Module namespace cleanup for v2.0

benchmarks/utils.py

@@ -3,7 +3,8 @@
 import numpy as np
 
 import datasets
-from datasets.features import _ArrayXD
+from datasets.arrow_writer import ArrowWriter
+from datasets.features.features import _ArrayXD
 
 
 def get_duration(func):
@@ -46,7 +47,7 @@ def generate_examples(features: dict, num_examples=100, seq_shapes=None):
 def generate_example_dataset(dataset_path, features, num_examples=100, seq_shapes=None):
     dummy_data = generate_examples(features, num_examples=num_examples, seq_shapes=seq_shapes)
 
-    with datasets.ArrowWriter(features=features, path=dataset_path) as writer:
+    with ArrowWriter(features=features, path=dataset_path) as writer:
         for key, record in dummy_data:
             example = features.encode_example(record)
             writer.write(example)

metrics/perplexity/perplexity.py

@@ -17,7 +17,7 @@
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 import datasets
-from datasets.utils import tqdm
+from datasets import utils
 
 
 _CITATION = """\
@@ -113,7 +113,7 @@ def _compute(self, input_texts, model_id, stride=512, device=None):
 
         ppls = []
 
-        for text_index in tqdm(range(0, len(encoded_texts))):
+        for text_index in utils.tqdm_utils.tqdm(range(0, len(encoded_texts))):
             encoded_text = encoded_texts[text_index]
             special_tokens_mask = special_tokens_masks[text_index]
 

src/datasets/__init__.py

@@ -20,36 +20,26 @@
 __version__ = "1.18.5.dev0"
 
 import pyarrow
-from packaging import version as _version
-from pyarrow import total_allocated_bytes
+from packaging import version
 
 
-if _version.parse(pyarrow.__version__).major < 5:
+if version.parse(pyarrow.__version__).major < 5:
     raise ImportWarning(
         "To use `datasets`, the module `pyarrow>=5.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"
         "If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."
     )
 
+SCRIPTS_VERSION = "master" if version.parse(__version__).is_devrelease else __version__
+
+del pyarrow
+del version
+
 from .arrow_dataset import Dataset, concatenate_datasets
-from .arrow_reader import ArrowReader, ReadInstruction
-from .arrow_writer import ArrowWriter
+from .arrow_reader import ReadInstruction
 from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
 from .combine import interleave_datasets
 from .dataset_dict import DatasetDict, IterableDatasetDict
-from .features import (
-    Array2D,
-    Array3D,
-    Array4D,
-    Array5D,
-    Audio,
-    ClassLabel,
-    Features,
-    Image,
-    Sequence,
-    Translation,
-    TranslationVariableLanguages,
-    Value,
-)
+from .features import *
 from .fingerprint import is_caching_enabled, set_caching_enabled
 from .info import DatasetInfo, MetricInfo
 from .inspect import (
@@ -63,8 +53,7 @@
     list_metrics,
 )
 from .iterable_dataset import IterableDataset
-from .keyhash import KeyHasher
-from .load import import_main_class, load_dataset, load_dataset_builder, load_from_disk, load_metric
+from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
 from .metric import Metric
 from .splits import (
     NamedSplit,
@@ -79,6 +68,4 @@
 )
 from .tasks import *
 from .utils import *
-
-
-SCRIPTS_VERSION = "master" if _version.parse(__version__).is_devrelease else __version__
+from .utils import logging

