array.shape}" + ) return cls(array[0], array[1], sequence_field) diff --git a/collatable/fields/tensor_field.py b/src/collatable/fields/tensor_field.py similarity index 78% rename from collatable/fields/tensor_field.py rename to src/collatable/fields/tensor_field.py index 3caf4b2..083245b 100644 --- a/collatable/fields/tensor_field.py +++ b/src/collatable/fields/tensor_field.py @@ -24,14 +24,19 @@ def tensor(self) -> TensorT: def __eq__(self, other: object) -> bool: if isinstance(self, other.__class__): other = cast(TensorField, other) - return numpy.array_equal(self.tensor, other.tensor) and self.padding_value == other.padding_value + return ( + numpy.array_equal(self.tensor, other.tensor) + and self.padding_value == other.padding_value + ) return NotImplemented def __str__(self) -> str: return str(self._tensor) def __repr__(self) -> str: - return f"TensorField(tensor={self._tensor}, padding_value={self._padding_value})" + return ( + f"TensorField(tensor={self._tensor}, padding_value={self._padding_value})" + ) def as_array(self) -> TensorT: return self._tensor diff --git a/collatable/fields/text_field.py b/src/collatable/fields/text_field.py similarity index 82% rename from collatable/fields/text_field.py rename to src/collatable/fields/text_field.py index 66ae1e5..4fa7e68 100644 --- a/collatable/fields/text_field.py +++ b/src/collatable/fields/text_field.py @@ -1,4 +1,14 @@ -from typing import Callable, Generic, Hashable, Iterator, Mapping, Optional, Protocol, Sequence, TypeVar +from typing import ( + Callable, + Generic, + Hashable, + Iterator, + Mapping, + Optional, + Protocol, + Sequence, + TypeVar, +) import numpy @@ -23,7 +33,9 @@ def __init__( tokens: Sequence[TokenT], *, vocab: Optional[Mapping[TokenT, int]] = None, - indexer: Optional[Callable[[Sequence[TokenT]], Mapping[str, numpy.ndarray]]] = None, + indexer: Optional[ + Callable[[Sequence[TokenT]], Mapping[str, numpy.ndarray]] + ] = None, padding_value: PaddingValue = 0, ) -> None: if (vocab is None is indexer) or (vocab is not None and indexer is not None): @@ -72,9 +84,13 @@ def from_array( # type: ignore[override] return cls(tokens, indexer=indexer, padding_value=padding_value) @staticmethod - def _make_indexer(vocab: Mapping[TokenT, int]) -> Callable[[Sequence[TokenT]], Mapping[str, numpy.ndarray]]: + def _make_indexer( + vocab: Mapping[TokenT, int], + ) -> Callable[[Sequence[TokenT]], Mapping[str, numpy.ndarray]]: def indexer(tokens: Sequence[TokenT]) -> Mapping[str, numpy.ndarray]: - token_ids: numpy.ndarray = numpy.array([vocab[token] for token in tokens], dtype=numpy.int64) + token_ids: numpy.ndarray = numpy.array( + [vocab[token] for token in tokens], dtype=numpy.int64 + ) mask: numpy.ndarray = numpy.ones_like(token_ids, dtype=bool) output = {"token_ids": token_ids, "mask": mask} return output diff --git a/collatable/py.typed b/src/collatable/py.typed similarity index 100% rename from collatable/py.typed rename to src/collatable/py.typed diff --git a/collatable/types.py b/src/collatable/types.py similarity index 68% rename from collatable/types.py rename to src/collatable/types.py index 50469b5..01e4532 100644 --- a/collatable/types.py +++ b/src/collatable/types.py @@ -1,8 +1,38 @@ import dataclasses -from typing import Any, ClassVar, Dict, Mapping, Protocol, Sequence, Tuple, TypeVar, Union, runtime_checkable +from typing import ( + Any, + ClassVar, + Dict, + Mapping, + Protocol, + Sequence, + Tuple, + TypeVar, + Union, + runtime_checkable, +) import