release for of en2pl with massive filtering and en2es without massive filtering

README.md

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+---
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: locale
+    dtype: string
+  - name: origin
+    dtype: string
+  - name: partition
+    dtype: string
+  - name: translation_utt
+    dtype:
+      translation:
+        languages:
+        - en
+        - pl
+  - name: translation_xml
+    dtype:
+      translation:
+        languages:
+        - en
+        - pl
+  - name: src_bio
+    dtype: string
+  - name: tgt_bio
+    dtype: string
+task_categories:
+- translation
+language:
+- en
+- pl
+- de
+- es
+- sv
+tags:
+- machine translation
+- nlu
+- natural-language-understanding
+- virtual assistant
+pretty_name: Machine translation for NLU with slot transfer
+size_categories:
+- 10K<n<100K
+license: cc-by-4.0
+---
+# Machine translation dataset for NLU (Virual Assistant) with slot transfer between languages
+## Dataset Summary
+
+Disclaimer: This is for research purposes only. Please have a look at the license section below. Some of the datasets used to construct IVA_MT have an unknown license.
+
+IVA_MT is a machine translation dataset that can be used to train, adapt and evaluate MT models used in Virtual Assistant NLU context (e.g. to translate trainig corpus of NLU).
+
+## Dataset Composition
+
+### en-pl
+
+| Corpus                                                               | Train  | Dev   | Test  |
+|----------------------------------------------------------------------|--------|-------|-------|
+| [Massive 1.1](https://huggingface.co/datasets/AmazonScience/massive) | 11514  | 2033  | 2974  |
+| [Leyzer 0.2.0](https://github.com/cartesinus/leyzer/tree/0.2.0)      | 3974   | 701   | 1380  |
+| [OpenSubtitles from OPUS](https://opus.nlpl.eu/OpenSubtitles-v1.php) | 2329   | 411   | 500   |
+| [KDE from OPUS](https://opus.nlpl.eu/KDE4.php)                       | 1154   | 241   | 241   |
+| [CCMatrix from Opus](https://opus.nlpl.eu/CCMatrix.php)              | 1096   | 232   | 237   |
+| [Ubuntu from OPUS](https://opus.nlpl.eu/Ubuntu.php)                  | 281    | 60    | 59    |
+| [Gnome from OPUS](https://opus.nlpl.eu/GNOME.php)                    | 14     | 3     | 3     |
+| *total*                                                              | 20362  | 3681  | 5394  |
+
+### en-de
+
+| Corpus                                                               | Train  | Dev   | Test  |
+|----------------------------------------------------------------------|--------|-------|-------|
+| [Massive 1.1](https://huggingface.co/datasets/AmazonScience/massive) | 7536   | 1346  | 1955  |
+
+### en-es
+
+| Corpus                                                               | Train  | Dev   | Test  |
+|----------------------------------------------------------------------|--------|-------|-------|
+| [Massive 1.1](https://huggingface.co/datasets/AmazonScience/massive) | 8415   | 1526  | 2202  |
+
+### en-sv
+
+| Corpus                                                               | Train  | Dev   | Test  |
+|----------------------------------------------------------------------|--------|-------|-------|
+| [Massive 1.1](https://huggingface.co/datasets/AmazonScience/massive) | 7540   | 1360  | 1921  |
+
+
+## Tools
+Scripts used to generate this dataset can be found on [github](https://github.com/cartesinus/iva_mt).
+
+## License
+This is a composition of 7 datasets, and the license is as defined in original release:
+- MASSIVE: [CC-BY 4.0](https://huggingface.co/datasets/AmazonScience/massive/blob/main/LICENSE)
+- Leyzer: [CC BY-NC 4.0](https://github.com/cartesinus/leyzer/blob/master/LICENSE)
+- OpenSubtitles: unknown
+- KDE: [GNU Public License](https://l10n.kde.org/about.php)
+- CCMatrix: no license given, therefore assuming it is LASER project license [BSD](https://github.com/facebookresearch/LASER/blob/main/LICENSE)
+- Ubuntu: [GNU Public License](https://help.launchpad.net/Legal)
+- Gnome: unknown

