/usr/local/lib/python3.6/site-packages/datasets/commands
Edit: /usr/local/lib/python3.6/site-packages/datasets/commands/run_beam.py (6528B)
import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile
from typing import List
from datasets import config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
def run_beam_command_factory(args, **kwargs):
return RunBeamCommand(
args.dataset,
args.name,
args.cache_dir,
args.beam_pipeline_options,
args.data_dir,
args.all_configs,
args.save_infos,
args.ignore_verifications,
args.force_redownload,
**kwargs,
)
class RunBeamCommand(BaseDatasetsCLICommand):
@staticmethod
def register_subcommand(parser: ArgumentParser):
run_beam_parser = parser.add_parser("run_beam", help="Run a Beam dataset processing pipeline")
run_beam_parser.add_argument("dataset", type=str, help="Name of the dataset to download")
run_beam_parser.add_argument("--name", type=str, default=None, help="Dataset config name")
run_beam_parser.add_argument(
"--cache_dir",
type=str,
default=None,
help="Cache directory where the datasets are stored",
)
run_beam_parser.add_argument(
"--beam_pipeline_options",
type=str,
default="",
help="Beam pipeline options, separated by commas. Example:: `--beam_pipeline_options=job_name=my-job,project=my-project`",
)
run_beam_parser.add_argument(
"--data_dir",
type=str,
default=None,
help="Can be used to specify a manual directory to get the files from",
)
run_beam_parser.add_argument("--all_configs", action="store_true", help="Test all dataset configurations")
run_beam_parser.add_argument("--save_infos", action="store_true", help="Save the dataset infos file")
run_beam_parser.add_argument(
"--ignore_verifications", action="store_true", help="Run the test without checksums and splits checks"
)
run_beam_parser.add_argument("--force_redownload", action="store_true", help="Force dataset redownload")
run_beam_parser.set_defaults(func=run_beam_command_factory)
def __init__(
self,
dataset: str,
name: str,
cache_dir: str,
beam_pipeline_options: str,
data_dir: str,
all_configs: bool,
save_infos: bool,
ignore_verifications: bool,
force_redownload: bool,
**config_kwargs,
):
self._dataset = dataset
self._name = name
self._cache_dir = cache_dir
self._beam_pipeline_options = beam_pipeline_options
self._data_dir = data_dir
self._all_configs = all_configs
self._save_infos = save_infos
self._ignore_verifications = ignore_verifications
self._force_redownload = force_redownload
self._config_kwargs = config_kwargs
def run(self):
import apache_beam as beam
if self._name is not None and self._all_configs:
print("Both parameters `name` and `all_configs` can't be used at once.")
exit(1)
path, config_name = self._dataset, self._name
dataset_module = dataset_module_factory(path)
builder_cls = import_main_class(dataset_module.module_path)
builders: List[DatasetBuilder] = []
if self._beam_pipeline_options:
beam_options = beam.options.pipeline_options.PipelineOptions(
flags=[f"--{opt.strip()}" for opt in self._beam_pipeline_options.split(",") if opt]
)
else:
beam_options = None
if self._all_configs and len(builder_cls.BUILDER_CONFIGS) > 0:
for builder_config in builder_cls.BUILDER_CONFIGS:
builders.append(
builder_cls(
config_name=builder_config.name,
data_dir=self._data_dir,
hash=dataset_module.hash,
beam_options=beam_options,
cache_dir=self._cache_dir,
base_path=dataset_module.builder_kwargs.get("base_path"),
)
)
else:
builders.append(
builder_cls(
config_name=config_name,
data_dir=self._data_dir,
beam_options=beam_options,
cache_dir=self._cache_dir,
base_path=dataset_module.builder_kwargs.get("base_path"),
**self._config_kwargs,
)
)
for builder in builders:
builder.download_and_prepare(
download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
if not self._force_redownload
else DownloadMode.FORCE_REDOWNLOAD,
download_config=DownloadConfig(cache_dir=config.DOWNLOADED_DATASETS_PATH),
ignore_verifications=self._ignore_verifications,
try_from_hf_gcs=False,
)
if self._save_infos:
builder._save_infos()
print("Apache beam run successful.")
# If save_infos=True, the dataset infos file is created next to the loaded module file.
# Let's move it to the original directory of the dataset script, to allow the user to
# upload them on S3 at the same time afterwards.
if self._save_infos:
dataset_infos_path = os.path.join(builder_cls.get_imported_module_dir(), config.DATASETDICT_INFOS_FILENAME)
name = Path(path).name + ".py"
combined_path = os.path.join(path, name)
if os.path.isfile(path):
dataset_dir = os.path.dirname(path)
elif os.path.isfile(combined_path):
dataset_dir = path
else: # in case of a remote dataset
print(f"Dataset Infos file saved at {dataset_infos_path}")
exit(1)
# Move datasetinfo back to the user
user_dataset_infos_path = os.path.join(dataset_dir, config.DATASETDICT_INFOS_FILENAME)
copyfile(dataset_infos_path, user_dataset_infos_path)
print(f"Dataset Infos file saved at {user_dataset_infos_path}")