text stringlengths 1 1.02k | class_index int64 0 271 | source stringclasses 76
values |
|---|---|---|
Returns:
`pa.StructArray`: Array in the Video arrow storage type, that is
`pa.struct({"bytes": pa.binary(), "path": pa.string()})`.
"""
if pa.types.is_string(storage.type):
bytes_array = pa.array([None] * len(storage), type=pa.binary())
storage = pa.St... | 162 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/video.py |
else:
path_array = pa.array([None] * len(storage), type=pa.string())
storage = pa.StructArray.from_arrays([bytes_array, path_array], ["bytes", "path"], mask=storage.is_null())
elif pa.types.is_list(storage.type):
bytes_array = pa.array(
[encode_np_array(np... | 162 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/video.py |
class Image:
"""Image [`Feature`] to read image data from an image file.
Input: The Image feature accepts as input:
- A `str`: Absolute path to the image file (i.e. random access is allowed).
- A `dict` with the keys:
- `path`: String with relative path of the image file to the archive file.
... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
```py
>>> from datasets import load_dataset, Image
>>> ds = load_dataset("beans", split="train")
>>> ds.features["image"]
Image(decode=True, id=None)
>>> ds[0]["image"]
<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=500x500 at 0x15E52E7F0>
>>> ds = ds.cast_column('image', Image(decod... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
def encode_example(self, value: Union[str, bytes, dict, np.ndarray, "PIL.Image.Image"]) -> dict:
"""Encode example into a format for Arrow.
Args:
value (`str`, `np.ndarray`, `PIL.Image.Image` or `dict`):
Data passed as input to Image feature.
Returns:
`d... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
if isinstance(value, str):
return {"path": value, "bytes": None}
elif isinstance(value, bytes):
return {"path": None, "bytes": value}
elif isinstance(value, np.ndarray):
# convert the image array to PNG/TIFF bytes
return encode_np_array(value)
elif... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
f"An image sample should have one of 'path' or 'bytes' but they are missing or None in {value}."
) | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
def decode_example(self, value: dict, token_per_repo_id=None) -> "PIL.Image.Image":
"""Decode example image file into image data.
Args:
value (`str` or `dict`):
A string with the absolute image file path, a dictionary with
keys:
- `path`: Str... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
if config.PIL_AVAILABLE:
import PIL.Image
import PIL.ImageOps
else:
raise ImportError("To support decoding images, please install 'Pillow'.")
if token_per_repo_id is None:
token_per_repo_id = {} | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
path, bytes_ = value["path"], value["bytes"]
if bytes_ is None:
if path is None:
raise ValueError(f"An image should have one of 'path' or 'bytes' but both are None in {value}.")
else:
if is_local_path(path):
image = PIL.Image.open(path)... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
with xopen(path, "rb", download_config=download_config) as f:
bytes_ = BytesIO(f.read())
image = PIL.Image.open(bytes_)
else:
image = PIL.Image.open(BytesIO(bytes_))
image.load() # to avoid "Too many open files" errors
if image.getexif().g... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
def flatten(self) -> Union["FeatureType", Dict[str, "FeatureType"]]:
"""If in the decodable state, return the feature itself, otherwise flatten the feature into a dictionary."""
from .features import Value
return (
self
if self.decode
else {
"... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
- `pa.string()` - it must contain the "path" data
- `pa.binary()` - it must contain the image bytes
- `pa.struct({"bytes": pa.binary()})`
- `pa.struct({"path": pa.string()})`
- `pa.struct({"bytes": pa.binary(), "path": pa.string()})` - order doesn't matter
- `pa.list(*)` - it mu... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
Returns:
`pa.StructArray`: Array in the Image arrow storage type, that is
`pa.struct({"bytes": pa.binary(), "path": pa.string()})`.
"""
if pa.types.is_string(storage.type):
bytes_array = pa.array([None] * len(storage), type=pa.binary())
storage = pa.St... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
else:
path_array = pa.array([None] * len(storage), type=pa.string())
storage = pa.StructArray.from_arrays([bytes_array, path_array], ["bytes", "path"], mask=storage.is_null())
elif pa.types.is_list(storage.type):
bytes_array = pa.array(
[encode_np_array(np... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
def embed_storage(self, storage: pa.StructArray) -> pa.StructArray:
"""Embed image files into the Arrow array.
