Do several small refactorings

PiperOrigin-RevId: 704717347

tensorflow_datasets/core/data_sources/base.py

@@ -20,6 +20,7 @@
 import typing
 from typing import Any, Generic, Iterable, Protocol, SupportsIndex, TypeVar
 
+from absl import logging
 from tensorflow_datasets.core import dataset_info as dataset_info_lib
 from tensorflow_datasets.core import decode
 from tensorflow_datasets.core import splits as splits_lib

tensorflow_datasets/core/dataset_builder.py

@@ -1543,7 +1543,6 @@ def _as_dataset(
       file_format = file_adapters.FileFormat.from_value(file_format)
 
     reader = reader_lib.Reader(
-        self.data_dir,
         example_specs=example_specs,
         file_format=file_format,
     )

tensorflow_datasets/core/reader.py

@@ -17,10 +17,11 @@
 
 from __future__ import annotations
 
+from collections.abc import Sequence
 import functools
 import os
 import re
-from typing import Any, Callable, List, NamedTuple, Optional, Sequence
+from typing import Any, Callable, NamedTuple
 
 from absl import logging
 import numpy as np
@@ -63,7 +64,7 @@ def _get_dataset_from_filename(
     do_take: bool,
     file_format: file_adapters.FileFormat,
     add_tfds_id: bool,
-    override_buffer_size: Optional[int] = None,
+    override_buffer_size: int | None = None,
 ) -> tf.data.Dataset:
   """Returns a tf.data.Dataset instance from given instructions."""
   ds = file_adapters.ADAPTER_FOR_FORMAT[file_format].make_tf_data(
@@ -361,39 +362,38 @@ def _verify_read_config_for_ordered_dataset(
       logging.warning(error_message)
 
 
-class Reader(object):
+class Reader:
   """Build a tf.data.Dataset object out of Instruction instance(s).
 
   This class should not typically be exposed to the TFDS user.
   """
 
   def __init__(
       self,
-      path,  # TODO(b/216427814) remove this as it isn't used anymore
       example_specs,
-      file_format=file_adapters.DEFAULT_FILE_FORMAT,
+      file_format: (
+          str | file_adapters.FileFormat
+      ) = file_adapters.DEFAULT_FILE_FORMAT,
   ):
     """Initializes Reader.
 
     Args:
-      path (str): path where tfrecords are stored.
       example_specs: spec to build ExampleParser.
       file_format: file_adapters.FileFormat, format of the record files in which
         the dataset will be read/written from.
     """
-    self._path = path
     self._parser = example_parser.ExampleParser(example_specs)
-    self._file_format = file_format
+    self._file_format = file_adapters.FileFormat.from_value(file_format)
 
   def read(
       self,
       *,
       instructions: Tree[splits_lib.SplitArg],
-      split_infos: List[splits_lib.SplitInfo],
+      split_infos: Sequence[splits_lib.SplitInfo],
       read_config: read_config_lib.ReadConfig,
       shuffle_files: bool,
       disable_shuffling: bool = False,
-      decode_fn: Optional[DecodeFn] = None,
+      decode_fn: DecodeFn | None = None,
   ) -> Tree[tf.data.Dataset]:
     """Returns tf.data.Dataset instance(s).
 
@@ -417,8 +417,11 @@ def read(
 
     splits_dict = splits_lib.SplitDict(split_infos=split_infos)
 
-    def _read_instruction_to_ds(instruction):
-      file_instructions = splits_dict[instruction].file_instructions
+    def _read_instruction_to_ds(
+        instruction: splits_lib.SplitArg,
+    ) -> tf.data.Dataset:
+      split_info = splits_dict[instruction]
+      file_instructions = split_info.file_instructions
       return self.read_files(
           file_instructions,
           read_config=read_config,
@@ -436,7 +439,7 @@ def read_files(
       read_config: read_config_lib.ReadConfig,
       shuffle_files: bool,
       disable_shuffling: bool = False,
-      decode_fn: Optional[DecodeFn] = None,
+      decode_fn: DecodeFn | None = None,
   ) -> tf.data.Dataset:
     """Returns single tf.data.Dataset instance for the set of file instructions.
 

tensorflow_datasets/core/reader_test.py

@@ -76,7 +76,7 @@ def setUp(self):
     with mock.patch.object(
         example_parser, 'ExampleParser', testing.DummyParser
     ):
-      self.reader = reader_lib.Reader(self.tmp_dir, 'some_spec')
+      self.reader = reader_lib.Reader(self.tmp_dir, 'tfrecord')
       self.reader.read = functools.partial(
           self.reader.read,
           read_config=read_config_lib.ReadConfig(),

