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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
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