text stringlengths 1 1.02k | class_index int64 0 271 | source stringclasses 76
values |
|---|---|---|
def _check_legacy_cache2(self, dataset_module: "DatasetModule") -> Optional[str]:
"""Check for the old cache directory template {cache_dir}/{namespace}___{dataset_name}/{config_name}-xxx from 2.14 and 2.15"""
if (
self.__module__.startswith("datasets.")
and not is_remote_url(self... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def update_hash_with_config_parameters(hash: str, config_parameters: dict) -> str:
"""
Used to update hash of packaged modules which is used for creating unique cache directories to reflect
different config parameters which are passed in metadata from readme.
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
namespace = self.repo_id.split("/")[0] if self.repo_id and self.repo_id.count("/") > 0 else None
with patch.object(Pickler, "_legacy_no_dict_keys_sorting", True):
config_id = self.config.name + "-" + Hasher.hash({"data_files": self.config.data_files})
hash = _PACKAGED_DATASETS_MO... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
legacy_cache_dir = posixpath.join(self._cache_dir_root, legacy_relative_data_dir)
if os.path.isdir(legacy_cache_dir):
return legacy_relative_data_dir | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
@classmethod
def get_all_exported_dataset_infos(cls) -> DatasetInfosDict:
"""Empty dict if doesn't exist
Example: | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
```py
>>> from datasets import load_dataset_builder
>>> ds_builder = load_dataset_builder('vivos')
>>> ds_builder.get_all_exported_dataset_infos()
{'default': DatasetInfo(description='', citation='', homepage='', license='', features={'speaker_id': Value(dtype='string', id=None), 'path':... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
return DatasetInfosDict.from_directory(cls.get_imported_module_dir()) | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def get_exported_dataset_info(self) -> DatasetInfo:
"""Empty `DatasetInfo` if doesn't exist
Example: | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
```py
>>> from datasets import load_dataset_builder
>>> ds_builder = load_dataset_builder('rotten_tomatoes')
>>> ds_builder.get_exported_dataset_info()
DatasetInfo(description='', citation='', homepage='', license='', features={'speaker_id': Value(dtype='string', id=None), 'path': Value(... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
return self.get_all_exported_dataset_infos().get(self.config.name, DatasetInfo()) | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _create_builder_config(
self, config_name=None, custom_features=None, **config_kwargs
) -> Tuple[BuilderConfig, str]:
"""Create and validate BuilderConfig object as well as a unique config id for this config.
Raises ValueError if there are multiple builder configs and config_name and DEF... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# try default config
if config_name is None and self.BUILDER_CONFIGS:
if self.DEFAULT_CONFIG_NAME is not None:
builder_config = self.builder_configs.get(self.DEFAULT_CONFIG_NAME)
logger.info(f"No config specified, defaulting to: {self.dataset_name}/{builder_config.nam... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
builder_config = self.BUILDER_CONFIGS[0]
logger.info(
f"No config specified, defaulting to the single config: {self.dataset_name}/{builder_config.name}"
) | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# try to get config by name
if isinstance(config_name, str):
builder_config = self.builder_configs.get(config_name)
if builder_config is None and self.BUILDER_CONFIGS:
raise ValueError(
f"BuilderConfig '{config_name}' not found. Available: {list(self.b... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# otherwise use the config_kwargs to overwrite the attributes
else:
builder_config = copy.deepcopy(builder_config) if config_kwargs else builder_config
for key, value in config_kwargs.items():
if value is not None:
if not hasattr(builder_config, key):
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# compute the config id that is going to be used for caching
config_id = builder_config.create_config_id(
config_kwargs,
custom_features=custom_features,
)
is_custom = (config_id not in self.builder_configs) and config_id != "default"
if is_custom:
log... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
@classproperty
@classmethod
@memoize()
def builder_configs(cls) -> Dict[str, BuilderConfig]:
"""Dictionary of pre-defined configurations for this builder class."""