tensorflow_datasets/core/splits.py

@@ -18,7 +18,7 @@
 from __future__ import annotations
 
 import abc
-from collections.abc import Iterable
+from collections.abc import Iterable, Sequence
 import dataclasses
 import functools
 import itertools
@@ -123,7 +123,7 @@ def __post_init__(self):
   def get_available_shards(
       self,
       data_dir: epath.Path | None = None,
-      file_format: file_adapters.FileFormat | None = None,
+      file_format: str | file_adapters.FileFormat | None = None,
       strict_matching: bool = True,
   ) -> list[epath.Path]:
     """Returns the list of shards that are present in the data dir.
@@ -140,6 +140,7 @@ def get_available_shards(
     """
     if filename_template := self.filename_template:
       if file_format:
+        file_format = file_adapters.FileFormat.from_value(file_format)
         filename_template = filename_template.replace(
             filetype_suffix=file_format.file_suffix
         )
@@ -250,7 +251,9 @@ def replace(self, **kwargs: Any) -> SplitInfo:
     """Returns a copy of the `SplitInfo` with updated attributes."""
     return dataclasses.replace(self, **kwargs)
 
-  def file_spec(self, file_format: file_adapters.FileFormat) -> str:
+  def file_spec(
+      self, file_format: str | file_adapters.FileFormat
+  ) -> str | None:
     """Returns the file spec of the split for the given file format.
 
     A file spec is the full path with sharded notation, e.g.,
@@ -259,6 +262,7 @@ def file_spec(self, file_format: file_adapters.FileFormat) -> str:
     Args:
       file_format: the file format for which to create the file spec for.
     """
+    file_format = file_adapters.FileFormat.from_value(file_format)
     if filename_template := self.filename_template:
       if filename_template.filetype_suffix != file_format.file_suffix:
         raise ValueError(
@@ -268,9 +272,7 @@ def file_spec(self, file_format: file_adapters.FileFormat) -> str:
       return filename_template.sharded_filepaths_pattern(
           num_shards=self.num_shards
       )
-    raise ValueError(
-        f'Could not get filename template for split from split info: {self}.'
-    )
+    return None
 
 
 @dataclasses.dataclass(eq=False, frozen=True)
@@ -425,7 +427,7 @@ def __repr__(self) -> str:
 if typing.TYPE_CHECKING:
   # For type checking, `tfds.Split` is an alias for `str` with additional
   # `.TRAIN`, `.TEST`,... attributes. All strings are valid split type.
-  Split = Union[Split, str]
+  Split = Split | str
 
 
 class SplitDict(utils.NonMutableDict[str, SplitInfo]):
@@ -438,7 +440,7 @@ def __init__(
       # TODO(b/216470058): remove this parameter
       dataset_name: str | None = None,  # deprecated, please don't use
   ):
-    super(SplitDict, self).__init__(
+    super().__init__(
         {split_info.name: split_info for split_info in split_infos},
         error_msg='Split {key} already present',
     )
@@ -457,7 +459,7 @@ def __getitem__(self, key) -> SplitInfo | SubSplitInfo:
       )
     # 1st case: The key exists: `info.splits['train']`
     elif str(key) in self.keys():
-      return super(SplitDict, self).__getitem__(str(key))
+      return super().__getitem__(str(key))
     # 2nd case: Uses instructions: `info.splits['train[50%]']`
     else:
       instructions = _make_file_instructions(
@@ -543,7 +545,7 @@ def _file_instructions_for_split(
 
 
 def _make_file_instructions(
-    split_infos: list[SplitInfo],
+    split_infos: Sequence[SplitInfo],
     instruction: SplitArg,
 ) -> list[shard_utils.FileInstruction]:
   """Returns file instructions by applying the given instruction on the given splits.
@@ -587,7 +589,7 @@ class AbstractSplit(abc.ABC):
   """
 
   @classmethod
-  def from_spec(cls, spec: SplitArg) -> 'AbstractSplit':
+  def from_spec(cls, spec: SplitArg) -> AbstractSplit:
     """Creates a ReadInstruction instance out of a string spec.
 
     Args:
@@ -632,7 +634,7 @@ def to_absolute(self, split_infos) -> list[_AbsoluteInstruction]:
     """
     raise NotImplementedError
 
-  def __add__(self, other: Union[str, 'AbstractSplit']) -> 'AbstractSplit':
+  def __add__(self, other: str | AbstractSplit) -> AbstractSplit:
     """Sum of 2 splits."""
     if not isinstance(other, (str, AbstractSplit)):
       raise TypeError(f'Adding split {self!r} with non-split value: {other!r}')

tensorflow_datasets/core/splits_test.py

@@ -666,10 +666,11 @@ def test_file_spec_missing_template(self):
         num_bytes=42,
         filename_template=None,
     )
-    with self.assertRaises(ValueError):
-      split_info.file_spec(
-          file_format=tfds.core.file_adapters.FileFormat.TFRECORD
-      )
+    self.assertIsNone(
+        split_info.file_spec(
+            file_format=tfds.core.file_adapters.FileFormat.TFRECORD
+        )
+    )
 
   def test_get_available_shards(self):
     tmp_dir = epath.Path(self.tmp_dir)