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Move scores per type handling into util function (#8590)

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Ines Montani 2021-07-06 21:02:37 +10:00 committed by GitHub
parent 5fd0b5207e
commit 327f83573a
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1 changed files with 34 additions and 23 deletions
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57
spacy/cli/evaluate.py
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@ -1,4 +1,4 @@
from typing import Optional, List, Dict
from typing import Optional, List, Dict, Any, Union
from wasabi import Printer
from pathlib import Path
import re
@ -60,8 +60,8 @@ def evaluate(
displacy_path: Optional[Path] = None,
displacy_limit: int = 25,
silent: bool = True,
spans_key="sc",
) -> Scorer:
spans_key: str = "sc",
) -> Dict[str, Any]:
msg = Printer(no_print=silent, pretty=not silent)
fix_random_seed()
setup_gpu(use_gpu)
@ -112,7 +112,37 @@ def evaluate(
data[re.sub(r"[\s/]", "_", key.lower())] = scores[key]
msg.table(results, title="Results")
data = handle_scores_per_type(scores, data, spans_key=spans_key, silent=silent)
if displacy_path:
factory_names = [nlp.get_pipe_meta(pipe).factory for pipe in nlp.pipe_names]
docs = list(nlp.pipe(ex.reference.text for ex in dev_dataset[:displacy_limit]))
render_deps = "parser" in factory_names
render_ents = "ner" in factory_names
render_parses(
docs,
displacy_path,
model_name=model,
limit=displacy_limit,
deps=render_deps,
ents=render_ents,
)
msg.good(f"Generated {displacy_limit} parses as HTML", displacy_path)
if output_path is not None:
srsly.write_json(output_path, data)
msg.good(f"Saved results to {output_path}")
return data
def handle_scores_per_type(
scores: Union[Scorer, Dict[str, Any]],
data: Dict[str, Any] = {},
*,
spans_key: str = "sc",
silent: bool = False,
) -> Dict[str, Any]:
msg = Printer(no_print=silent, pretty=not silent)
if "morph_per_feat" in scores:
if scores["morph_per_feat"]:
print_prf_per_type(msg, scores["morph_per_feat"], "MORPH", "feat")
@ -139,26 +169,7 @@ def evaluate(
if scores["cats_auc_per_type"]:
print_textcats_auc_per_cat(msg, scores["cats_auc_per_type"])
data["cats_auc_per_type"] = scores["cats_auc_per_type"]
if displacy_path:
factory_names = [nlp.get_pipe_meta(pipe).factory for pipe in nlp.pipe_names]
docs = list(nlp.pipe(ex.reference.text for ex in dev_dataset[:displacy_limit]))
render_deps = "parser" in factory_names
render_ents = "ner" in factory_names
render_parses(
docs,
displacy_path,
model_name=model,
limit=displacy_limit,
deps=render_deps,
ents=render_ents,
)
msg.good(f"Generated {displacy_limit} parses as HTML", displacy_path)
if output_path is not None:
srsly.write_json(output_path, data)
msg.good(f"Saved results to {output_path}")
return data
return scores
def render_parses(