configs = {config.name: config for config in cls.BUILDER_CONFIGS}
if len(configs) != len(cls.BUILDER_CONFIGS):
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _relative_data_dir(self, with_version=True, with_hash=True) -> str:
"""Relative path of this dataset in cache_dir:
Will be:
self.dataset_name/self.config.version/self.hash/
or if a repo_id with a namespace has been specified:
self.namespace___self.dataset_name/self.co... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
namespace = self.repo_id.split("/")[0] if self.repo_id and self.repo_id.count("/") > 0 else None
builder_data_dir = self.dataset_name if namespace is None else f"{namespace}___{self.dataset_name}"
builder_data_dir = posixpath.join(builder_data_dir, self.config_id)
if with_version:
bu... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _other_versions_on_disk():
"""Returns previous versions on disk."""
if not os.path.exists(builder_data_dir):
return []
version_dirnames = []
for dir_name in os.listdir(builder_data_dir):
try:
version_dirnames.append... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# Check and warn if other versions exist
if not is_remote_url(builder_data_dir):
version_dirs = _other_versions_on_disk()
if version_dirs:
other_version = version_dirs[0][0]
if other_version != self.config.version:
warn_msg = (
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
Returns:
info: (DatasetInfo) The dataset information
"""
raise NotImplementedError
@classmethod
def get_imported_module_dir(cls):
"""Return the path of the module of this class or subclass."""
return os.path.dirname(inspect.getfile(inspect.getmodule(cls)))
def _... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def download_and_prepare(
self,
output_dir: Optional[str] = None,
download_config: Optional[DownloadConfig] = None,
download_mode: Optional[Union[DownloadMode, str]] = None,
verification_mode: Optional[Union[VerificationMode, str]] = None,
dl_manager: Optional[DownloadMan... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
<Added version="2.5.0"/>
download_config (`DownloadConfig`, *optional*):
Specific download configuration parameters.
download_mode ([`DownloadMode`] or `str`, *optional*):
Select the download/generate mode, default to `REUSE_DATASET_IF_EXISTS`.
verific... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
<Added version="2.9.1"/>
dl_manager (`DownloadManager`, *optional*):
Specific `DownloadManger` to use.
base_path (`str`, *optional*):
Base path for relative paths that are used to download files. This can be a remote url.
If not specified, the valu... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
<Added version="2.5.0"/>
max_shard_size (`Union[str, int]`, *optional*):
Maximum number of bytes written per shard, default is "500MB".
The size is based on uncompressed data size, so in practice your shard files may be smaller than
`max_shard_size` thanks to ... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
Download and prepare the dataset as Arrow files that can be loaded as a Dataset using `builder.as_dataset()`:
```py
>>> from datasets import load_dataset_builder
>>> builder = load_dataset_builder("rotten_tomatoes")
>>> builder.download_and_prepare()
```
Download and pr... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
```py
>>> from datasets import load_dataset_builder
>>> storage_options = {"key": aws_access_key_id, "secret": aws_secret_access_key}
>>> builder = load_dataset_builder("rotten_tomatoes")
>>> builder.download_and_prepare("s3://my-bucket/my_rotten_tomatoes", storage_options=storage_option... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
if file_format is not None and file_format not in ["arrow", "parquet"]:
raise ValueError(f"Unsupported file_format: {file_format}. Expected 'arrow' or 'parquet'")
self._file_format = file_format
if self._fs._strip_protocol(self._output_dir) == "":
# We don't support the root dir... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
if dl_manager is None:
if download_config is None:
download_config = DownloadConfig(
cache_dir=self._cache_downloaded_dir,
force_download=download_mode == DownloadMode.FORCE_REDOWNLOAD,
force_extract=download_mode == DownloadMode.FO... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
is_local = not is_remote_filesystem(self._fs)
self.dl_manager = dl_manager
# Prevent parallel local disk operations
if is_local:
# Create parent directory of the output_dir to put the lock file in there
Path(self._output_dir).parent.mkdir(parents=True, exist_ok=True)
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# File locking only with local paths; no file locking on GCS or S3
with FileLock(lock_path) if is_local else contextlib.nullcontext():
# Check if the data already exists
data_exists = self._fs.exists(posixpath.join(self._output_dir, config.DATASET_INFO_FILENAME))
if data_exis... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
logger.info(f"Generating dataset {self.dataset_name} ({self._output_dir})")
if is_local: # if cache dir is local, check for available space
if not has_sufficient_disk_space(
self.info.size_in_bytes or 0, directory=Path(self._output_dir).parent
):
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
@contextlib.contextmanager
def incomplete_dir(dirname):
"""Create temporary dir for dirname and rename on exit."""