src/datasets/arrow_dataset.py

@@ -58,19 +58,8 @@
 from . import config, utils
 from .arrow_reader import ArrowReader
 from .arrow_writer import ArrowWriter, OptimizedTypedSequence
-from .features import (
-    Audio,
-    ClassLabel,
-    Features,
-    FeatureType,
-    Image,
-    Sequence,
-    Value,
-    _ArrayXD,
-    decode_nested_example,
-    pandas_types_mapper,
-    require_decoding,
-)
+from .features import Audio, ClassLabel, Features, Image, Sequence, Value
+from .features.features import FeatureType, _ArrayXD, decode_nested_example, pandas_types_mapper, require_decoding
 from .filesystems import extract_path_from_uri, is_remote_filesystem
 from .fingerprint import (
     fingerprint_transform,
@@ -2316,7 +2305,7 @@ def init_buffer_and_writer():
                     pbar_total = (num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size
                 pbar_unit = "ex" if not batched else "ba"
                 pbar_desc = (desc + " " if desc is not None else "") + "#" + str(rank) if rank is not None else desc
-                pbar = utils.tqdm(
+                pbar = utils.tqdm_utils.tqdm(
                     pbar_iterable,
                     total=pbar_total,
                     disable=disable_tqdm,
@@ -3465,7 +3454,7 @@ def delete_file(file):
             api.delete_file(file, repo_id=repo_id, token=token, repo_type="dataset", revision=branch)
 
         if len(file_shards_to_delete):
-            for file in utils.tqdm(
+            for file in utils.tqdm_utils.tqdm(
                 file_shards_to_delete,
                 desc="Deleting unused files from dataset repository",
                 total=len(file_shards_to_delete),
@@ -3474,7 +3463,7 @@ def delete_file(file):
                 delete_file(file)
 
         uploaded_size = 0
-        for index, shard in utils.tqdm(
+        for index, shard in utils.tqdm_utils.tqdm(
             enumerate(shards),
             desc="Pushing dataset shards to the dataset hub",
             total=num_shards,

src/datasets/arrow_reader.py

@@ -26,11 +26,10 @@
 import pyarrow as pa
 import pyarrow.parquet as pq
 
-from datasets.utils.file_utils import DownloadConfig
-
 from .naming import _split_re, filename_for_dataset_split
 from .table import InMemoryTable, MemoryMappedTable, Table, concat_tables
-from .utils import cached_path, logging
+from .utils import logging
+from .utils.file_utils import DownloadConfig, cached_path
 
 
 if TYPE_CHECKING:

src/datasets/arrow_writer.py

@@ -22,12 +22,10 @@
 import numpy as np
 import pyarrow as pa
 
-from datasets.features.features import FeatureType, Value
-
 from . import config, utils
-from .features import (
-    Features,
-    Image,
+from .features import Features, Image, Value
+from .features.features import (
+    FeatureType,
     _ArrayXDExtensionType,
     cast_to_python_objects,
     generate_from_arrow_type,
@@ -641,9 +639,9 @@ def parquet_to_arrow(sources, destination):
     stream = None if isinstance(destination, str) else destination
     disable = not utils.is_progress_bar_enabled()
     with ArrowWriter(path=destination, stream=stream) as writer:
-        for source in utils.tqdm(sources, unit="sources", disable=disable):
+        for source in utils.tqdm_utils.tqdm(sources, unit="sources", disable=disable):
             pf = pa.parquet.ParquetFile(source)
-            for i in utils.tqdm(range(pf.num_row_groups), unit="row_groups", leave=False, disable=disable):
+            for i in utils.tqdm_utils.tqdm(range(pf.num_row_groups), unit="row_groups", leave=False, disable=disable):
                 df = pf.read_row_group(i).to_pandas()
                 for col in df.columns:
                     df[col] = df[col].apply(json.loads)

src/datasets/builder.py

@@ -27,9 +27,6 @@
 from functools import partial
 from typing import Dict, Mapping, Optional, Tuple, Union
 
