mypy-status mypy exited with status 1.

flair/data.py 1730: error: Argument 1 to "len" has incompatible type "Dataset[Any]"; expected "Sized" [arg-type]

ruff pytest_ruff.RuffError: flair/datasets/biomedical.py:375:9: F841 Local variable `entity_types` is assigned to but never used | 373 | # Add task description for multi-task learning 374 | assert len(dataset.entity_types) > 0 375 | entity_types = sorted(set(dataset.entity_types)) | ^^^^^^^^^^^^ F841 376 | mapping = { 377 | CELL_LINE_TAG: "cell lines", | = help: Remove assignment to unused variable `entity_types` flair/datasets/biomedical.py:376:9: F841 Local variable `mapping` is assigned to but never used | 374 | assert len(dataset.entity_types) > 0 375 | entity_types = sorted(set(dataset.entity_types)) 376 | mapping = { | ^^^^^^^ F841 377 | CELL_LINE_TAG: "cell lines", 378 | CHEMICAL_TAG: "chemicals", | = help: Remove assignment to unused variable `mapping`

ruff pytest_ruff.RuffError: flair/models/sequence_tagger_model.py:1046:5: D415 First line should end with a period, question mark, or exclamation point | 1045 | class AugmentedSentence(Sentence): 1046 | """A Sentence that expresses that a sentence is augmented and compatible with the HunFlairAllInOneSequenceTagger | _____^ 1047 | | 1048 | | For inference, i.e. `predict` and `evaluate`, the HunFlairAllInOneSequenceTagger internally encodes the sentences. 1049 | | Therefore, these functions work with the regular flair sentence objects. 1050 | | """ | |_______^ D415 | = help: Add closing punctuation flair/models/sequence_tagger_model.py:1056:54: RUF013 PEP 484 prohibits implicit `Optional` | 1054 | @AbstractMethod 1055 | def augment_sentence( 1056 | self, sentence: Sentence, annotation_layers: Union[str, List[str]] = None | ^^^^^^^^^^^^^^^^^^^^^ RUF013 1057 | ) -> AugmentedSentence: 1058 | """ | = help: Convert to `Optional[T]` flair/models/sequence_tagger_model.py:1058:9: D205 1 blank line required between summary line and description | 1056 | self, sentence: Sentence, annotation_layers: Union[str, List[str]] = None 1057 | ) -> AugmentedSentence: 1058 | """ | _________^ 1059 | | Augments the given sentence text with additional instructions for working / predicting 1060 | | the task on the given annotations. 1061 | | 1062 | | Args: 1063 | | sentence: The sentence to be augmented 1064 | | annotation_layers: Annotations which should be predicted. 1065 | | """ | |___________^ D205 1066 | ... | = help: Insert single blank line flair/models/sequence_tagger_model.py:1058:9: D212 [*] Multi-line docstring summary should start at the first line | 1056 | self, sentence: Sentence, annotation_layers: Union[str, List[str]] = None 1057 | ) -> AugmentedSentence: 1058 | """ | _________^ 1059 | | Augments the given sentence text with additional instructions for working / predicting 1060 | | the task on the given annotations. 1061 | | 1062 | | Args: 1063 | | sentence: The sentence to be augmented 1064 | | annotation_layers: Annotations which should be predicted. 1065 | | """ | |___________^ D212 1066 | ... | = help: Remove whitespace after opening quotes flair/models/sequence_tagger_model.py:1076:9: D212 [*] Multi-line docstring summary should start at the first line | 1074 | target_annotation_layer: str, 1075 | ): 1076 | """ | _________^ 1077 | | Transfers the predictions made on the augmented sentence to the original one. 1078 | | 1079 | | Args: 1080 | | augmented_sentence: The augmented sentence instance 1081 | | original_sentence: The original sentence before the augmentation was applied 1082 | | source_annotation_layer: Annotation layer of the augmented sentence in which the predictions are stored. 1083 | | target_annotation_layer: Annotation layer in which the predictions should be stored in the original sentence. 1084 | | """ | |___________^ D212 1085 | ... | = help: Remove whitespace after opening quotes flair/models/sequence_tagger_model.py:1089:9: D200 One-line docstring should fit on one line | 1087 | @AbstractMethod 1088 | def _get_state_dict(self): 1089 | """ | _________^ 1090 | | Returns the state dict for the given augmentation strategy. 1091 | | """ | |___________^ D200 1092 | ... | = help: Reformat to one line flair/models/sequence_tagger_model.py:1089:9: D212 [*] Multi-line docstring summary should start at the first line | 1087 | @AbstractMethod 1088 | def _get_state_dict(self): 1089 | """ |

