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# Copyright (c) OpenMMLab. All rights reserved.
from functools import partial
from datasets import load_dataset
from torch.utils.data import ConcatDataset
from xtuner.dataset import process_hf_dataset
from xtuner.dataset.collate_fns import default_collate_fn
from xtuner.dataset.map_fns import (alpaca_map_fn, alpaca_zh_map_fn,
template_map_fn_factory)
from xtuner.utils import PROMPT_TEMPLATE
def alpaca_enzh_dataset(tokenizer,
path_en='tatsu-lab/alpaca',
path_zh='silk-road/alpaca-data-gpt4-chinese',
max_length=2048,
prompt_template=PROMPT_TEMPLATE.default,
remove_unused_columns=True,
pack_to_max_length=True):
alpaca = alpaca_dataset(
tokenizer,
path=path_en,
max_length=max_length,
prompt_template=prompt_template,
shuffle_before_pack=True,
remove_unused_columns=remove_unused_columns,
pack_to_max_length=pack_to_max_length)
alpaca_zh = alpaca_zh_dataset(
tokenizer,
path=path_zh,
max_length=max_length,
prompt_template=prompt_template,
shuffle_before_pack=True,
remove_unused_columns=remove_unused_columns,
pack_to_max_length=pack_to_max_length)
dataset = ConcatDataset([alpaca, alpaca_zh])
return dataset
def alpaca_enzh_data_collator(return_hf_format=False):
return partial(default_collate_fn, return_hf_format=return_hf_format)
def alpaca_zh_dataset(tokenizer,
path='silk-road/alpaca-data-gpt4-chinese',
max_length=2048,
prompt_template=PROMPT_TEMPLATE.default,
remove_unused_columns=True,
pack_to_max_length=True):
template_map_fn = template_map_fn_factory(template=prompt_template)
dataset_org = load_dataset(path)
dataset = process_hf_dataset(
dataset=dataset_org,
tokenizer=tokenizer,
max_length=max_length,
dataset_map_fn=alpaca_zh_map_fn,
template_map_fn=template_map_fn,
remove_unused_columns=remove_unused_columns,
shuffle_before_pack=True,
pack_to_max_length=pack_to_max_length)
return dataset
def alpaca_zh_data_collator(return_hf_format=False):
return partial(default_collate_fn, return_hf_format=return_hf_format)
def alpaca_dataset(tokenizer,
path='tatsu-lab/alpaca',
max_length=2048,
prompt_template=PROMPT_TEMPLATE.default,
remove_unused_columns=True,
pack_to_max_length=True):
template_map_fn = template_map_fn_factory(template=prompt_template)
dataset_org = load_dataset(path)
dataset = process_hf_dataset(
dataset=dataset_org,
tokenizer=tokenizer,
max_length=max_length,
dataset_map_fn=alpaca_map_fn,
template_map_fn=template_map_fn,
remove_unused_columns=remove_unused_columns,
shuffle_before_pack=True,
pack_to_max_length=pack_to_max_length)
return dataset
def alpaca_data_collator(return_hf_format=False):
return partial(default_collate_fn, return_hf_format=return_hf_format)
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