if not is_local:
self._fs.makedirs(dirname, exist_ok=True)
yield dirname
else:
tmp_di... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# Print is intentional: we want this to always go to stdout so user has
# information needed to cancel download/preparation if needed.
# This comes right before the progress bar.
if self.info.size_in_bytes:
logger.info(
f"Downloading and preparing ... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# Create a tmp dir and rename to self._output_dir on successful exit.
with incomplete_dir(self._output_dir) as tmp_output_dir:
# Temporarily assign _output_dir to tmp_data_dir to avoid having to forward
# it to every sub function.
with temporary_assignment(sel... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
self.info.dataset_size = sum(split.num_bytes for split in self.info.splits.values())
self.info.download_checksums = dl_manager.get_recorded_sizes_checksums()
if self.info.download_size is not None:
self.info.size_in_bytes = self.info.dataset_size + self.in... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# Download post processing resources
self.download_post_processing_resources(dl_manager)
logger.info(
f"Dataset {self.dataset_name} downloaded and prepared to {self._output_dir}. "
f"Subsequent calls will reuse this data."
)
def _check_manual_dow... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs):
"""Downloads and prepares dataset for reading.
This is the internal implementation to overwrite called when user calls
`download_and_prepare`. It should download all required data and generate
the pr... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
Args:
dl_manager ([`DownloadManager`]):
`DownloadManager` used to download and cache data.
verification_mode ([`VerificationMode`]):
if `ALL_CHECKS`, perform all the verifications including checksums.
if `BASIC_CHECKS`, do not perform checksums, on... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# Checksums verification
if verification_mode == VerificationMode.ALL_CHECKS and dl_manager.record_checksums:
verify_checksums(
self.info.download_checksums, dl_manager.get_recorded_sizes_checksums(), "dataset source files"
)
# Build splits
for split_gene... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
try:
# Prepare split will record examples associated to the split
self._prepare_split(split_generator, **prepare_split_kwargs)
except OSError as e:
raise OSError(
"Cannot find data file. "
+ (self.manual_download_instruc... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
if verification_mode == VerificationMode.BASIC_CHECKS or verification_mode == VerificationMode.ALL_CHECKS:
verify_splits(self.info.splits, split_dict)
# Update the info object with the splits.
self.info.splits = split_dict
self.info.download_size = dl_manager.downloaded_size | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def download_post_processing_resources(self, dl_manager):
for split in self.info.splits or []:
for resource_name, resource_file_name in self._post_processing_resources(split).items():
if not not is_remote_filesystem(self._fs):
raise NotImplementedError(f"Post proc... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
shutil.move(downloaded_resource_path, resource_path) | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _load_info(self) -> DatasetInfo:
return DatasetInfo.from_directory(self._output_dir, storage_options=self._fs.storage_options)
def _save_info(self):
file_lock = (
FileLock(self._output_dir + "_info.lock")
if not is_remote_filesystem(self._fs)
else contextlib.... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def as_dataset(
self,
split: Optional[Split] = None,
run_post_process=True,
verification_mode: Optional[Union[VerificationMode, str]] = None,
in_memory=False,
) -> Union[Dataset, DatasetDict]:
"""Return a Dataset for the specified split.
Args:
spl... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
```py
>>> from datasets import load_dataset_builder
>>> builder = load_dataset_builder('rotten_tomatoes')
>>> builder.download_and_prepare()
>>> ds = builder.as_dataset(split='train')
>>> ds
Dataset({
features: ['text', 'label'],
num_rows: 8530
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
"datasets.load_dataset() before trying to access the Dataset object."
) | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
logger.debug(f"Constructing Dataset for split {split or ', '.join(self.info.splits)}, from {self._output_dir}")
# By default, return all splits
if split is None:
split = {s: s for s in self.info.splits}
verification_mode = VerificationMode(verification_mode or VerificationMode.BASI... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _build_single_dataset(
self,
split: Union[str, ReadInstruction, Split],
run_post_process: bool,
verification_mode: VerificationMode,
in_memory: bool = False,
):
"""as_dataset for a single split."""
if not isinstance(split, ReadInstruction):
spl... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# Build base dataset
ds = self._as_dataset(
split=split,
in_memory=in_memory,
)
if run_post_process:
for resource_file_name in self._post_processing_resources(split).values():
if os.sep in resource_file_name:
raise ValueErro... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
recorded_checksums[resource_name] = size_checksum
if verification_mode == VerificationMode.ALL_CHECKS and record_checksums:
if self.info.post_processed is None or self.info.post_processed.resources_checksums is None:
expected_checksums = None
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
for split_checksums_dicts in self.info.post_processed.resources_checksums.values()
for checksums_dict in split_checksums_dicts.values()
)
if self.info.dataset_size is not None and self.info.download_size is not None:
self.info.size_in_bytes = (
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
f"Post-processed features info don't match the dataset:\nGot\n{self.info.post_processed.features}\nbut expected something like\n{ds.features}"
)
else:
ds.info.features = self.info.post_processed.features | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
return ds
def _as_dataset(self, split: Union[ReadInstruction, Split] = Split.TRAIN, in_memory: bool = False) -> Dataset:
"""Constructs a `Dataset`.
This is the internal implementation to overwrite called when user calls
`as_dataset`. It should read the pre-processed datasets files and gene... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
Returns:
`Dataset`
"""
cache_dir = self._fs._strip_protocol(self._output_dir)
dataset_name = self.dataset_name
if self._check_legacy_cache():
dataset_name = self.name
dataset_kwargs = ArrowReader(cache_dir, self.info).read(
name=dataset_name,
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _get_dataset_fingerprint(self, split: Union[ReadInstruction, Split]) -> str:
"""The dataset fingerprint is the hash of the relative directory dataset_name/config_name/version/hash, as well as the split specs."""
hasher = Hasher()
hasher.update(Path(self._relative_data_dir()).as_posix())
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
dl_manager = StreamingDownloadManager(
base_path=base_path or self.base_path,
download_config=DownloadConfig(token=self.token, storage_options=self.storage_options),
dataset_name=self.dataset_name,
data_dir=self.config.data_dir,
)
self._check_manual_downlo... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
# Create a dataset for each of the given splits
datasets = map_nested(
self._as_streaming_dataset_single,
splits_generator,
map_tuple=True,
)
if isinstance(datasets, dict):
datasets = IterableDatasetDict(datasets)
return datasets
def _... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _post_processing_resources(self, split: str) -> Dict[str, str]:
"""Mapping resource_name -> resource_file_name"""
return {}
def _download_post_processing_resources(
self, split: str, resource_name: str, dl_manager: DownloadManager
) -> Optional[str]:
"""Download the resource... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={'file': 'train_data.zip'},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
For downloads and extractions, use the given `download_manager`.
Note that the `DownloadManager` caches downloads, so it is fine to have each
generator attempt to download the source data.
A good practice is to download all data in this function, and then
distribute the relevant parts t... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
Args:
split_generator (`SplitGenerator`):
Split generator to process
file_format (`str`, *optional*):
format of the data files in which the dataset will be written.
Supported formats: "arrow", "parquet". Default to "arrow" format.
max_s... | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _get_examples_iterable_for_split(self, split_generator: SplitGenerator) -> ExamplesIterable:
"""Generate the examples on the fly.
Args:
split_generator (`SplitGenerator`):
Split generator to process
"""
raise NotImplementedError() | 54 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
class GeneratorBasedBuilder(DatasetBuilder):
"""Base class for datasets with data generation based on dict generators.
`GeneratorBasedBuilder` is a convenience class that abstracts away much
of the data writing and reading of `DatasetBuilder`. It expects subclasses to
implement generators of feature di... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
Yields:
key: `str` or `int`, a unique deterministic example identification key.