numpy -from numpy.typing import ArrayLike, NDArray # noqa: F401 +from numpy.typing import ArrayLike, NDArray + +__all__ = [ + "ArrayLike", + "BoolTensor", + "DataArray", + "DataArrayT", + "DataArrayT_co", + "DataclassT", + "IDataclass", + "IntTensor", + "INamedTuple", + "NamedTupleT", + "Scalar", + "ScalarT", + "ScalarT_co", + "Tensor", + "TensorT", + "TensorT_co", +] Scalar = Union[int, float, complex, bool] Tensor = NDArray diff --git a/collatable/utils.py b/src/collatable/utils.py similarity index 86% rename from collatable/utils.py rename to src/collatable/utils.py index 38d027c..425c712 100644 --- a/collatable/utils.py +++ b/src/collatable/utils.py @@ -14,7 +14,9 @@ def stack_with_padding( max_shape = tuple(max(shape) for shape in zip(*shapes)) if max_shape == (): return cast(TensorT, numpy.array(tensors)) - stacked = cast(TensorT, numpy.zeros((num_arrays, *max_shape), dtype=tensors[0].dtype)) + stacked = cast( + TensorT, numpy.zeros((num_arrays, *max_shape), dtype=tensors[0].dtype) + ) for index, tensor in enumerate(tensors): stacked[index] = numpy.pad( tensor, @@ -43,5 +45,8 @@ def debatched(array: DataArray) -> List[DataArray]: keys = set(array) debatched_values = {key: debatched(value) for key, value in array.items()} batch_size = len(debatched_values[next(iter(keys))]) - return [{key: debatched_values[key][index] for key in keys} for index in range(batch_size)] + return [ + {key: debatched_values[key][index] for key in keys} + for index in range(batch_size) + ] raise TypeError(f"Unsupported type: {type(array)}") diff --git a/tests/extras/test_dataloader.py b/tests/extras/test_dataloader.py index 152da58..5646602 100644 --- a/tests/extras/test_dataloader.py +++ b/tests/extras/test_dataloader.py @@ -9,7 +9,9 @@ def test_dataloader() -> None: PAD_TOKEN = "" UNK_TOKEN = "" - token_indexer = TokenIndexer[str](specials=[PAD_TOKEN, UNK_TOKEN], default=UNK_TOKEN) + token_indexer = TokenIndexer[str]( + specials=[PAD_TOKEN, UNK_TOKEN], default=UNK_TOKEN + ) label_indexer = LabelIndexer[str]() def read_dataset() -> Iterator[dict]: diff --git a/tests/extras/test_datamodule.py b/tests/extras/test_datamodule.py index 1a9a464..81212ea 100644 --- a/tests/extras/test_datamodule.py +++ b/tests/extras/test_datamodule.py @@ -1,8 +1,18 @@ from dataclasses import dataclass from typing import Mapping, Sequence, Union -from collatable.extras import DataLoader, Dataset, DefaultBatchSampler, LabelIndexer, TokenIndexer -from collatable.extras.datamodule import DataModule, LabelFieldTransform, TextFieldTransform +from collatable.extras import ( + DataLoader, + Dataset, + DefaultBatchSampler, + LabelIndexer, + TokenIndexer, +) +from collatable.extras.datamodule import ( + DataModule, + LabelFieldTransform, + TextFieldTransform, +) from collatable.utils import debatched @@ -18,7 +28,9 @@ class Text2TextExample: Text2TextExample(source="what is your name?", target="My name is John."), Text2TextExample(source="where are you?", target="I am in New-York."), Text2TextExample(source="what is the time?", target="It is 10:00 AM."), - Text2TextExample(source="comment ça va?", target="Je vais bien.", language="fr"), + Text2TextExample( + source="comment ça va?", target="Je vais bien.", language="fr" + ), ] shared_token_indexer = TokenIndexer(default="", specials=["", ""]) @@ -26,8 +38,12 @@ class Text2TextExample: text2text_datamodule = DataModule[Text2TextExample]( fields={ - "source": TextFieldTransform(indexer=shared_token_indexer, pad_token=""), - "target": TextFieldTransform(indexer=shared_token_indexer, pad_token=""), + "source": TextFieldTransform( + indexer=shared_token_indexer, pad_token="" + ), + "target": TextFieldTransform( + indexer=shared_token_indexer, pad_token="" + ), "language": LabelFieldTransform(indexer=language_indexer), } ) diff --git a/tests/fields/test_adjacency_field.py b/tests/fields/test_adjacency_field.py index 1477f51..8e9b520 100644 --- a/tests/fields/test_adjacency_field.py +++ b/tests/fields/test_adjacency_field.py @@ -16,12 +16,32 @@ def test_adajacency_field() -> None: instances = [] with token_indexer.context(train=True), label_indexer.context(train=True): text = TextField( - ["john", "smith", "was", "born", "in", "new", "york", "and", "now", "lives", "in", "tokyo"], + [ + "john", + "smith", + "was", + "born", + "in", + "new", + "york", + "and", + "now", + "lives", + "in", + "tokyo", + ], indexer=token_indexer, padding_value=token_indexer[PAD_TOKEN], ) - spans = ListField([SpanField(0, 2, text), SpanField(5, 7, text), SpanField(11, 12, text)]) - relations = AdjacencyField([(0, 1), (0, 2)], spans, labels=["born-in", "lives-in"], indexer=label_indexer) + spans = ListField( + [SpanField(0, 2, text), SpanField(5, 7, text), SpanField(11, 12, text)] + ) + relations = AdjacencyField( + [(0, 1), (0, 2)], + spans, + labels=["born-in", "lives-in"], + indexer=label_indexer, + ) instance = dict(text=text, spans=spans, relations=relations) instances.append(instance) @@ -31,7 +51,9 @@ def test_adajacency_field() -> None: padding_value=token_indexer[PAD_TOKEN], ) spans = ListField([SpanField(0, 1, text), SpanField(5, 6, text)]) - relations = AdjacencyField([(0, 1)], spans, labels=["capital-of"], indexer=label_indexer) + relations = AdjacencyField( + [(0, 1)], spans, labels=["capital-of"], indexer=label_indexer + ) instance = dict(text=text, spans=spans, relations=relations) instances.append(instance) diff --git a/tests/fields/test_index_field.py b/tests/fields/test_index_field.py index 12723f1..7ffd78f 100644 --- a/tests/fields/test_index_field.py +++ b/tests/fields/test_index_field.py @@ -15,5 +15,7 @@ def test_index_field_can_be_converted_to_array() -> None: def test_index_field_can_raise_value_error() -> None: vocab = {"a": 0, "is": 1, "test": 2, "this": 3} text = TextField(["this", "is", "a", "test"], vocab=vocab) - with pytest.raises(ValueError, match="Index 4 is out of range for sequence of length 4"): + with pytest.raises( + ValueError, match="Index 4 is out of range for sequence of length 4" + ): IndexField(4, text) diff --git a/tests/fields/test_mapping_field.py b/tests/fields/test_mapping_field.py index 2794ef0..16fe137 100644 --- a/tests/fields/test_mapping_field.py +++ b/tests/fields/test_mapping_field.py @@ -27,17 +27,30 @@ def test_mapping_field_can_be_converted_to_array() -> None: def test_mapping_field_can_be_collated() -> None: class TokenIndexer: - VOCAB = {"": -1, "a": 0, "first": 1, "is": 2, "this": 3, "second": 4, "sentence": 5, "!": 6} + VOCAB = { + "": -1, + "a": 0, + "first": 1, + "is": 2, + "this": 3, + "second": 4, + "sentence": 5, + "!": 6, + } INV_VOCAB = {index: token for token, index in VOCAB.items()} def __call__(self, tokens: Sequence[str], /) -> Mapping[str, numpy.ndarray]: return { - "token_ids": numpy.array([self.VOCAB[token] for token in