Args:
storage (`pa.StructArray`):
PyArrow array to embed.
Returns:
`pa.StructArray`: Array in the Image arrow storage type, that is
... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
bytes_array = pa.array(
[
(path_to_bytes(x["path"]) if x["bytes"] is None else x["bytes"]) if x is not None else None
for x in storage.to_pylist()
],
type=pa.binary(),
)
path_array = pa.array(
[os.path.basename(path) if path... | 163 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/features/image.py |
class WebDataset(datasets.GeneratorBasedBuilder):
DEFAULT_WRITER_BATCH_SIZE = 100
IMAGE_EXTENSIONS: List[str] # definition at the bottom of the script
AUDIO_EXTENSIONS: List[str] # definition at the bottom of the script
VIDEO_EXTENSIONS: List[str] # definition at the bottom of the script
DECODERS... | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
@classmethod
def _get_pipeline_from_tar(cls, tar_path, tar_iterator):
current_example = {}
fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
streaming_download_manager = datasets.StreamingDownloadManager()
for filename, f in tar_iterator:
example_key, field_name... | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
if field_name.split(".")[-1] in SINGLE_FILE_COMPRESSION_EXTENSION_TO_PROTOCOL:
fs.write_bytes(filename, current_example[field_name.lower()])
extracted_file_path = streaming_download_manager.extract(f"memory://{filename}")
with fsspec.open(extracted_file_path) as f:
... | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
def _info(self) -> datasets.DatasetInfo:
return datasets.DatasetInfo() | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
def _split_generators(self, dl_manager):
"""We handle string, list and dicts in datafiles"""
# Download the data files
if not self.config.data_files:
raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
data_files = dl_man... | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
if any(example.keys() != first_examples[0].keys() for example in first_examples):
raise ValueError(
"The TAR archives of the dataset should be in WebDataset format, "
"bu... | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
# Set Image types
for field_name in first_examples[0]:
extension = field_name.rsplit(".", 1)[-1]
if extension in self.IMAGE_EXTENSIONS:
features[field_name] = datasets.Image()
# Set Audio types
for field_name in first_examples[0]:
... | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
def _generate_examples(self, tar_paths, tar_iterators):
image_field_names = [
field_name for field_name, feature in self.info.features.items() if isinstance(feature, datasets.Image)
]
audio_field_names = [
field_name for field_name, feature in self.info.features.items() i... | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
"path": example["__key__"] + "." + field_name,
"bytes": example[field_name],
}
yield f"{tar_idx}_{example_idx}", example | 164 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/webdataset/webdataset.py |
class FolderBasedBuilderConfig(datasets.BuilderConfig):
"""BuilderConfig for AutoFolder."""
features: Optional[datasets.Features] = None
drop_labels: bool = None
drop_metadata: bool = None
def __post_init__(self):
super().__post_init__() | 165 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
class FolderBasedBuilder(datasets.GeneratorBasedBuilder):
"""
Base class for generic data loaders for vision and image data.
Abstract class attributes to be overridden by a child class:
BASE_FEATURE: feature object to decode data (i.e. datasets.Image, datasets.Audio, ...)
BASE_COLUMN_NAME:... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
def _split_generators(self, dl_manager):
if not self.config.data_files:
raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
dl_manager.download_config.extract_on_the_fly = True
# Do an early pass if:
# * `drop_labels` is ... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
def analyze(files_or_archives, downloaded_files_or_dirs, split):
if len(downloaded_files_or_dirs) == 0:
return
# The files are separated from the archives at this point, so check the first sample
# to see if it's a file or a directory and iterate accordingly
... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
path_depths.add(count_path_segments(original_file))
elif os.path.basename(original_file) in self.METADATA_FILENAMES:
metadata_files[split].add((original_file, downloaded_file))
else:
original_file_name = os.path.basename(original_fi... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
if downloaded_dir_file_ext in self.EXTENSIONS:
if not self.config.drop_labels:
labels.add(os.path.basename(os.path.dirname(downloaded_dir_file)))
path_depths.add(count_path_segments(downloaded_dir_file))
... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
data_files = self.config.data_files
splits = []
for split_name, files in data_files.items():
if isinstance(files, str):
files = [files]
files, archives = self._split_files_and_archives(files)
downloaded_files = dl_manager.download(files)
do... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
if metadata_files:
# add metadata if `metadata_files` are found and `drop_metadata` is None (default) or False
add_metadata = not self.config.drop_metadata
# if `metadata_files` are found, add labels only if
# `drop_labels` is set up to Fal... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
) | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
if add_labels:
logger.info("Adding the labels inferred from data directories to the dataset's features...")