* Unique: An error will be raised if two examples are yield with the
same key.
* Deterministic: When generating the dataset twice, the same example
should h... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _prepare_split(
self,
split_generator: SplitGenerator,
check_duplicate_keys: bool,
file_format="arrow",
num_proc: Optional[int] = None,
max_shard_size: Optional[Union[int, str]] = None,
):
max_shard_size = convert_file_size_to_int(max_shard_size or config.... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
if num_proc and num_proc > 1:
num_input_shards = _number_of_shards_in_gen_kwargs(split_generator.gen_kwargs)
if num_input_shards <= 1:
logger.warning(
f"Setting num_proc from {num_proc} back to 1 for the {split_info.name} split to disable multiprocessing as it... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
_prepare_split_args = {
"fpath": fpath,
"file_format": file_format,
"max_shard_size": max_shard_size,
"split_info": split_info,
"check_duplicate_keys": check_duplicate_keys,
} | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
if num_proc is None or num_proc == 1:
result = None
gen_kwargs = split_generator.gen_kwargs
job_id = 0
with pbar:
for job_id, done, content in self._prepare_split_single(
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
_split_gen_kwargs(split_generator.gen_kwargs, max_num_jobs=num_proc)
)
]
num_jobs = len(kwargs_per_job) | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
examples_per_job = [None] * num_jobs
bytes_per_job = [None] * num_jobs
features_per_job = [None] * num_jobs
shards_per_job = [None] * num_jobs
shard_lengths_per_job = [None] * num_jobs | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
with Pool(num_proc) as pool:
with pbar:
for job_id, done, content in iflatmap_unordered(
pool, self._prepare_split_single, kwargs_iterable=kwargs_per_job
):
if done:
# the content is the r... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
assert None not in examples_per_job, (
f"Failed to retrieve results from prepare_split: result list {examples_per_job} still contains None - at least one worker failed to return its results"
)
total_shards = sum(shards_per_job)
total_num_examples = sum(examples_per_job)
... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _rename_shard(shard_and_job: Tuple[int]):
shard_id, job_id = shard_and_job
global_shard_id = sum(shards_per_job[:job_id]) + shard_id
self._rename(
fpath.replace("SSSSS", f"{shard_id:05d}").replace("JJJJJ", f"{job_id:05d}"),
fpat... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
split_generator.split_info.shard_lengths = [
shard_length for shard_lengths in shard_lengths_per_job for shard_length in shard_lengths
]
else:
# don't use any pattern
shard_id, job_id = 0, 0
self._rename(
fpath.replace("SSSSS", f"{s... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _prepare_split_single(
self,
gen_kwargs: dict,
fpath: str,
file_format: str,
max_shard_size: int,
split_info: SplitInfo,
check_duplicate_keys: bool,
job_id: int,
) -> Iterable[Tuple[int, bool, Union[int, tuple]]]:
generator = self._generate... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
shard_id = 0
num_examples_progress_update = 0
try:
writer = writer_class(
features=self.info.features,
path=fpath.replace("SSSSS", f"{shard_id:05d}").replace("JJJJJ", f"{job_id:05d}"),
writer_batch_size=self._writer_batch_size,
... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
shard_id += 1
writer = writer_class(
features=writer._features,
path=fpath.replace("SSSSS", f"{shard_id:05d}").replace("JJJJJ", f"{job_id:05d}"),
writer_batch_size=self._writer_batch_size,
... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
num_examples_progress_update = 0
finally:
yield job_id, False, num_examples_progress_update
num_shards = shard_id + 1
num_examples, num_bytes = writer.finalize()
writer.close()
shard_lengths.append(num_examples)
... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)
def _download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs):
super()._download_and_prepare(
dl_manager,
verification_mode,
check_duplicate_k... | 55 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
class ArrowBasedBuilder(DatasetBuilder):
"""Base class for datasets with data generation based on Arrow loading functions (CSV/JSON/Parquet)."""
