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[new] add seperator for conll loader (#293)

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* add ConfusionMatrix, ConfusionMatrixMetric

* add confusionmatrix to utils

* add ConfusionMatrixmetric

* add ConfusionMatrixMetric

* init for test

* begin test

* test finish

* doc finish

* revised confusion

* revised two

* revise two

* add sep for conll loader

* with remote

* withdraw some update

* finish merge

* update test

* update test

* to avoid none situation
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ROGERDJQ 2020-05-03 19:46:11 +08:00 committed by GitHub
parent ae7b916355
commit 4e95989e97
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6 changed files with 24 additions and 9 deletions
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2
fastNLP/core/metrics.py
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@ -316,6 +316,7 @@ class ConfusionMatrixMetric(MetricBase):
print_ratio=False
):
r"""
:param vocab: vocab词表类,要求有to_word()方法。
:param pred: 参数映射表中 `pred` 的映射关系，None表示映射关系为 `pred` -> `pred`
:param target: 参数映射表中 `target` 的映射关系，None表示映射关系为 `target` -> `target`
@ -332,7 +333,6 @@ class ConfusionMatrixMetric(MetricBase):
def evaluate(self, pred, target, seq_len=None):
r"""
evaluate函数将针对一个批次的预测结果做评价指标的累计
:param torch.Tensor pred: 预测的tensor, tensor的形状可以是torch.Size([B,]), torch.Size([B, n_classes]),
torch.Size([B, max_len]), 或者torch.Size([B, max_len, n_classes])
:param torch.Tensor target: 真实值的tensor, tensor的形状可以是Element's can be: torch.Size([B,]),

2
fastNLP/core/utils.py
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@ -62,6 +62,7 @@ class ConfusionMatrix:
target = [2,2,1]
confusion.add_pred_target(pred, target)
print(confusion)
target 1 2 3 all
pred
1 0 1 0 1
@ -157,7 +158,6 @@ class ConfusionMatrix:
(k, str(k if self.vocab == None else self.vocab.to_word(k)))
for k in totallabel
])
for label, idx in zip(totallabel, range(lenth)):
idx2row[
label] = idx # 建立一个临时字典，key:vocab的index, value: 行列index 1,3,5...->0,1,2,...

7
fastNLP/io/file_reader.py
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@ -81,12 +81,13 @@ def _read_json(path, encoding='utf-8', fields=None, dropna=True):
yield line_idx, _res
def _read_conll(path, encoding='utf-8', indexes=None, dropna=True):
def _read_conll(path, encoding='utf-8',sep=None, indexes=None, dropna=True):
r"""
Construct a generator to read conll items.
:param path: file path
:param encoding: file's encoding, default: utf-8
:param sep: seperator
:param indexes: conll object's column indexes that needed, if None, all columns are needed. default: None
:param dropna: weather to ignore and drop invalid data,
:if False, raise ValueError when reading invalid data. default: True
@ -105,7 +106,7 @@ def _read_conll(path, encoding='utf-8', indexes=None, dropna=True):
sample = []
start = next(f).strip()
if start != '':
sample.append(start.split())
sample.append(start.split(sep)) if sep else sample.append(start.split())
for line_idx, line in enumerate(f, 1):
line = line.strip()
if line == '':
@ -123,7 +124,7 @@ def _read_conll(path, encoding='utf-8', indexes=None, dropna=True):
elif line.startswith('#'):
continue
else:
sample.append(line.split())
sample.append(line.split(sep)) if sep else sample.append(line.split())
if len(sample) > 0:
try:
res = parse_conll(sample)

