|
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 <end> 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 |
|
|