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Fixes on tokeniser, normalisation, qualifiers and CI #329

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@Thomzoy Thomzoy commented Oct 11, 2024

Description

Regarding tokenization:

In texts, words can be split with "-" when too long. This can impede matching: dia-\nbete won't be matched by a simple "diabete" regex. To this end:

  • The EDS.Tokenizer now threats -\n as a token by itself
  • The eds.pollution can tag this token a to-be-discarded

Regarding ignore_space_tokens

With ignore_space_tokens=True, using edsnlp.utils.doc_to_text.get_text (which is used under the hood by e.g. the regex matcher) will remove linebreaks, which can be problematic in texts with enumeration without trailing spaces. E.g, get_text("Tabac\nAlcool\nSport", "TEXT", ignore_space_tokens=True) would ouput "TabacAlcoolSport"`.

Now, we replace this \n with a space when necessary

Regarding the status mapping of behavior/disorder pipes

For entities matched by those pipes, there is:

  • A _.status attribute, by default set to 1, but that can take the value 2
  • A _.detailed_status attribute, which is actually a getter that uses a mapping dictionary to get the human-readable status

When loading already-annotated docs, it can occurs that a status will be automaticaly set to None. To avoid a KeyError, when now handle this status=None case

Regarding CI

ubuntu-latest doesn't support python 3.7 anymore, so we should use ubuntu-22

Checklist

  • If this PR is a bug fix, the bug is documented in the test suite.
  • Changes were documented in the changelog (pending section).
  • If necessary, changes were made to the documentation (eg new pipeline).

@Thomzoy Thomzoy changed the title Fix handling of Span in BaseQualifier.process [DRAFT] Fix handling of Span in BaseQualifier.process Oct 11, 2024
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Coverage Report

NameStmtsMiss∆ MissCover
edsnlp/pipes/qualifiers/base.py

New missing coverage at line 178 !

     def process(self, doc: Doc) -> BaseQualifierResults:
-         doc = self.ensure_doc(doc)
         raise NotImplementedError
Was already missing at line 182
     def __call__(self, doc: Doc) -> Doc:
-         results = self.process(doc)
         raise NotImplementedError(f"{type(results)} should be used to tag the document")

532196.23%
TOTAL9450211197.77%
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edsnlp/utils/span_getters.py

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         else:
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         else:
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     if callable(span_setter):
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             elif isinstance(v, list) and all(isinstance(i, str) for i in v):

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edsnlp/utils/resources.py

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     if not verbs:
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edsnlp/utils/numbers.py

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-         return parsed

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edsnlp/utils/lazy_module.py

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             ):
-                 continue
             for import_node in node.body:

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edsnlp/utils/filter.py

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     if isinstance(label, int):
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     else:

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edsnlp/utils/bindings.py

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         return "." + path
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edsnlp/train.py

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         else:
-             sample_len = lambda idx, noise=True: 1  # noqa: E731
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             if total + num_tokens > self.grad_accumulation_max_tokens:
-                 print(
  ...
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edsnlp/processing/spark.py

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-     except AttributeError:

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edsnlp/processing/multiprocessing.py

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 if os.environ.get("TORCH_SHARING_STRATEGY"):
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         def save_align_devices_hook(pickler: Any, obj: Any):
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                     else:
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edsnlp/processing/deprecated_pipe.py

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         def converter(doc):
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-             return (
                 [{"note_id": doc._.note_id, **row} for row in res]

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edsnlp/pipes/trainable/span_linker/span_linker.py

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             if self.reference_mode == "synonym":
-                 embeds = embeds.to(new_lin.weight)
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edsnlp/pipes/trainable/ner_crf/ner_crf.py

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             if callable(self.target_span_getter):
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-                     inferred_labels.add(span.label_)
             else:

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edsnlp/pipes/trainable/layers/crf.py

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     # out: 2 * N * O
-     return (log_A.unsqueeze(-1) + log_B.unsqueeze(-3)).logsumexp(-2)
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                 torch.zeros_like(forbidden_transitions, dtype=torch.float)
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edsnlp/pipes/trainable/embeddings/transformer/transformer.py

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edsnlp/pipes/qualifiers/reported_speech/reported_speech.py

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         return "REPORTED"
-     elif token._.rspeech is False:
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-     else:
-         return None

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edsnlp/pipes/qualifiers/negation/negation.py

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edsnlp/pipes/qualifiers/hypothesis/hypothesis.py

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edsnlp/pipes/qualifiers/history/history.py

