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Copy patharguments.py
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151 lines (148 loc) · 4.89 KB
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from dataclasses import dataclass, field
from typing import Optional
@dataclass
class FilteringArguments:
# add arguments in the following format
dataset_name: Optional[str] = field(
default="bigcode/python_permissive",
metadata={"help": "HF repo name/path of the dataset."},
)
subset: Optional[str] = field(
default="data/",
metadata={"help": "Data subset."},
)
split: Optional[str] = field(
default="train",
metadata={"help": "Dataset split to process."},
)
tokenizer_name: Optional[str] = field(
default="bigcode/digit-bytelevel-bpe-jss-v1.1-49152",
metadata={"help": "HF repo name/path of the tokenizer."},
)
line_max: Optional[int] = field(
default=1000,
metadata={"help": "Max line length allowed"},
)
line_mean: Optional[int] = field(
default=100,
metadata={"help": "Mean line length allowed"},
)
alpha_frac: Optional[float] = field(
default=0.25,
metadata={"help": "Minimum fraction of alphanumeric characters allowed."},
)
min_threshold_comments: Optional[float] = field(
default=0.01,
metadata={"help": "Minimum threshold for comment to code ratio."},
)
max_threshold_comments: Optional[float] = field(
default=0.8,
metadata={"help": "Maximum threshold for comment to code ratio."},
)
threshold_stars: Optional[int] = field(
default=5,
metadata={"help": "Minimum threshold for number of stars."},
)
min_size: Optional[int] = field(
default=100,
metadata={"help": "Minimum content size."},
)
max_size: Optional[int] = field(
default=5000,
metadata={"help": "Maximum content size."},
)
per_extension_filter_csv: Optional[str] = field(
default=None,
metadata={"help": "Path to csv file containing the filters to be applied depending on file extension"},
)
num_workers: Optional[int] = field(
default=96,
metadata={"help": "Number of workers for multiprocessing."},
)
batch_size: Optional[int] = field(
default=1000,
metadata={"help": "Batch size for multiprocessing."},
)
push_to_hub: Optional[bool] = field(
default=False,
metadata={"help": "Push the dataset to the Hub."},
)
remote_repo: Optional[str] = field(
default="stack-pjj-stars-filtering",
metadata={"help": "HF repo name of the target dataset in the hub."},
)
hub_username: Optional[str] = field(
default="loubnabnl",
metadata={"help": "Username for the hub."},
)
out_path: Optional[str] = field(
default=None,
metadata={"help": "Local path to save the ouptut dataset."},
)
log_file: Optional[str] = field(
default="filtering.log",
metadata={"help": "File to write log to."},
)
fix_license_columns: Optional[bool] = field(
default=False,
metadata={"help": "Fix license columns."},
)
run_decontamination: Optional[bool] = field(
default=False,
metadata={"help": "Run decontamination after the filtering"},
)
@dataclass
class ContentWithMetaArguments:
# add arguments in the following format
dataset_name: Optional[str] = field(
default="bigcode/the-stack-smol",
metadata={"help": "HF repo name/path of the dataset."},
)
subset: Optional[str] = field(
default="data/java",
metadata={"help": "Data subset."},
)
split: Optional[str] = field(
default="train",
metadata={"help": "Datasset split to process."},
)
add_repo_name_prob: float = field(
default=.2,
metadata={"help": "Probability to add repo-name"}
)
add_file_name_prob: float = field(
default=.2,
metadata={"help": "Probability to add filename"}
)
add_num_stars_prob: float = field(
default=.2,
metadata={"help": "Probability to add number of stars"}
)
num_workers: Optional[int] = field(
default=96,
metadata={"help": "Number of workers for multiprocessing."},
)
batch_size: Optional[int] = field(
default=1000,
metadata={"help": "Batch size for multiprocessing."},
)
push_to_hub: Optional[bool] = field(
default=False,
metadata={"help": "Push the dataset to the Hub."},
)
remote_repo: Optional[str] = field(
default="stack-pjj-stars-filtering",
metadata={"help": "HF repo name of the target dataset in the hub."},
)
hub_username: Optional[str] = field(
default="loubnabnl",
metadata={"help": "Username for the hub."},
)
out_path: Optional[str] = field(
default=None,
metadata={"help": "Local path to save the ouptut dataset."},
)
log_file: Optional[str] = field(
default="filtering.log",
metadata={"help": "File to write log to."},
)