if add_metadata:
logger.info("Adding metadata to the dataset...")
else:
add_labels, add_metadata, metadata_files = False, False,... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
if add_metadata:
# Verify that:
# * all metadata files have the same set of features
# * the `file_name` key is one of the metadata keys and is of type string
features_per_metadata_file: List[Tuple[str, datasets.Features]] = []
# Check that all metadata files... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
for _, downloaded_metadata_file in itertools.chain.from_iterable(metadata_files.values()):
pa_metadata_table = self._read_metadata(downloaded_metadata_file, metadata_ext=metadata_ext)
features_per_metadata_file.append(
(downloaded_metadata_file, datasets.Features.from... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
if metadata_features["file_name"] != datasets.Value("string"):
raise ValueError("`file_name` key must be a string")
del metadata_features["file_name"]
else:
metadata_features = None | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
# Normally, we would do this in _info, but we need to know the labels and/or metadata
# before building the features
if self.config.features is None:
if add_labels:
self.info.features = datasets.Features(
{
self.BASE_COLUMN_NAME: se... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
if add_metadata:
# Warn if there are duplicated keys in metadata compared to the existing features
# (`BASE_COLUMN_NAME`, optionally "label")
duplicated_keys = set(self.info.features) & set(metadata_features)
if duplicated_keys:
logger.... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
def _split_files_and_archives(self, data_files):
files, archives = [], []
for data_file in data_files:
_, data_file_ext = os.path.splitext(data_file)
if data_file_ext.lower() in self.EXTENSIONS:
files.append(data_file)
elif os.path.basename(data_file) ... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
def _generate_examples(self, files, metadata_files, split_name, add_metadata, add_labels):
split_metadata_files = metadata_files.get(split_name, [])
sample_empty_metadata = (
{k: None for k in self.info.features if k != self.BASE_COLUMN_NAME} if self.info.features else {}
)
l... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
file_idx = 0
for original_file, downloaded_file_or_dir in files:
if original_file is not None:
_, original_file_ext = os.path.splitext(original_file)
if original_file_ext.lower() in self.EXTENSIONS:
if add_metadata:
# If the... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
downloaded_metadata_file,
)
for metadata_file_candidate, downloaded_metadata_file in split_metadata_files
if metadata_file_candidate
is not None # ignore metadata_files that are inside archiv... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
downloaded_metadata_file, metadata_ext=metadata_ext
)
pa_file_name_array = pa_metadata_table["file_name"]
pa_metadata_table = pa_metadata_table.drop(["file_name"])
metadata_dir = os.path.dirna... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
f"One or several metadata{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_file_or_dir}."
)
if metadata_dir is not None and downloaded_metadata_file is not None:
file_relpath = os.path.relp... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
f"One or several metadata{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_file_or_dir}."
)
else:
sample_metadata = {}
if add_labels:
sample_label = {"label"... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
_, downloaded_dir_file_ext = os.path.splitext(downloaded_dir_file)
if downloaded_dir_file_ext.lower() in self.EXTENSIONS:
if add_metadata:
current_dir = os.path.dirname(downloaded_dir_file)
if last_checked_dir is None or... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
for metadata_file_candidate, downloaded_metadata_file in split_metadata_files
if metadata_file_candidate
is None # ignore metadata_files that are not inside archives
and not os.path.relpath(
... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
)
pa_file_name_array = pa_metadata_table["file_name"]
pa_metadata_table = pa_metadata_table.drop(["file_name"])
metadata_dir = os.path.dirname(downloaded_metadata_file)
metadat... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
)
if metadata_dir is not None and downloaded_metadata_file is not None:
downloaded_dir_file_relpath = os.path.relpath(downloaded_dir_file, metadata_dir)
downloaded_dir_file_relpath = downloaded_dir_file_relpath.replace("\\", "/"... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
f"One or several metadata{metadata_ext} were found, but not in the same directory or in a parent directory of {downloaded_dir_file}."