-from datasets.features import Features
-from datasets.utils.mock_download_manager import MockDownloadManager
-
 from . import config, utils
 from .arrow_dataset import Dataset
 from .arrow_reader import (
@@ -42,16 +39,26 @@
 from .arrow_writer import ArrowWriter, BeamWriter
 from .data_files import DataFilesDict, sanitize_patterns
 from .dataset_dict import DatasetDict, IterableDatasetDict
+from .features import Features
 from .fingerprint import Hasher
 from .info import DatasetInfo, DatasetInfosDict, PostProcessedInfo
 from .iterable_dataset import ExamplesIterable, IterableDataset, _generate_examples_from_tables_wrapper
 from .naming import camelcase_to_snakecase, filename_prefix_for_split
 from .splits import Split, SplitDict, SplitGenerator
 from .utils import logging
 from .utils.download_manager import DownloadManager, DownloadMode
-from .utils.file_utils import DownloadConfig, is_remote_url
+from .utils.file_utils import DownloadConfig, cached_path, is_remote_url
 from .utils.filelock import FileLock
 from .utils.info_utils import get_size_checksum_dict, verify_checksums, verify_splits
+from .utils.mock_download_manager import MockDownloadManager
+from .utils.py_utils import (
+    classproperty,
+    has_sufficient_disk_space,
+    map_nested,
+    memoize,
+    size_str,
+    temporary_assignment,
+)
 from .utils.streaming_download_manager import StreamingDownloadManager
 
 
@@ -389,9 +396,9 @@ def _create_builder_config(self, name=None, custom_features=None, **config_kwarg
 
         return builder_config, config_id
 
-    @utils.classproperty
+    @classproperty
     @classmethod
-    @utils.memoize()
+    @memoize()
     def builder_configs(cls):
         """Pre-defined list of configurations for this builder class."""
         configs = {config.name: config for config in cls.BUILDER_CONFIGS}
@@ -537,9 +544,9 @@ def download_and_prepare(
                 return
             logger.info(f"Generating dataset {self.name} ({self._cache_dir})")
             if not is_remote_url(self._cache_dir_root):  # if cache dir is local, check for available space
-                if not utils.has_sufficient_disk_space(self.info.size_in_bytes or 0, directory=self._cache_dir_root):
+                if not has_sufficient_disk_space(self.info.size_in_bytes or 0, directory=self._cache_dir_root):
                     raise OSError(
-                        f"Not enough disk space. Needed: {utils.size_str(self.info.size_in_bytes or 0)} (download: {utils.size_str(self.info.download_size or 0)}, generated: {utils.size_str(self.info.dataset_size or 0)}, post-processed: {utils.size_str(self.info.post_processing_size or 0)})"
+                        f"Not enough disk space. Needed: {size_str(self.info.size_in_bytes or 0)} (download: {size_str(self.info.download_size or 0)}, generated: {size_str(self.info.dataset_size or 0)}, post-processed: {size_str(self.info.post_processing_size or 0)})"
                     )
 
             @contextlib.contextmanager
@@ -565,9 +572,9 @@ def incomplete_dir(dirname):
             if self.info.size_in_bytes:
                 print(
                     f"Downloading and preparing dataset {self.info.builder_name}/{self.info.config_name} "
-                    f"(download: {utils.size_str(self.info.download_size)}, generated: {utils.size_str(self.info.dataset_size)}, "
-                    f"post-processed: {utils.size_str(self.info.post_processing_size)}, "
-                    f"total: {utils.size_str(self.info.size_in_bytes)}) to {self._cache_dir}..."
+                    f"(download: {size_str(self.info.download_size)}, generated: {size_str(self.info.dataset_size)}, "
+                    f"post-processed: {size_str(self.info.post_processing_size)}, "
+                    f"total: {size_str(self.info.size_in_bytes)}) to {self._cache_dir}..."
                 )
             else:
                 print(
@@ -580,7 +587,7 @@ def incomplete_dir(dirname):
             with incomplete_dir(self._cache_dir) as tmp_data_dir:
                 # Temporarily assign _cache_dir to tmp_data_dir to avoid having to forward
                 # it to every sub function.
-                with utils.temporary_assignment(self, "_cache_dir", tmp_data_dir):
+                with temporary_assignment(self, "_cache_dir", tmp_data_dir):
                     # Try to download the already prepared dataset files
                     downloaded_from_gcs = False
                     if try_from_hf_gcs:
@@ -637,7 +644,7 @@ def _download_prepared_from_hf_gcs(self, download_config: DownloadConfig):
                 if os.sep in resource_file_name:
                     raise ValueError(f"Resources shouldn't be in a sub-directory: {resource_file_name}")
                 try:
-                    resource_path = utils.cached_path(remote_cache_dir + "/" + resource_file_name)
+                    resource_path = cached_path(remote_cache_dir + "/" + resource_file_name)
                     shutil.move(resource_path, os.path.join(self._cache_dir, resource_file_name))
                 except ConnectionError:
                     logger.info(f"Couldn't download resourse file {resource_file_name} from Hf google storage.")
@@ -761,7 +768,7 @@ def as_dataset(
             split = {s: s for s in self.info.splits}
 
