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

* 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

fastNLP/core/metrics.py

@@ -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,]),

fastNLP/core/utils.py

@@ -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,...

fastNLP/io/file_reader.py

@@ -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)

fastNLP/io/loader/conll.py

@@ -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

test/core/test_metrics.py

@@ -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

test/io/loader/test_conll_loader.py

@@ -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)