)
else:
sample_metadata = {}
if add_labels:
sample... | 166 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py |
class Cache(datasets.ArrowBasedBuilder):
def __init__(
self,
cache_dir: Optional[str] = None,
dataset_name: Optional[str] = None,
config_name: Optional[str] = None,
version: Optional[str] = "0.0.0",
hash: Optional[str] = None,
base_path: Optional[str] = None,
... | 167 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/cache/cache.py |
if data_dir is not None:
config_kwargs["data_dir"] = data_dir
if hash == "auto" and version == "auto":
config_name, version, hash = _find_hash_in_cache(
dataset_name=repo_id or dataset_name,
config_name=config_name,
cache_dir=cache_dir,
... | 167 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/cache/cache.py |
def _info(self) -> datasets.DatasetInfo:
return datasets.DatasetInfo()
def download_and_prepare(self, output_dir: Optional[str] = None, *args, **kwargs):
if not os.path.exists(self.cache_dir):
raise ValueError(f"Cache directory for {self.dataset_name} doesn't exist at {self.cache_dir}")... | 167 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/cache/cache.py |
def _split_generators(self, dl_manager):
# used to stream from cache
if isinstance(self.info.splits, datasets.SplitDict):
split_infos: List[datasets.SplitInfo] = list(self.info.splits.values())
else:
raise ValueError(f"Missing splits info for {self.dataset_name} in cache ... | 167 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/cache/cache.py |
def _generate_tables(self, files):
# used to stream from cache
for file_idx, file in enumerate(files):
with open(file, "rb") as f:
try:
for batch_idx, record_batch in enumerate(pa.ipc.open_stream(f)):
pa_table = pa.Table.from_batche... | 167 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/cache/cache.py |
class ArrowConfig(datasets.BuilderConfig):
"""BuilderConfig for Arrow."""
features: Optional[datasets.Features] = None
def __post_init__(self):
super().__post_init__() | 168 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/arrow/arrow.py |
class Arrow(datasets.ArrowBasedBuilder):
BUILDER_CONFIG_CLASS = ArrowConfig
def _info(self):
return datasets.DatasetInfo(features=self.config.features) | 169 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/arrow/arrow.py |
def _split_generators(self, dl_manager):
"""We handle string, list and dicts in datafiles"""
if not self.config.data_files:
raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
dl_manager.download_config.extract_on_the_fly = True
... | 169 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/arrow/arrow.py |
except (OSError, pa.lib.ArrowInvalid):
reader = pa.ipc.open_file(f)
self.info.features = datasets.Features.from_arrow_schema(reader.schema)
break
splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs={"files": files}))
r... | 169 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/arrow/arrow.py |
def _cast_table(self, pa_table: pa.Table) -> pa.Table:
if self.info.features is not None:
# more expensive cast to support nested features with keys in a different order
# allows str <-> int/float or str to Audio for example
pa_table = table_cast(pa_table, self.info.features.... | 169 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/arrow/arrow.py |
def _generate_tables(self, files):
for file_idx, file in enumerate(itertools.chain.from_iterable(files)):
with open(file, "rb") as f:
try:
try:
batches = pa.ipc.open_stream(f)
except (OSError, pa.lib.ArrowInvalid):
... | 169 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/arrow/arrow.py |
except ValueError as e:
logger.error(f"Failed to read file '{file}' with error {type(e)}: {e}")
raise | 169 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/arrow/arrow.py |
class ImageFolderConfig(folder_based_builder.FolderBasedBuilderConfig):
"""BuilderConfig for ImageFolder."""
drop_labels: bool = None
drop_metadata: bool = None
def __post_init__(self):
super().__post_init__() | 170 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/imagefolder/imagefolder.py |
class ImageFolder(folder_based_builder.FolderBasedBuilder):
BASE_FEATURE = datasets.Image
BASE_COLUMN_NAME = "image"
BUILDER_CONFIG_CLASS = ImageFolderConfig
EXTENSIONS: List[str] # definition at the bottom of the script | 171 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/imagefolder/imagefolder.py |
class XmlConfig(datasets.BuilderConfig):
"""BuilderConfig for xml files."""
features: Optional[datasets.Features] = None
encoding: str = "utf-8"
encoding_errors: Optional[str] = None | 172 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/xml/xml.py |
class Xml(datasets.ArrowBasedBuilder):
BUILDER_CONFIG_CLASS = XmlConfig
def _info(self):
return datasets.DatasetInfo(features=self.config.features)
def _split_generators(self, dl_manager):
"""The `data_files` kwarg in load_dataset() can be a str, List[str], Dict[str,str], or Dict[str,List[... | 173 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/xml/xml.py |
If str or List[str], then the dataset returns only the 'train' split.