6
fastNLP/io/loader/conll.py
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@ -55,10 +55,11 @@ class ConllLoader(Loader):
"""
def __init__(self, headers, indexes=None, dropna=True):
def __init__(self, headers, sep=None, indexes=None, dropna=True):
r"""
:param list headers: 每一列数据的名称，需为List or Tuple of str。``header`` 与 ``indexes`` 一一对应
:param list sep: 指定分隔符，默认为制表符
:param list indexes: 需要保留的数据列下标，从0开始。若为 ``None`` ，则所有列都保留。Default: ``None``
:param bool dropna: 是否忽略非法数据，若 ``False`` ，遇到非法数据时抛出 ``ValueError`` 。Default: ``True``
"""
@ -68,6 +69,7 @@ class ConllLoader(Loader):
'invalid headers: {}, should be list of strings'.format(headers))
self.headers = headers
self.dropna = dropna
self.sep=sep
if indexes is None:
self.indexes = list(range(len(self.headers)))
else:
@ -83,7 +85,7 @@ class ConllLoader(Loader):
:return: DataSet
"""
ds = DataSet()
for idx, data in _read_conll(path, indexes=self.indexes, dropna=self.dropna):
for idx, data in _read_conll(path,sep=self.sep, indexes=self.indexes, dropna=self.dropna):
ins = {h: data[i] for i, h in enumerate(self.headers)}
ds.append(Instance(**ins))
return ds

7
test/core/test_metrics.py
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@ -45,6 +45,7 @@ def _convert_res_to_fastnlp_res(metric_result):
return allen_result
class TestConfusionMatrixMetric(unittest.TestCase):
def test_ConfusionMatrixMetric1(self):
pred_dict = {"pred": torch.zeros(4,3)}
@ -56,6 +57,7 @@ class TestConfusionMatrixMetric(unittest.TestCase):
def test_ConfusionMatrixMetric2(self):
# (2) with corrupted size
with self.assertRaises(Exception):
pred_dict = {"pred": torch.zeros(4, 3, 2)}
target_dict = {'target': torch.zeros(4)}
@ -78,7 +80,6 @@ class TestConfusionMatrixMetric(unittest.TestCase):
print(metric.get_metric())
def test_ConfusionMatrixMetric4(self):
# (4) check reset
metric = ConfusionMatrixMetric()
@ -91,6 +92,7 @@ class TestConfusionMatrixMetric(unittest.TestCase):
def test_ConfusionMatrixMetric5(self):
# (5) check numpy array is not acceptable
with self.assertRaises(Exception):
metric = ConfusionMatrixMetric()
pred_dict = {"pred": np.zeros((4, 3, 2))}
@ -122,6 +124,7 @@ class TestConfusionMatrixMetric(unittest.TestCase):
metric(pred_dict=pred_dict, target_dict=target_dict)
print(metric.get_metric())
def test_duplicate(self):
# 0.4.1的潜在bug，不能出现形参重复的情况
metric = ConfusionMatrixMetric(pred='predictions', target='targets')
@ -130,6 +133,7 @@ class TestConfusionMatrixMetric(unittest.TestCase):
metric(pred_dict=pred_dict, target_dict=target_dict)
print(metric.get_metric())
def test_seq_len(self):
N = 256
seq_len = torch.zeros(N).long()
@ -155,6 +159,7 @@ class TestConfusionMatrixMetric(unittest.TestCase):
print(metric.get_metric())
class TestAccuracyMetric(unittest.TestCase):
def test_AccuracyMetric1(self):
# (1) only input, targets passed

9
test/io/loader/test_conll_loader.py
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@ -2,7 +2,7 @@
import unittest
import os
from fastNLP.io.loader.conll import MsraNERLoader, PeopleDailyNERLoader, WeiboNERLoader, \
Conll2003Loader
Conll2003Loader, ConllLoader
class TestMSRANER(unittest.TestCase):
@ -35,3 +35,10 @@ class TestConllLoader(unittest.TestCase):
db = Conll2003Loader().load('test/data_for_tests/io/conll2003')
print(db)
class TestConllLoader(unittest.TestCase):
def test_sep(self):
headers = [
'raw_words', 'ner',
]
db = ConllLoader(headers = headers,sep="\n").load('test/data_for_tests/io/MSRA_NER')
print(db)