iva_mt_wslot-exp.py

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+# coding=utf-8
+"""IVA_MT_WSLOT"""
+
+
+import datasets
+import json
+
+
+_DESCRIPTION = """\
+"""
+
+_URL = "https://github.com/cartesinus/iva_mt/raw/main/release/0.2/iva_mt_wslot-dataset-0.2.1.tar.gz"
+
+_LANGUAGE_PAIRS = ["en-pl", "en-de", "en-es", "en-sv"]
+
+class IVA_MTConfig(datasets.BuilderConfig):
+    """BuilderConfig for IVA_MT"""
+
+    def __init__(self, language_pair, **kwargs):
+        super().__init__(**kwargs)
+        """
+
+        Args:
+            language_pair: language pair, you want to load
+            **kwargs: keyword arguments forwarded to super.
+        """
+        self.language_pair = language_pair
+
+
+class IVA_MT(datasets.GeneratorBasedBuilder):
+    """OPUS-100 is English-centric, meaning that all training pairs include English on either the source or target side."""
+
+    VERSION = datasets.Version("0.2.1")
+
+    BUILDER_CONFIG_CLASS = IVA_MTConfig
+    BUILDER_CONFIGS = [
+        IVA_MTConfig(name=pair, description=_DESCRIPTION, language_pair=pair)
+        for pair in _LANGUAGE_PAIRS
+    ]
+
+    def _info(self):
+        src_tag, tgt_tag = self.config.language_pair.split("-")
+        return datasets.DatasetInfo(
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("int64"),
+                    "locale": datasets.Value("string"),
+                    "origin": datasets.Value("string"),
+                    "partition": datasets.Value("string"),
+                    "translation_utt": datasets.features.Translation(languages=(src_tag, tgt_tag)),
+                    "translation_xml": datasets.features.Translation(languages=(src_tag, tgt_tag)),
+                    "src_bio": datasets.Value("string"),
+                    "tgt_bio": datasets.Value("string")
+                }
+            ),
+            supervised_keys=(src_tag, tgt_tag),
+        )
+
+    def _split_generators(self, dl_manager):
+
+        lang_pair = self.config.language_pair
+        src_tag, tgt_tag = lang_pair.split("-")
+
+        archive = dl_manager.download(_URL)
+
+        data_dir = "/".join(["iva_mt_wslot-dataset", "0.2.1", lang_pair])
+        output = []
+
+        test = datasets.SplitGenerator(
+            name=datasets.Split.TEST,
+            # These kwargs will be passed to _generate_examples
+            gen_kwargs={
+                "filepath": f"{data_dir}/iva_mt_wslot-{lang_pair}-test.jsonl",
+                "files": dl_manager.iter_archive(archive),
+                "split": "test",
+            },
+        )
+
+        output.append(test)
+
+        train = datasets.SplitGenerator(
+            name=datasets.Split.TRAIN,
+            gen_kwargs={
+                "filepath": f"{data_dir}/iva_mt_wslot-{lang_pair}-train.jsonl",
+                "files": dl_manager.iter_archive(archive),
+                "split": "train",
+            },
+        )
+
+        output.append(train)
+
+        valid = datasets.SplitGenerator(
+            name=datasets.Split.VALIDATION,
+            # These kwargs will be passed to _generate_examples
+            gen_kwargs={
+                "filepath": f"{data_dir}/iva_mt_wslot-{lang_pair}-valid.jsonl",
+                "files": dl_manager.iter_archive(archive),
+                "split": "valid",
+            },
+        )
+
+        output.append(valid)
+
+        return output
+
+    def _generate_examples(self, filepath, files, split):
+        """Yields examples."""
+        src_tag, tgt_tag = self.config.language_pair.split("-")
+        key_ = 0
+        lang = _LANGUAGE_PAIRS.copy()
+
+        for path, f in files:
+            l = path.split("/")[-1].split("-")[1].replace('2', '-')
+
+            if l != self.config.language_pair:
+                continue
+
+            # Read the file
+            lines = f.read().decode(encoding="utf-8").split("\n")
+
+            for line in lines:
+                if not line:
+                    continue
+
+                data = json.loads(line)
+
+                if data["partition"] != split:
+                    continue
+
+                yield key_, {
+                    "id": data["id"],
+                    "locale": data["locale"],
+                    "origin": data["origin"],
+                    "partition": data["partition"],
+                    "translation_utt": {src_tag: str(data['src_utt']), tgt_tag: str(data['tgt_utt'])},
+                    "translation_xml": {src_tag: str(data['src_xml']), tgt_tag: str(data['tgt_xml'])},
+                    "src_bio": str(data['src_bio']),
+                    "tgt_bio": str(data['tgt_bio'])
+                }
+
+                key_ += 1