11625814262

Committed 01 Nov 2024 07:14AM UTC coverage: 20.782% (+20.8%) from 0.0%

Build # 11625814262

Build Type

Pull #952

github

Committed by

web-flow

Commit Message

Merge c8385dcae into 515fe7ced

Pull Request Pull Request #952: Specify a limited test suite

Run Details

45 of 80 new or added lines in 48 files covered. (56.25%)

1537 of 7396 relevant lines covered (20.78%)

0.21 hits per line

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27.27

/pythainlp/coref/core.py

# -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: 2016-2024 PyThaiNLP Project
# SPDX-License-Identifier: Apache-2.0
from typing import List

_MODEL = None


def coreference_resolution(
    texts: List[str], model_name: str = "han-coref-v1.0", device: str = "cpu"
):
    """
    Coreference Resolution

    :param List[str] texts: list of texts to apply coreference resolution to
    :param str model_name: coreference resolution model
    :param str device: device for running coreference resolution model on\
        ("cpu", "cuda", and others)
    :return: List of texts with coreference resolution
    :rtype: List[dict]

    :Options for model_name:
        * *han-coref-v1.0* - (default) Han-Coref: Thai coreference resolution\
            by PyThaiNLP v1.0

    :Example:
    ::

        from pythainlp.coref import coreference_resolution

        print(
            coreference_resolution(
                ["Bill Gates ได้รับวัคซีน COVID-19 เข็มแรกแล้ว ระบุ ผมรู้สึกสบายมาก"]
            )
        )
        # output:
        # [
        # {'text': 'Bill Gates ได้รับวัคซีน COVID-19 เข็มแรกแล้ว ระบุ ผมรู้สึกสบายมาก',
        # 'clusters_string': [['Bill Gates', 'ผม']],
        # 'clusters': [[(0, 10), (50, 52)]]}
        # ]
    """
    global _MODEL
    if isinstance(texts, str):
        texts = [texts]

    if _MODEL is None and model_name == "han-coref-v1.0":
        from pythainlp.coref.han_coref import HanCoref

        _MODEL = HanCoref(device=device)

    if _MODEL:
        return _MODEL.predict(texts)

    return [
        {"text": text, "clusters_string": [], "clusters": []} for text in texts
    ]

1	# -- coding: utf-8 --
2	# SPDX-FileCopyrightText: 2016-2024 PyThaiNLP Project
3	# SPDX-License-Identifier: Apache-2.0
4	from typing import List	1✔
5
6	_MODEL = None	1✔
7
8
9	def coreference_resolution(	1✔
10	texts: List[str], model_name: str = "han-coref-v1.0", device: str = "cpu"
11	):
12	"""
13	Coreference Resolution
14
15	:param List[str] texts: list of texts to apply coreference resolution to
16	:param str model_name: coreference resolution model
17	:param str device: device for running coreference resolution model on\
18	("cpu", "cuda", and others)
19	:return: List of texts with coreference resolution
20	:rtype: List[dict]
21
22	:Options for model_name:
23	* han-coref-v1.0 - (default) Han-Coref: Thai coreference resolution\
24	by PyThaiNLP v1.0
25
26	:Example:
27	::
28
29	from pythainlp.coref import coreference_resolution
30
31	print(
32	coreference_resolution(
33	["Bill Gates ได้รับวัคซีน COVID-19 เข็มแรกแล้ว ระบุ ผมรู้สึกสบายมาก"]
34	)
35	)
36	# output:
37	# [
38	# {'text': 'Bill Gates ได้รับวัคซีน COVID-19 เข็มแรกแล้ว ระบุ ผมรู้สึกสบายมาก',
39	# 'clusters_string': [['Bill Gates', 'ผม']],
40	# 'clusters': [[(0, 10), (50, 52)]]}
41	# ]
42	"""
43	global _MODEL
44	if isinstance(texts, str):	×
45	texts = [texts]	×
46
NEW 47	if _MODEL is None and model_name == "han-coref-v1.0":	×
48	from pythainlp.coref.han_coref import HanCoref	×
49
NEW 50	_MODEL = HanCoref(device=device)	×
51
NEW 52	if _MODEL:	×
NEW 53	return _MODEL.predict(texts)	×
54
55	return [	×
56	{"text": text, "clusters_string": [], "clusters": []} for text in texts
57	]

PyThaiNLP / pythainlp / 11625814262

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