If dict, then keys should be from the `datasets.Split` enum.
"""
if not self.config.data_files:
raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
dl_... | 173 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/xml/xml.py |
def _cast_table(self, pa_table: pa.Table) -> pa.Table:
if self.config.features is not None:
schema = self.config.features.arrow_schema
if all(not require_storage_cast(feature) for feature in self.config.features.values()):
# cheaper cast
pa_table = pa_tabl... | 173 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/xml/xml.py |
def _generate_tables(self, files):
pa_table_names = list(self.config.features) if self.config.features is not None else ["xml"]
for file_idx, file in enumerate(itertools.chain.from_iterable(files)):
# open in text mode, by default translates universal newlines ("\n", "\r\n" and "\r") into "\... | 173 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/xml/xml.py |
class GeneratorConfig(datasets.BuilderConfig):
generator: Optional[Callable] = None
gen_kwargs: Optional[dict] = None
features: Optional[datasets.Features] = None
split: datasets.NamedSplit = datasets.Split.TRAIN
def __post_init__(self):
super().__post_init__()
if self.generator is ... | 174 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/generator/generator.py |
class Generator(datasets.GeneratorBasedBuilder):
BUILDER_CONFIG_CLASS = GeneratorConfig
def _info(self):
return datasets.DatasetInfo(features=self.config.features)
def _split_generators(self, dl_manager):
return [datasets.SplitGenerator(name=self.config.split, gen_kwargs=self.config.gen_kw... | 175 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/generator/generator.py |
class JsonConfig(datasets.BuilderConfig):
"""BuilderConfig for JSON."""
features: Optional[datasets.Features] = None
encoding: str = "utf-8"
encoding_errors: Optional[str] = None
field: Optional[str] = None
use_threads: bool = True # deprecated
block_size: Optional[int] = None # deprecate... | 176 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
class Json(datasets.ArrowBasedBuilder):
BUILDER_CONFIG_CLASS = JsonConfig
def _info(self):
if self.config.block_size is not None:
logger.warning("The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead")
self.config.chunksize = self.config.block_size... | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
def _split_generators(self, dl_manager):
"""We handle string, list and dicts in datafiles"""
if not self.config.data_files:
raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
dl_manager.download_config.extract_on_the_fly = True
... | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
def _cast_table(self, pa_table: pa.Table) -> pa.Table:
if self.config.features is not None:
# adding missing columns
for column_name in set(self.config.features) - set(pa_table.column_names):
type = self.config.features.arrow_schema.field(column_name).type
... | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
def _generate_tables(self, files):
for file_idx, file in enumerate(itertools.chain.from_iterable(files)):
# If the file is one json object and if we need to look at the items in one specific field
if self.config.field is not None:
with open(file, encoding=self.config.enco... | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
# If the file has one json object per line
else:
with open(file, "rb") as f:
batch_idx = 0
# Use block_size equal to the chunk size divided by 32 to leverage multithreading
# Set a default minimum value of 16kB if the chunk size is ... | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
# PyArrow only accepts utf-8 encoded bytes
if self.config.encoding != "utf-8":
batch = batch.decode(self.config.encoding, errors=encoding_errors).encode("utf-8")
try:
while True:
try:
... | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
else:
