Entity Mention Linker #2088
Annotations
11 errors and 1 warning
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Run tests:
flair/data.py#L345
ruff
pytest_ruff.RuffError: flair/data.py:366:16: SIM401 Use `self.annotation_layers.get(typename, [])` instead of an `if` block
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364 | return self.labels
365 |
366 | return self.annotation_layers[typename] if typename in self.annotation_layers else []
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SIM401
367 |
368 | @Property
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= help: Replace with `self.annotation_layers.get(typename, [])`
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Run tests:
flair/data.py#L1
Black format check
--- /home/runner/work/flair/flair/flair/data.py 2024-02-02 15:09:53.017994+00:00
+++ /home/runner/work/flair/flair/flair/data.py 2024-02-02 15:12:18.100663+00:00
@@ -1042,16 +1042,14 @@
def get_span(self, start: int, stop: int):
span_slice = slice(start, stop)
return self[span_slice]
@typing.overload
- def __getitem__(self, idx: int) -> Token:
- ...
+ def __getitem__(self, idx: int) -> Token: ...
@typing.overload
- def __getitem__(self, s: slice) -> Span:
- ...
+ def __getitem__(self, s: slice) -> Span: ...
def __getitem__(self, subscript):
if isinstance(subscript, slice):
return Span(self.tokens[subscript])
else:
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Run tests:
flair/datasets/base.py#L345
ruff
pytest_ruff.RuffError: flair/datasets/base.py:185:22: SIM401 Use `document.get(_, "")` instead of an `if` block
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183 | sentence = self._parse_document_to_sentence(
184 | document[self.text],
185 | [document[_] if _ in document else "" for _ in self.categories],
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SIM401
186 | tokenizer,
187 | )
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= help: Replace with `document.get(_, "")`
flair/datasets/base.py:228:18: SIM401 Use `document.get(_, "")` instead of an `if` block
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226 | sentence = self._parse_document_to_sentence(
227 | document[self.text],
228 | [document[_] if _ in document else "" for _ in self.categories],
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SIM401
229 | self.tokenizer,
230 | )
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= help: Replace with `document.get(_, "")`
|
Run tests:
flair/datasets/biomedical.py#L345
ruff
pytest_ruff.RuffError: flair/datasets/biomedical.py:2197:30: SIM401 Use `patch_lines.get(line_no, line)` instead of an `if` block
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2196 | for line in input:
2197 | output.write(patch_lines[line_no] if line_no in patch_lines else line)
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SIM401
2198 | line_no += 1
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= help: Replace with `patch_lines.get(line_no, line)`
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Run tests:
flair/datasets/sequence_labeling.py#L345
ruff
pytest_ruff.RuffError: flair/datasets/sequence_labeling.py:2767:21: SIM113 Use `enumerate()` for index variable `k` in `for` loop
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2765 | k = 0
2766 | for line in file.readlines():
2767 | k += 1
| ^^^^^^ SIM113
2768 | if k <= train_len:
2769 | train.write(line)
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Run tests:
flair/datasets/text_image.py#L345
ruff
pytest_ruff.RuffError: flair/datasets/text_image.py:66:12: RUF019 [*] Unnecessary key check before dictionary access
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65 | preprocessor = identity
66 | if "lowercase" in kwargs and kwargs["lowercase"]:
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ RUF019
67 | preprocessor = str.lower
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= help: Replace with `dict.get`
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Run tests:
flair/file_utils.py#L1
Black format check
--- /home/runner/work/flair/flair/flair/file_utils.py 2024-02-02 15:09:53.021994+00:00
+++ /home/runner/work/flair/flair/flair/file_utils.py 2024-02-02 15:12:25.977403+00:00
@@ -1,6 +1,7 @@
"""Utilities for working with the local dataset cache. Copied from AllenNLP."""
+
import base64
import functools
import io
import logging
import mmap
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Run tests:
flair/models/entity_linker_model.py#L1
Black format check
--- /home/runner/work/flair/flair/flair/models/entity_linker_model.py 2024-02-02 15:09:53.021994+00:00
+++ /home/runner/work/flair/flair/flair/models/entity_linker_model.py 2024-02-02 15:12:26.990886+00:00
@@ -106,13 +106,13 @@
**classifierargs: The arguments propagated to :meth:`flair.nn.DefaultClassifier.__init__`
"""
super().__init__(
embeddings=embeddings,
label_dictionary=label_dictionary,
- final_embedding_size=embeddings.embedding_length * 2
- if pooling_operation == "first_last"
- else embeddings.embedding_length,
+ final_embedding_size=(
+ embeddings.embedding_length * 2 if pooling_operation == "first_last" else embeddings.embedding_length
+ ),
**classifierargs,
)
self.pooling_operation = pooling_operation
self._label_type = label_type
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Run tests:
flair/models/entity_mention_linking.py#L345
ruff
pytest_ruff.RuffError: flair/models/entity_mention_linking.py:605:13: SIM401 Use `HYBRID_MODELS_SPARSE_WEIGHT.get(model_name_or_path, sparse_weight)` instead of an `if` block
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604 | sparse_weight = (
605 | sparse_weight
| _____________^
606 | | if model_name_or_path not in HYBRID_MODELS_SPARSE_WEIGHT
607 | | else HYBRID_MODELS_SPARSE_WEIGHT[model_name_or_path]
| |________________________________________________________________^ SIM401
608 | )
|
= help: Replace with `HYBRID_MODELS_SPARSE_WEIGHT.get(model_name_or_path, sparse_weight)`
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Run tests:
flair/models/entity_mention_linking.py#L1
Black format check
--- /home/runner/work/flair/flair/flair/models/entity_mention_linking.py 2024-02-02 15:09:53.021994+00:00
+++ /home/runner/work/flair/flair/flair/models/entity_mention_linking.py 2024-02-02 15:12:27.748945+00:00
@@ -441,13 +441,15 @@
}
@classmethod
def _from_state(cls, state_dict: Dict[str, Any]) -> "EntityPreprocessor":
return cls(
- preprocessor=None
- if state_dict["preprocessor"] is None
- else EntityPreprocessor._from_state(state_dict["preprocessor"]),
+ preprocessor=(
+ None
+ if state_dict["preprocessor"] is None
+ else EntityPreprocessor._from_state(state_dict["preprocessor"])
+ ),
)
class CandidateSearchIndex(ABC):
"""Base class for a candidate generator.
@@ -901,13 +903,15 @@
# Preprocess entity mentions
for entity in entities_mentions:
data_points.append(entity.data_point)
mentions.append(
- self.preprocessor.process_mention(entity.data_point.text, sentence)
- if self.preprocessor is not None
- else entity.data_point.text,
+ (
+ self.preprocessor.process_mention(entity.data_point.text, sentence)
+ if self.preprocessor is not None
+ else entity.data_point.text
+ ),
)
# Retrieve top-k concept / entity candidates
for i in range(0, len(mentions), batch_size):
candidates = self.candidate_generator.search(entity_mentions=mentions[i : i + batch_size], top_k=top_k)
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Node.js 16 actions are deprecated. Please update the following actions to use Node.js 20: actions/checkout@v3, actions/setup-python@v4, actions/cache@v3. For more information see: https://github.blog/changelog/2023-09-22-github-actions-transitioning-from-node-16-to-node-20/.
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