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README.md DELETED
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- ---
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- language:
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- - de
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- - en
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mtop-intent.py DELETED
@@ -1,65 +0,0 @@
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- import json
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- import datasets
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-
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- _DESCRIPTION = "MTOP: Multilingual Task-Oriented Semantic Parsing"
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- _LANGUAGES = ["en", "de", "es", "fr", "hi", "th"]
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-
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- URL = "" # https://huggingface.co/datasets/mteb/mtop/resolve/main/"
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- _URLs = {
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- split: {
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- "train": URL + f"{split}/train.jsonl",
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- "validation": URL + f"{split}/validation.jsonl",
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- }
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- for split in _LANGUAGES
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- }
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-
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-
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- class MTOP(datasets.GeneratorBasedBuilder):
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- """MTOP Dataset."""
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-
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- BUILDER_CONFIGS = [
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- datasets.BuilderConfig(name=name, description=f"This part of my dataset covers {name} part of MTOP Dataset.",)
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- for name in _LANGUAGES
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- ]
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-
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- DEFAULT_CONFIG_NAME = "en"
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-
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- def _info(self):
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- return datasets.DatasetInfo(
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- description=_DESCRIPTION,
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- features=datasets.Features(
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- {
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- "id": datasets.Value("int64"),
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- "text": datasets.Value("string"),
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- "label": datasets.Value("int32"),
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- "label_text": datasets.Value("string"),
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- }
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- ),
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- supervised_keys=None,
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- )
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-
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- def _split_generators(self, dl_manager):
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- """Returns SplitGenerators."""
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- my_urls = _URLs[self.config.name]
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- data_dir = dl_manager.download_and_extract(my_urls)
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TRAIN,
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- # These kwargs will be passed to _generate_examples
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- gen_kwargs={"text_path": data_dir["train"]},
51
- ),
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- datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"text_path": data_dir["validation"]},),
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- datasets.SplitGenerator(
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- name=datasets.Split.TEST,
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- # These kwargs will be passed to _generate_examples
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- gen_kwargs={"text_path": data_dir["test"]},
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- ),
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- ]
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-
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- def _generate_examples(self, text_path):
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- """Yields examples."""
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- with open(text_path, encoding="utf-8") as f:
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- texts = f.readlines()
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- for i, text in enumerate(texts):
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- yield i, json.loads(text)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
mtop_intent.py DELETED
@@ -1,65 +0,0 @@
1
- import json
2
- import datasets
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-
4
- _DESCRIPTION = "MTOP: Multilingual Task-Oriented Semantic Parsing"
5
- _LANGUAGES = ["en", "de", "es", "fr", "hi", "th"]
6
-
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- URL = "" # https://huggingface.co/datasets/mteb/mtop/resolve/main/"
8
- _URLs = {
9
- split: {
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- "train": URL + f"{split}/train.jsonl",
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- "test": URL + f"{split}/test.jsonl",
12
- "validation": URL + f"{split}/validation.jsonl",
13
- }
14
- for split in _LANGUAGES
15
- }
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-
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-
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- class MTOP_INTENT(datasets.GeneratorBasedBuilder):
19
- """MTOP Dataset."""
20
-
21
- BUILDER_CONFIGS = [
22
- datasets.BuilderConfig(name=name, description=f"This part of my dataset covers {name} part of MTOP Dataset.",)
23
- for name in _LANGUAGES
24
- ]
25
-
26
- DEFAULT_CONFIG_NAME = "en"
27
-
28
- def _info(self):
29
- return datasets.DatasetInfo(
30
- description=_DESCRIPTION,
31
- features=datasets.Features(
32
- {
33
- "id": datasets.Value("int64"),
34
- "text": datasets.Value("string"),
35
- "label": datasets.Value("int32"),
36
- "label_text": datasets.Value("string"),
37
- }
38
- ),
39
- supervised_keys=None,
40
- )
41
-
42
- def _split_generators(self, dl_manager):
43
- """Returns SplitGenerators."""
44
- my_urls = _URLs[self.config.name]
45
- data_dir = dl_manager.download_and_extract(my_urls)
46
- return [
47
- datasets.SplitGenerator(
48
- name=datasets.Split.TRAIN,
49
- # These kwargs will be passed to _generate_examples
50
- gen_kwargs={"text_path": data_dir["train"]},
51
- ),
52
- datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"text_path": data_dir["validation"]},),
53
- datasets.SplitGenerator(
54
- name=datasets.Split.TEST,
55
- # These kwargs will be passed to _generate_examples
56
- gen_kwargs={"text_path": data_dir["test"]},
57
- ),
58
- ]
59
-
60
- def _generate_examples(self, text_path):
61
- """Yields examples."""
62
- with open(text_path, encoding="utf-8") as f:
63
- texts = f.readlines()
64
- for i, text in enumerate(texts):
65
- yield i, json.loads(text)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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