# Increase the block size in case it was too small.
# The block size will be reset for the next file.
logger.debug(
f"Batch of {len(batch)} bytes coul... | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
logger.error(f"Failed to load JSON from file '{file}' with error {type(e)}: {e}")
raise e
if df.columns.tolist() == [0]:
df.columns = list(self.config.features) if self.config.features else ["text"]
t... | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
yield (file_idx, batch_idx), self._cast_table(pa_table)
batch_idx += 1 | 177 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/json/json.py |
class CsvConfig(datasets.BuilderConfig):
"""BuilderConfig for CSV.""" | 178 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
sep: str = ","
delimiter: Optional[str] = None
header: Optional[Union[int, List[int], str]] = "infer"
names: Optional[List[str]] = None
column_names: Optional[List[str]] = None
index_col: Optional[Union[int, str, List[int], List[str]]] = None
usecols: Optional[Union[List[int], List[str]]] = None... | 178 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
quoting: int = 0
escapechar: Optional[str] = None
comment: Optional[str] = None
encoding: Optional[str] = None
dialect: Optional[str] = None
error_bad_lines: bool = True
warn_bad_lines: bool = True
skipfooter: int = 0
doublequote: bool = True
memory_map: bool = False
float_precis... | 178 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
def __post_init__(self):
super().__post_init__()
if self.delimiter is not None:
self.sep = self.delimiter
if self.column_names is not None:
self.names = self.column_names | 178 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
@property
def pd_read_csv_kwargs(self):
pd_read_csv_kwargs = {
"sep": self.sep,
"header": self.header,
"names": self.names,
"index_col": self.index_col,
"usecols": self.usecols,
"prefix": self.prefix,
"mangle_dupe_cols": sel... | 178 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
"quotechar": self.quotechar,
"quoting": self.quoting,
"escapechar": self.escapechar,
"comment": self.comment,
"encoding": self.encoding,
"dialect": self.dialect,
"error_bad_lines": self.error_bad_lines,
"warn_bad_lines": self.warn_bad_l... | 178 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
# some kwargs must not be passed if they don't have a default value
# some others are deprecated and we can also not pass them if they are the default value
for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
if pd_read_csv_kwargs[pd_... | 178 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
# Remove 2.2 deprecated arguments
if datasets.config.PANDAS_VERSION.release >= (2, 2):
for pd_read_csv_parameter in _PANDAS_READ_CSV_DEPRECATED_2_2_0_PARAMETERS:
if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig(), pd_read_csv_parameter):
del pd_re... | 178 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
class Csv(datasets.ArrowBasedBuilder):
BUILDER_CONFIG_CLASS = CsvConfig
def _info(self):
return datasets.DatasetInfo(features=self.config.features)
def _split_generators(self, dl_manager):
"""We handle string, list and dicts in datafiles"""
if not self.config.data_files:
... | 179 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
def _cast_table(self, pa_table: pa.Table) -> pa.Table:
if self.config.features is not None:
schema = self.config.features.arrow_schema
if all(not require_storage_cast(feature) for feature in self.config.features.values()):
# cheaper cast
pa_table = pa.Tabl... | 179 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
def _generate_tables(self, files):
schema = self.config.features.arrow_schema if self.config.features else None
# dtype allows reading an int column as str
dtype = (
{
name: dtype.to_pandas_dtype() if not require_storage_cast(feature) else object
for n... | 179 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
yield (file_idx, batch_idx), self._cast_table(pa_table)
except ValueError as e:
logger.error(f"Failed to read file '{file}' with error {type(e)}: {e}")
rai... | 179 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/csv/csv.py |
class TextConfig(datasets.BuilderConfig):
"""BuilderConfig for text files."""
features: Optional[datasets.Features] = None
encoding: str = "utf-8"
encoding_errors: Optional[str] = None
chunksize: int = 10 << 20 # 10MB
keep_linebreaks: bool = False
sample_by: str = "line" | 180 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/text/text.py |
class Text(datasets.ArrowBasedBuilder):
BUILDER_CONFIG_CLASS = TextConfig
def _info(self):
return datasets.DatasetInfo(features=self.config.features)
def _split_generators(self, dl_manager):
"""The `data_files` kwarg in load_dataset() can be a str, List[str], Dict[str,str], or Dict[str,Lis... | 181 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/text/text.py |
If str or List[str], then the dataset returns only the 'train' split.
If dict, then keys should be from the `datasets.Split` enum.
"""
if not self.config.data_files:
raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
dl_... | 181 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/text/text.py |
def _cast_table(self, pa_table: pa.Table) -> pa.Table:
if self.config.features is not None:
schema = self.config.features.arrow_schema
if all(not require_storage_cast(feature) for feature in self.config.features.values()):
# cheaper cast
pa_table = pa_tabl... | 181 | /Users/nielsrogge/Documents/python_projecten/datasets/src/datasets/packaged_modules/text/text.py |
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