update

.history/IE-SemParse_20230707224435.py

@@ -0,0 +1,154 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'iTOP',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+class IESemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IESemParseConfig, self).__init__(**kwargs)
+        
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+        
+        self._URLS = [os.path.join(_URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IESemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IESemParseConfig
+    BUILDER_CONFIGS = [
+        IESemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset = dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "premise": datasets.Value("string"),
+                "hypothesis": datasets.Value("string"),
+                "label": datasets.ClassLabel(names=["entailment", "neutral", "contradiction"]),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+        
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                            "split_key": "train", 
+                            "file_path": downloaded_file, 
+                            "data_format": "IE-SemParse"
+                            }
+                ,
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                            "split_key": "test", 
+                            "files": downloaded_file, 
+                            "data_format": "IE-SemParse"
+                            },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                            "split_key": "val", 
+                            "files": downloaded_file, 
+                            "data_format": "IE-SemParse"
+                    },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k:v for k,v in data.items()
+            }

.history/IE-SemParse_20230707232421.py

@@ -0,0 +1,162 @@
+# coding=utf-8
+
+
+# Lint as: python3
+"""IndicXNLI: The Cross-Lingual NLI Corpus for Indic Languages."""
+
+
+import os
+import json
+
+import pandas as pd
+
+import datasets
+
+from datasets import DownloadManager
+
+
+_CITATION = """\
+@misc{aggarwal2023evaluating,
+      title={Evaluating Inter-Bilingual Semantic Parsing for Indian Languages}, 
+      author={Divyanshu Aggarwal and Vivek Gupta and Anoop Kunchukuttan},
+      year={2023},
+      eprint={2304.13005},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+    IE-SemParse is an Inter-bilingual Seq2seq Semantic parsing dataset for 11 distinct Indian languages
+"""
+
+_LANGUAGES = (
+    'hi',
+    'bn',
+    'mr',
+    'as',
+    'ta',
+    'te',
+    'or',
+    'ml',
+    'pa',
+    'gu',
+    'kn'
+)
+
+
+_DATASETS = (
+    'iTOP',
+    'indic-atis',
+    'indic-TOP'
+)
+
+
+_URL = "https://huggingface.co/datasets/Divyanshu/IE-SemParse/resolve/main/"
+
+class IESemParseConfig(datasets.BuilderConfig):
+    """BuilderConfig for IE-SemParse."""
+
+    def __init__(self, dataset: str, language: str, **kwargs):
+        """BuilderConfig for IE-SemParse.
+
+        Args:
+        language: One of hi, bn, mr, as, ta, te, or, ml, pa, gu, kn
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(IESemParseConfig, self).__init__(**kwargs)
+        
+        self.dataset = dataset
+        self.language = language
+        self.languages = _LANGUAGES
+        self.datasets = _DATASETS
+        
+        self._URLS = [os.path.join(_URL, "unfiltered_data", dataset, f"{language}.json")]
+
+
+class IESemParse(datasets.GeneratorBasedBuilder):
+    """IE-SemParse: Inter-Bilingual Semantic Parsing Dataset for Indic Languages. Version 1.0."""
+
+    VERSION = datasets.Version("1.0.0", "")
+    BUILDER_CONFIG_CLASS = IESemParseConfig
+    BUILDER_CONFIGS = [
+        IESemParseConfig(
+            name=f"{dataset}_{language}",
+            language=language,
+            dataset = dataset,
+            version=datasets.Version("1.0.0", ""),
+            description=f"Plain text import of IE-SemParse for the {language} language for {dataset} dataset",
+        )
+        for language, dataset in zip(_LANGUAGES, _DATASETS)
+    ]
+
+    def _info(self):
+        dl_manager = datasets.DownloadManager()
+        
+        urls_to_download = self.config._URLS
+        
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+        
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+        
+        
+        features = datasets.Features(
+            { k: datasets.Value("string") for k in data.keys()}
+        )
+   
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            # No default supervised_keys (as we have to pass both premise
+            # and hypothesis as input).
+            supervised_keys=None,
+            homepage="https://github.com/divyanshuaggarwal/IE-SemParse",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = self.config._URLS
+        
+        downloaded_file = dl_manager.download_and_extract(urls_to_download)[0]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                            "split_key": "train", 
+                            "file_path": downloaded_file, 
+                            "data_format": "IE-SemParse"
+                            }
+                ,
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                            "split_key": "test", 
+                            "files": downloaded_file, 
+                            "data_format": "IE-SemParse"
+                            },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                            "split_key": "val", 
+                            "files": downloaded_file, 
+                            "data_format": "IE-SemParse"
+                    },
+            ),
+        ]
+
+    def _generate_examples(self, data_format, filepath):
+        """This function returns the examples in the raw (text) form."""
+
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+
+        for idx, row in enumerate(data):
+            yield idx, {
+                k:v for k,v in data.items()
+            }

IE-SemParse.py

@@ -91,13 +91,21 @@ class IESemParse(datasets.GeneratorBasedBuilder):
     ]
 
     def _info(self):
+        dl_manager = datasets.DownloadManager()
+        
+        urls_to_download = self.config._URLS
+        
+        filepath = dl_manager.download_and_extract(urls_to_download)[0]
+        
+        with open(filepath, "r") as f:
+            data = json.load(f)
+            data = data[list(data.keys())[0]]
+        
+        
         features = datasets.Features(
-            {
-                "premise": datasets.Value("string"),
-                "hypothesis": datasets.Value("string"),
-                "label": datasets.ClassLabel(names=["entailment", "neutral", "contradiction"]),
-            }
+            { k: datasets.Value("string") for k in data.keys()}
         )
+   
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
             features=features,