import os import json import jinja2 import datasets logger = datasets.logging.get_logger(__name__) _LANG = ["ar", "en", "en-ar"] _COLLECTION = ["ncwm", "ncwm-1000", "ncwm-5000", "ncwm-10000", "adgen", "dialog", "arce", "alpaca"] class JinJa2Formatter: def __init__(self, instruction: str, input: str, output=""): self.instruction = jinja2.Template(instruction) self.input = jinja2.Template(input) self.output = jinja2.Template(output) def __call__(self, example): try: return { "instruction": self.instruction.render(**example), "input": self.input.render(**example), "output": self.output.render(**example), } except Exception as e: raise ValueError(f"Error while formatting example: {example}") from e _FORMATTER = { "adgen": JinJa2Formatter( instruction="Generate advertisement for product according to its description, using the language provided in the contents.", input="Product:{{product}}\nDescription:{{description}}", output="{{ad}}", ), "dialog": JinJa2Formatter( instruction="Summarize the dialogue with respect to the provided topic. Use to end your response", input="Dialogue:{{dialogue}}\nTopic:{{topic}}", output="{{summary}}", ), "arce": JinJa2Formatter( instruction="Question:{{question}}\nChoices:{{choices.text}}", input="", output="{{choices.text[choices.label.index(answerKey)]}}", ), "ncwm": JinJa2Formatter( instruction="{{instruction}}", input="{{input}}", output="{{output}}", ), "alpaca": JinJa2Formatter( instruction="{{instruction}}", input="{{input}}", output="{{output}}", ), } _FORMATTER["ncwm-1000"] = _FORMATTER["ncwm"] _FORMATTER["ncwm-5000"] = _FORMATTER["ncwm"] _FORMATTER["ncwm-10000"] = _FORMATTER["ncwm"] class MultilingualConfig(datasets.BuilderConfig): """BuilderConfig for Alpaca""" def __init__(self, lang: str, collection: str, **kwargs): """ Args: lang: string, language for the input text collection: string, collection name **kwargs: keyword arguments forwarded to super. """ super(MultilingualConfig, self).__init__(**kwargs) self.lang = lang self.collection = collection def _get_config(collection, lang): return MultilingualConfig(lang=lang, collection=collection, name=f"{collection}_{lang}") class Multilingual(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("1.0.0") BUILDER_CONFIGS = [ _get_config("adgen", "ar"), _get_config("adgen", "en"), _get_config("dialog", "ar"), _get_config("dialog", "en"), _get_config("arce", "en"), _get_config("arce", "ar"), _get_config("ncwm", "en-ar"), _get_config("ncwm-1000", "en-ar"), _get_config("ncwm-5000", "en-ar"), _get_config("ncwm-10000", "en-ar"), _get_config("alpaca", "en"), ] BUILDER_CONFIG_CLASS = MultilingualConfig def _info(self): return datasets.DatasetInfo( features=datasets.Features( { "id": datasets.Value("string"), "instruction": datasets.Value("string"), "input": datasets.Value("string"), "output": datasets.Value("string"), } ), ) def _split_generators(self, dl_manager): splits_generators = [] for name in [ datasets.Split.TRAIN, datasets.Split.TEST, datasets.Split.VALIDATION, ]: filepath = os.path.join( self.base_path, f"{self.config.collection}_{self.config.lang}_{name}.jsonl", ) if os.path.exists(filepath): splits_generators.append(datasets.SplitGenerator(name=name, gen_kwargs={"filepath": filepath})) if not splits_generators: raise ValueError("no splits found") return splits_generators def _generate_examples(self, filepath): """This function returns the examples in the raw (text) form.""" logger.info("[multilingual] generating examples from = %s", filepath) formatter = None if f"{self.config.collection}_{self.config.lang}" in _FORMATTER: formatter = _FORMATTER[f"{self.config.collection}_{self.config.lang}"] elif f"{self.config.collection}" in _FORMATTER: formatter = _FORMATTER[f"{self.config.collection}"] else: raise ValueError( f"Formatter for the collection `{self.config.collection}` and language `{self.config.lang}` not found." ) with open(filepath, encoding="utf-8") as f: samples = [json.loads(x) for x in f.readlines()] id_ = 0 for sample in samples: yield id_, formatter(sample) | {"id": str(id_)} id_ += 1