@abc.abstractmethod
def _generate_tables(self, **kwargs):
"""Default function generating examples for each `SplitGenerator`.
This function prepro... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
Yields:
key: `str` or `int`, a unique deterministic example identification key.
* Unique: An error will be raised if two examples are yield with the
same key.
* Deterministic: When generating the dataset twice, the same example
should h... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _prepare_split(
self,
split_generator: SplitGenerator,
file_format: str = "arrow",
num_proc: Optional[int] = None,
max_shard_size: Optional[Union[str, int]] = None,
):
max_shard_size = convert_file_size_to_int(max_shard_size or config.MAX_SHARD_SIZE)
try:... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
if num_proc and num_proc > 1:
num_input_shards = _number_of_shards_in_gen_kwargs(split_generator.gen_kwargs)
if num_input_shards <= 1:
logger.warning(
f"Setting num_proc from {num_proc} back to 1 for the {split_info.name} split to disable multiprocessing as it... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
if num_proc is None or num_proc == 1:
result = None
gen_kwargs = split_generator.gen_kwargs
job_id = 0
with pbar:
for job_id, done, content in self._prepare_split_single(
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
_split_gen_kwargs(split_generator.gen_kwargs, max_num_jobs=num_proc)
)
]
num_jobs = len(kwargs_per_job) | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
examples_per_job = [None] * num_jobs
bytes_per_job = [None] * num_jobs
features_per_job = [None] * num_jobs
shards_per_job = [None] * num_jobs
shard_lengths_per_job = [None] * num_jobs | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
with Pool(num_proc) as pool:
with pbar:
for job_id, done, content in iflatmap_unordered(
pool, self._prepare_split_single, kwargs_iterable=kwargs_per_job
):
if done:
# the content is the r... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
assert None not in examples_per_job, (
f"Failed to retrieve results from prepare_split: result list {examples_per_job} still contains None - at least one worker failed to return its results"
)
total_shards = sum(shards_per_job)
total_num_examples = sum(examples_per_job)
... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _rename_shard(shard_id_and_job: Tuple[int]):
shard_id, job_id = shard_id_and_job
global_shard_id = sum(shards_per_job[:job_id]) + shard_id
self._rename(
fpath.replace("SSSSS", f"{shard_id:05d}").replace("JJJJJ", f"{job_id:05d}"),
... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
split_generator.split_info.shard_lengths = [
shard_length for shard_lengths in shard_lengths_per_job for shard_length in shard_lengths
]
else:
# don't use any pattern
shard_id, job_id = 0, 0
self._rename(
fpath.replace("SSSSS", f"{s... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
def _prepare_split_single(
self, gen_kwargs: dict, fpath: str, file_format: str, max_shard_size: int, job_id: int
) -> Iterable[Tuple[int, bool, Union[int, tuple]]]:
gen_kwargs = {k: tracked_list(v) if isinstance(v, list) else v for k, v in gen_kwargs.items()}
generator = self._generate_tabl... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
shard_id = 0
num_examples_progress_update = 0
try:
writer = writer_class(
features=self.info.features,
path=fpath.replace("SSSSS", f"{shard_id:05d}").replace("JJJJJ", f"{job_id:05d}"),
writer_batch_size=self._writer_batch_size,
... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
features=writer._features,
path=fpath.replace("SSSSS", f"{shard_id:05d}").replace("JJJJJ", f"{job_id:05d}"),
writer_batch_size=self._writer_batch_size,
storage_options=self._fs.storage_options,
embed_local_fi... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
yield job_id, False, num_examples_progress_update
num_examples_progress_update = 0
finally:
yield job_id, False, num_examples_progress_update
num_shards = shard_id + 1
num_examples, num_bytes = writer.finalize()
writer.c... | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)
def _get_examples_iterable_for_split(self, split_generator: SplitGenerator) -> ExamplesIterable:
return ArrowExamplesIterable(self._generate_tables, kwargs=split_generator.gen_kwargs) | 56 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/builder.py |
class SplitsNotFoundError(ValueError):
pass | 57 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/inspect.py |
class MissingIndex(Exception):
pass | 58 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/search.py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.