         # Create a dataset for each of the given splits
-        datasets = utils.map_nested(
+        datasets = map_nested(
             partial(
                 self._build_single_dataset,
                 run_post_process=run_post_process,
@@ -903,7 +910,7 @@ def as_streaming_dataset(
             raise ValueError(f"Bad split: {split}. Available splits: {list(splits_generators)}")
 
         # Create a dataset for each of the given splits
-        datasets = utils.map_nested(
+        datasets = map_nested(
             self._as_streaming_dataset_single,
             splits_generator,
             map_tuple=True,
@@ -1074,7 +1081,7 @@ def _prepare_split(self, split_generator):
             check_duplicates=True,
         ) as writer:
             try:
-                for key, record in utils.tqdm(
+                for key, record in utils.tqdm_utils.tqdm(
                     generator,
                     unit=" examples",
                     total=split_info.num_examples,
@@ -1135,7 +1142,7 @@ def _prepare_split(self, split_generator):
 
         generator = self._generate_tables(**split_generator.gen_kwargs)
         with ArrowWriter(features=self.info.features, path=fpath) as writer:
-            for key, table in utils.tqdm(
+            for key, table in utils.tqdm_utils.tqdm(
                 generator, unit=" tables", leave=False, disable=True  # not utils.is_progress_bar_enabled()
             ):
                 writer.write_table(table)

src/datasets/commands/dummy_data.py

@@ -11,10 +11,10 @@
 from datasets import config
 from datasets.commands import BaseDatasetsCLICommand
 from datasets.load import dataset_module_factory, import_main_class
-from datasets.utils import MockDownloadManager
 from datasets.utils.download_manager import DownloadManager
 from datasets.utils.file_utils import DownloadConfig
 from datasets.utils.logging import get_logger, set_verbosity_warning
+from datasets.utils.mock_download_manager import MockDownloadManager
 from datasets.utils.py_utils import map_nested
 
 

src/datasets/data_files.py

@@ -7,8 +7,7 @@
 from fsspec.implementations.local import LocalFileSystem
 from tqdm.contrib.concurrent import thread_map
 
-from datasets.filesystems.hffilesystem import HfFileSystem
-
+from .filesystems.hffilesystem import HfFileSystem
 from .splits import Split
 from .utils import logging
 from .utils.file_utils import hf_hub_url, is_remote_url, request_etag

src/datasets/features/__init__.py

@@ -1,12 +1,20 @@
 # flake8: noqa
+
+__all__ = [
+    "Audio",
+    "Array2D",
+    "Array3D",
+    "Array4D",
+    "Array5D",
+    "ClassLabel",
+    "Features",
+    "Sequence",
+    "Value",
+    "Image",
+    "Translation",
+    "TranslationVariableLanguages",
+]
 from .audio import Audio
-from .features import *
-from .features import (
-    _ArrayXD,
-    _ArrayXDExtensionType,
-    _arrow_to_datasets_dtype,
-    _cast_to_python_objects,
-    _is_zero_copy_only,
-)
-from .image import Image, objects_to_list_of_image_dicts
+from .features import Array2D, Array3D, Array4D, Array5D, ClassLabel, Features, Sequence, Value
+from .image import Image
 from .translation import Translation, TranslationVariableLanguages