flair/models/sequence_tagger_model.py 1056: error: Incompatible default for argument "annotation_layers" (default has type "None", argument has type "Union[str, List[str]]") [assignment] 1056: note: PEP 484 prohibits implicit Optional. Accordingly, mypy has changed its default to no_implicit_optional=True 1056: note: Use https://github.com/hauntsaninja/no_implicit_optional to automatically upgrade your codebase 1101: error: Incompatible default for argument "annotation_layers" (default has type "None", argument has type "Union[str, List[str]]") [assignment] 1101: note: PEP 484 prohibits implicit Optional. Accordingly, mypy has changed its default to no_implicit_optional=True 1101: note: Use https://github.com/hauntsaninja/no_implicit_optional to automatically upgrade your codebase 1123: error: Incompatible default for argument "annotation_layers" (default has type "None", argument has type "Union[str, List[str]]") [assignment] 1123: note: PEP 484 prohibits implicit Optional. Accordingly, mypy has changed its default to no_implicit_optional=True 1123: note: Use https://github.com/hauntsaninja/no_implicit_optional to automatically upgrade your codebase 1169: error: Incompatible default for argument "annotation_layers" (default has type "None", argument has type "Union[str, List[str]]") [assignment] 1169: note: PEP 484 prohibits implicit Optional. Accordingly, mypy has changed its default to no_implicit_optional=True 1169: note: Use https://github.com/hauntsaninja/no_implicit_optional to automatically upgrade your codebase 1282: error: Signature of "load" incompatible with supertype "SequenceTagger" [override] 1282: note: Superclass: 1282: note: @classmethod 1282: note: def load(cls, model_path: Union[str, Path, Dict[str, Any]]) -> SequenceTagger 1282: note: Subclass: 1282: note: @classmethod 1282: note: def load(cls, model_path: Union[str, Path, Dict[str, Any]], augmentation_strategy: EntityTypeTaskPromptAugmentationStrategy) -> AugmentedSentenceSequenceTagger 1282: error: Signature of "load" incompatible with supertype "Classifier" [override] 1282: note: Superclass: 1282: note: @classmethod 1282: note: def load(cls, model_path: Union[str, Path, Dict[str, Any]]) -> Classifier[Any] 1282: note: Subclass: 1282: note: @classmethod 1282: note: def load(cls, model_path: Union[str, Path, Dict[str, Any]], augmentation_strategy: EntityTypeTaskPromptAugmentationStrategy) -> AugmentedSentenceSequenceTagger 1282: error: Signature of "load" incompatible with supertype "Model" [override] 1282: note: Superclass: 1282: note: @classmethod 1282: note: def load(cls, model_path: Union[str, Path, Dict[str, Any]]) -> Model[Any] 1282: note: Subclass: 1282: note: @classmethod 1282: note: def load(cls, model_path: Union[str, Path, Dict[str, Any]], augmentation_strategy: EntityTypeTaskPromptAugmentationStrategy) -> AugmentedSentenceSequenceTagger 1303: error: Incompatible types in assignment (expression has type "List[AugmentedSentence]", variable has type "List[Sentence]") [assignment] 1303: note: "List" is invariant -- see https://mypy.readthedocs.io/en/stable/common_issues.html#variance 1303: note: Consider using "Sequence" instead, which is covariant 1309: error: Signature of "predict" incompatible with supertype "SequenceTagger" [override] 1309: note: Superclass: 1309: note: def predict(self, sentences: Union[List[Sentence], Sentence], mini_batch_size: int = ..., return_probabilities_for_all_classes: bool = ..., verbose: bool = ..., label_name: Optional[str] = ..., return_loss: Any = ..., embedding_storage_mode: Any = ..., force_token_predictions: bool = ...) -> Any 1309: note: Subclass: 1309: note: def predict(self, sentences: Union[List[Sentence], Sentence], **kwargs: Any) -> Any 1309: error: Signature of "predict" incompatible with supertype "Classifier" [override] 1309: note: Superclass: 1309: note: def predict(self, sentences: Union[List[Sentence], Se

Black format check --- /home/runner/work/flair/flair/flair/models/sequence_tagger_model.py 2024-01-15 09:04:26.189260+00:00 +++ /home/runner/work/flair/flair/flair/models/sequence_tagger_model.py 2024-01-15 09:06:47.248631+00:00 @@ -1190,11 +1190,13 @@ label_span = augmented_sentence[ len_task_prompt + label.data_point.idx - 1 : len_task_prompt + label.data_point.idx ] else: label_span = augmented_sentence[ - len_task_prompt + label.data_point.tokens[0].idx - 1 : len_task_prompt + len_task_prompt + + label.data_point.tokens[0].idx + - 1 : len_task_prompt + label.data_point.tokens[-1].idx ] label_span.add_label(layer, label.value, label.score) @@ -1213,11 +1215,13 @@ try: for label in new_labels: if label.data_point.tokens[0].idx - len_task_prompt - 1 < 0: continue orig_span = original_sentence[ - label.data_point.tokens[0].idx - len_task_prompt - 1 : label.data_point.tokens[-1].idx + label.data_point.tokens[0].idx + - len_task_prompt + - 1 : label.data_point.tokens[-1].idx - len_task_prompt ] orig_span.add_label(target_annotation_layer, label.value, label.score) except IndexError: for token in original_sentence:

ruff pytest_ruff.RuffError: tests/test_augmentation.py:1:1: I001 [*] Import block is un-sorted or un-formatted | 1 | / from flair.data import Sentence 2 | | from flair.models.sequence_tagger_model import EntityTypeTaskPromptAugmentationStrategy, AugmentedSentence 3 | | 4 | | 5 | | def test_entity_type_task_prompt_augmentation_single_type(): | |_^ I001 6 | strategy = EntityTypeTaskPromptAugmentationStrategy(["genes"]) | = help: Organize imports