tokens], dtype=numpy.int64), + "token_ids": numpy.array( + [self.VOCAB[token] for token in tokens], dtype=numpy.int64 + ), "mask": numpy.array([True] * len(tokens), dtype=numpy.bool_), } def decode(self, index: Mapping[str, numpy.ndarray], /) -> Sequence[str]: - return [self.INV_VOCAB[index] for index in index["token_ids"] if index != -1] + return [ + self.INV_VOCAB[index] for index in index["token_ids"] if index != -1 + ] class LabelIndexer: LABELS = {"negative": 0, "positive": 1} @@ -56,7 +69,9 @@ def decode(self, index: int, /) -> str: MappingField( { "text": TextField( - ["this", "is", "a", "first", "sentence"], indexer=token_indexer, padding_value=padding_value + ["this", "is", "a", "first", "sentence"], + indexer=token_indexer, + padding_value=padding_value, ), "label": LabelField("positive", indexer=label_indexer), } @@ -64,7 +79,9 @@ def decode(self, index: int, /) -> str: MappingField( { "text": TextField( - ["this", "is", "a", "second", "sentence", "!"], indexer=token_indexer, padding_value=padding_value + ["this", "is", "a", "second", "sentence", "!"], + indexer=token_indexer, + padding_value=padding_value, ), "label": LabelField("negative", indexer=label_indexer), } @@ -75,7 +92,10 @@ def decode(self, index: int, /) -> str: assert isinstance(output, dict) assert output.keys() == {"text", "label"} - assert output["text"]["token_ids"].tolist() == [[3, 2, 0, 1, 5, -1], [3, 2, 0, 4, 5, 6]] + assert output["text"]["token_ids"].tolist() == [ + [3, 2, 0, 1, 5, -1], + [3, 2, 0, 4, 5, 6], + ] assert output["text"]["mask"].sum(1).tolist() == [5, 6] assert output["label"].tolist() == [1, 0] @@ -95,7 +115,14 @@ def decode(self, index: int, /) -> str: assert isinstance(reconstruction[0]["text"], TextField) assert isinstance(reconstruction[1]["text"], TextField) assert reconstruction[0]["text"].tokens == ["this", "is", "a", "first", "sentence"] - assert reconstruction[1]["text"].tokens == ["this", "is", "a", "second", "sentence", "!"] + assert reconstruction[1]["text"].tokens == [ + "this", + "is", + "a", + "second", + "sentence", + "!", + ] assert isinstance(reconstruction[0]["label"], LabelField) assert isinstance(reconstruction[1]["label"], LabelField) assert reconstruction[0]["label"].label == "positive" diff --git a/tests/fields/test_sequence_label_field.py b/tests/fields/test_sequence_label_field.py index b2b8219..a9602e5 100644 --- a/tests/fields/test_sequence_label_field.py +++ b/tests/fields/test_sequence_label_field.py @@ -9,14 +9,19 @@ def test_sequence_label_field() -> None: label_vocab = {"O": 0, "B": 1, "I": 2, "U": 3} dataset = [ (["O", "O", "O", "B", "I"], ["my", "name", "is", "john", "smith"]), - (["O", "O", "O", "U", "O", "O", "O"], ["i", "lived", "in", "japan", "three", "years", "ago"]), + ( + ["O", "O", "O", "U", "O", "O", "O"], + ["i", "lived", "in", "japan", "three", "years", "ago"], + ), ] token_indexer = TokenIndexer[str]() fields = [] with token_indexer.context(train=True): for labels, tokens in dataset: text_field = TextField(tokens, indexer=token_indexer) - sequence_label_field = SequenceLabelField(labels, text_field, vocab=label_vocab) + sequence_label_field = SequenceLabelField( + labels, text_field, vocab=label_vocab + ) fields.append(sequence_label_field) output = fields[0].collate(fields) diff --git a/tests/fields/test_text_field.py b/tests/fields/test_text_field.py index 7c826d3..04c63e9 100644 --- a/tests/fields/test_text_field.py 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