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 def history_getter(token: Union[Token, Span]) -> Optional[str]:
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-     elif token._.history is False:
-         return "CURRENT"
-     else:
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                 )
-             except ValueError:
  ...
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                 )
-             except ValueError:
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-                 birth_datetime = None
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                         )
-                     except ValueError as e:
-                         absolute_date = None
-                         logger.warning(
                             "In doc {}, the following date {} raises this error: {}. "

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edsnlp/pipes/qualifiers/family/family.py

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edsnlp/pipes/ner/tnm/tnm.py

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                 value = TNM.parse_obj(groupdict)
-             except ValidationError:
-                 value = TNM.parse_obj({})

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edsnlp/pipes/ner/tnm/model.py

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edsnlp/pipes/ner/scores/sofa/sofa.py

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edsnlp/pipes/ner/scores/elston_ellis/patterns.py

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edsnlp/pipes/ner/scores/charlson/patterns.py

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edsnlp/pipes/ner/scores/base_score.py

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edsnlp/pipes/ner/disorders/solid_tumor/solid_tumor.py

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     def process_tnm(self, doc):
-         spans = self.tnm.process(doc)
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edsnlp/pipes/ner/disorders/peripheral_vascular_disease/peripheral_vascular_disease.py

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                 if "peripheral" not in span._.assigned.keys():
-                     continue

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edsnlp/pipes/ner/disorders/diabetes/diabetes.py

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                 # Mostly FP
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             elif self.has_far_complications(span):
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         if next(iter(self.complication_matcher(context)), None) is not None:
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         return False

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edsnlp/pipes/ner/disorders/connective_tissue_disease/connective_tissue_disease.py

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edsnlp/pipes/ner/disorders/ckd/ckd.py

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             dfg_value = float(dfg_span.text.replace(",", ".").strip())
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-             logger.trace(f"DFG value couldn't be extracted from {dfg_span.text}")
-             return False

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edsnlp/pipes/ner/disorders/cerebrovascular_accident/cerebrovascular_accident.py

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edsnlp/pipes/ner/adicap/models.py

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edsnlp/pipes/misc/sections/sections.py

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         sections = dict(sections)

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edsnlp/pipes/misc/quantities/quantities.py

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     def __getitem__(self, item: int):
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     def __eq__(self, other: Any):
-         if isinstance(other, SimpleQuantity):
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         if other.unit == self.unit:
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         return self.__class__(
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             raise AttributeError(f"Unit {other_unit} not found")
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     def verify(cls, ent):
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     def __lt__(self, other: Union[SimpleQuantity, "RangeQuantity"]):
-         return max(self.convert_to(other.unit)) < min((part.value for part in other))
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     def verify(cls, ent):
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         if snippet.end != last and doclike.doc[last: snippet.end].text.strip() == "":
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                         unit_norm = self.unit_followers[unit_before.label_]
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                     last._.set(last.label_, new_value)
-                 except (AttributeError, TypeError):
-                     merged.append(ent)
             else:

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edsnlp/pipes/misc/dates/models.py

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                     else:
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edsnlp/pipes/misc/dates/dates.py

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 def excluded_or_space_getter(t):
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             )
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     """
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@Thomzoy Thomzoy force-pushed the hotfix_qualifier_process branch 3 times, most recently from 5f31166 to 4f90b63 Compare October 15, 2024 09:23
@Thomzoy Thomzoy changed the title [DRAFT] Fix handling of Span in BaseQualifier.process Small fixes Oct 15, 2024
docs/pipes/ner/disorders/index.md Outdated Show resolved Hide resolved
edsnlp/pipes/ner/behaviors/alcohol/alcohol.py Outdated Show resolved Hide resolved
edsnlp/pipes/ner/disorders/base.py Outdated Show resolved Hide resolved
edsnlp/pipes/qualifiers/base.py Show resolved Hide resolved
edsnlp/pipes/qualifiers/family/family.py Outdated Show resolved Hide resolved
tests/pipelines/ner/disorders/alcohol.py Show resolved Hide resolved
tests/pipelines/ner/disorders/alcohol.py Show resolved Hide resolved
tests/pipelines/ner/disorders/tobacco.py Show resolved Hide resolved
tests/test_language.py Show resolved Hide resolved
edsnlp/utils/doc_to_text.py Show resolved Hide resolved
@Thomzoy Thomzoy changed the title Small fixes Fixes on tokeniser, normalisation, qualifiers and CI Oct 16, 2024
@percevalw percevalw force-pushed the master branch 4 times, most recently from 2038fb9 to 232ca91 Compare November 4, 2024 21:23
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