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dmahata commited on
Commit
bc07c01
1 Parent(s): 6e3c7f8

Update inspec.py

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Files changed (1) hide show
  1. inspec.py +16 -37
inspec.py CHANGED
@@ -1,20 +1,14 @@
1
- import csv
2
  import json
3
- import os
4
 
5
  import datasets
6
- from typing import List, Any
7
 
8
  # _SPLIT = ['train', 'test', 'valid']
9
  _CITATION = """\
10
- author: amardeep
11
  """
12
 
13
-
14
  _DESCRIPTION = """\
15
- This new dataset is designed to solve kp NLP task and is crafted with a lot of care.
16
- """
17
 
 
18
 
19
  _HOMEPAGE = ""
20
 
@@ -34,37 +28,36 @@ _URLS = {
34
  class TestLDKP(datasets.GeneratorBasedBuilder):
35
  """TODO: Short description of my dataset."""
36
 
37
- VERSION = datasets.Version("1.1.0")
38
 
39
  BUILDER_CONFIGS = [
40
- datasets.BuilderConfig(name="extraction", version=VERSION, description="This part of my dataset covers long document"),
41
- datasets.BuilderConfig(name="generation", version=VERSION, description="This part of my dataset covers abstract only"),
42
- datasets.BuilderConfig(name="raw", version=VERSION, description="This part of my dataset covers abstract only"),
43
- datasets.BuilderConfig(name="ldkp_generation", version=VERSION, description="This part of my dataset covers abstract only"),
44
- datasets.BuilderConfig(name="ldkp_extraction", version=VERSION, description="This part of my dataset covers abstract only"),
45
-
46
  ]
47
 
48
- DEFAULT_CONFIG_NAME = "extraction"
49
 
50
  def _info(self):
51
- if self.config.name == "extraction" or self.config.name == "ldkp_extraction": # This is the name of the configuration selected in BUILDER_CONFIGS above
52
  features = datasets.Features(
53
  {
54
  "id": datasets.Value("int64"),
55
  "document": datasets.features.Sequence(datasets.Value("string")),
56
  "doc_bio_tags": datasets.features.Sequence(datasets.Value("string"))
57
-
58
  }
59
  )
60
- elif self.config.name == "generation" or self.config.name == "ldkp_generation":
61
  features = datasets.Features(
62
  {
63
  "id": datasets.Value("int64"),
64
  "document": datasets.features.Sequence(datasets.Value("string")),
65
  "extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
66
  "abstractive_keyphrases": datasets.features.Sequence(datasets.Value("string"))
67
-
68
  }
69
  )
70
  else:
@@ -78,18 +71,17 @@ class TestLDKP(datasets.GeneratorBasedBuilder):
78
  "other_metadata": datasets.features.Sequence(
79
  {
80
  "text": datasets.features.Sequence(datasets.Value("string")),
81
- "bio_tags":datasets.features.Sequence(datasets.Value("string"))
82
  }
83
  )
84
 
85
-
86
  }
87
  )
88
  return datasets.DatasetInfo(
89
  # This is the description that will appear on the datasets page.
90
  description=_DESCRIPTION,
91
  # This defines the different columns of the dataset and their types
92
- features=features,
93
  homepage=_HOMEPAGE,
94
  # License for the dataset if available
95
  license=_LICENSE,
@@ -98,7 +90,7 @@ class TestLDKP(datasets.GeneratorBasedBuilder):
98
  )
99
 
100
  def _split_generators(self, dl_manager):
101
-
102
  data_dir = dl_manager.download_and_extract(_URLS)
103
  return [
104
  datasets.SplitGenerator(
@@ -139,20 +131,7 @@ class TestLDKP(datasets.GeneratorBasedBuilder):
139
  "document": data["document"],
140
  "doc_bio_tags": data["doc_bio_tags"]
141
  }
142
- elif self.config.name == "ldkp_extraction":
143
- yield key, {
144
- "id": data['paper_id'],
145
- "document": data["document"]+data["other_metadata"]['text'],
146
- "doc_bio_tags": data["document_tags"] + data["other_metadata"]['bio_tags']
147
- }
148
- elif self.config.name == "ldkp_generation":
149
- yield key, {
150
- "id": data['paper_id'],
151
- "document": data["document"]+data["other_metadata"]['text'],
152
- "extractive_keyphrases": data["extractive_keyphrases"],
153
- "abstractive_keyphrases": data["abstractive_keyphrases"]
154
- }
155
- elif self.config.name == "generation":
156
  yield key, {
157
  "id": data['paper_id'],
158
  "document": data["document"],
 
 
1
  import json
 
2
 
3
  import datasets
 
4
 
5
  # _SPLIT = ['train', 'test', 'valid']
6
  _CITATION = """\
 
7
  """
8
 
 
9
  _DESCRIPTION = """\
 
 
10
 
11
+ """
12
 
13
  _HOMEPAGE = ""
14
 
 
28
  class TestLDKP(datasets.GeneratorBasedBuilder):
29
  """TODO: Short description of my dataset."""
30
 
31
+ VERSION = datasets.Version("0.1")
32
 
33
  BUILDER_CONFIGS = [
34
+ datasets.BuilderConfig(name="extraction", version=VERSION,
35
+ description="This part of my dataset covers extraction"),
36
+ datasets.BuilderConfig(name="generation", version=VERSION,
37
+ description="This part of my dataset covers generation"),
38
+ datasets.BuilderConfig(name="raw", version=VERSION, description="This part of my dataset covers the raw data"),
 
39
  ]
40
 
41
+ DEFAULT_CONFIG_NAME = "extraction"
42
 
43
  def _info(self):
44
+ if self.config.name == "extraction": # This is the name of the configuration selected in BUILDER_CONFIGS above
45
  features = datasets.Features(
46
  {
47
  "id": datasets.Value("int64"),
48
  "document": datasets.features.Sequence(datasets.Value("string")),
49
  "doc_bio_tags": datasets.features.Sequence(datasets.Value("string"))
50
+
51
  }
52
  )
53
+ elif self.config.name == "generation":
54
  features = datasets.Features(
55
  {
56
  "id": datasets.Value("int64"),
57
  "document": datasets.features.Sequence(datasets.Value("string")),
58
  "extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
59
  "abstractive_keyphrases": datasets.features.Sequence(datasets.Value("string"))
60
+
61
  }
62
  )
63
  else:
 
71
  "other_metadata": datasets.features.Sequence(
72
  {
73
  "text": datasets.features.Sequence(datasets.Value("string")),
74
+ "bio_tags": datasets.features.Sequence(datasets.Value("string"))
75
  }
76
  )
77
 
 
78
  }
79
  )
80
  return datasets.DatasetInfo(
81
  # This is the description that will appear on the datasets page.
82
  description=_DESCRIPTION,
83
  # This defines the different columns of the dataset and their types
84
+ features=features,
85
  homepage=_HOMEPAGE,
86
  # License for the dataset if available
87
  license=_LICENSE,
 
90
  )
91
 
92
  def _split_generators(self, dl_manager):
93
+
94
  data_dir = dl_manager.download_and_extract(_URLS)
95
  return [
96
  datasets.SplitGenerator(
 
131
  "document": data["document"],
132
  "doc_bio_tags": data["doc_bio_tags"]
133
  }
134
+ elif self.config.name == "generation":
 
 
 
 
 
 
 
 
 
 
 
 
 
135
  yield key, {
136
  "id": data['paper_id'],
137
  "document": data["document"],