/
sequential_writer.py
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/
sequential_writer.py
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# coding=utf-8
# Copyright 2023 The TensorFlow Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Writer to sequentially write examples to disk."""
from __future__ import annotations
import dataclasses
import os
from typing import Any, Dict, List, Optional
from tensorflow_datasets.core import dataset_info
from tensorflow_datasets.core import example_serializer
from tensorflow_datasets.core import features as features_lib
from tensorflow_datasets.core import file_adapters
from tensorflow_datasets.core import naming
from tensorflow_datasets.core import splits as splits_lib
from tensorflow_datasets.core.utils import py_utils
from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow as tf
def _serialize_example(
example: Any,
features: features_lib.FeaturesDict,
serializer: example_serializer.ExampleSerializer,
) -> str:
try:
encoded_example = features.encode_example(example)
except Exception as e: # pylint: disable=broad-except
py_utils.reraise(
e, prefix='Failed to encode example:\n', suffix=f'{example}\n'
)
return serializer.serialize_example(encoded_example)
@dataclasses.dataclass
class Shard(object):
"""Shard that is being written."""
writer: tf.io.TFRecordWriter # TODO(sabela): use a file adapter
num_examples: int = 0
num_bytes: int = 0
def add_example(self, serialized_example: str) -> None:
"""Writes a new example."""
self.writer.write(serialized_example)
self.num_examples += 1
self.num_bytes += len(serialized_example)
def close_writer(self) -> None:
"""CLoses the writer."""
self.writer.flush()
self.writer.close()
@dataclasses.dataclass
class Split(object):
"""Information of a split that is being created."""
info: splits_lib.SplitInfo
current_shard: Optional[Shard] = None
complete_shards: int = 0
# The dataset name is taken from the builder class.
ds_name: str = ''
closed: bool = False
def add_example(self, serialized_example: str) -> None:
"""Adds an example to the shard.
If there is no open shard, it starts a new one.
Args:
serialized_example: example to add to the shard.
Raises:
ValueError: if the split is already closed.
"""
if self.closed:
raise ValueError(f'Split {self.info.name} is already closed.')
if self.current_shard is None:
path = self.info.filename_template.sharded_filepath(
shard_index=self.complete_shards, num_shards=None
)
self.current_shard = Shard(writer=tf.io.TFRecordWriter(os.fspath(path)))
self.current_shard.add_example(serialized_example)
def close_shard(self) -> None:
"""Finalizes a shard and updates the split metadata accordingly."""
if not self.current_shard:
return
self.current_shard.close_writer()
self.info = splits_lib.SplitInfo(
name=self.info.name,
shard_lengths=self.info.shard_lengths
+ [self.current_shard.num_examples],
num_bytes=self.info.num_bytes + self.current_shard.num_bytes,
filename_template=self.info.filename_template,
)
self.complete_shards += 1
self.current_shard = None
def close(self) -> None:
"""Closes the split (and the shard if it is still open)."""
if not self.closed and self.current_shard:
self.close_shard()
self.closed = True
def _split_dict(splits: Dict[str, Split]) -> splits_lib.SplitDict:
return splits_lib.SplitDict([split.info for _, split in splits.items()])
def _initialize_split(
split_name: str,
data_directory: Any,
ds_name: str,
filetype_suffix: str,
shard_lengths: Optional[List[int]] = None,
num_bytes: int = 0,
) -> Split:
"""Initializes a split.
Args:
split_name: name of the split.
data_directory: directory where the split data will be located.
ds_name: name of the dataset.
filetype_suffix: file format.
shard_lengths: if the split already has shards, it contains the list of the
shard lenghts. If None, it assumes that the split is empty.
num_bytes: number of bytes that have been written already.
Returns:
A Split.
"""
if not shard_lengths:
shard_lengths = []
filename_template = naming.ShardedFileTemplate(
dataset_name=ds_name,
data_dir=data_directory,
split=split_name,
filetype_suffix=filetype_suffix,
template='{DATASET}-{SPLIT}.{FILEFORMAT}-{SHARD_INDEX}',
)
return Split(
info=splits_lib.SplitInfo(
name=split_name,
shard_lengths=shard_lengths,
num_bytes=num_bytes,
filename_template=filename_template,
),
complete_shards=len(shard_lengths),
ds_name=ds_name,
)
class SequentialWriter:
"""Class to write a TFDS dataset sequentially.
The SequentialWriter can be used to generate TFDS datasets by directly
appending TF Examples to the desired splits.
Once the user creates a SequentialWriter with a given DatasetInfo, they can
create splits, append examples to them, and close them whenever they are
finished.
Note that:
* Not closing a split may cause data to be lost.
* The examples are written to disk in the same order that they are given to
the writer.
* Since the SequentialWriter doesn't know how many examples are going to be
written, it can't estimate the optimal number of shards per split. Use the
`max_examples_per_shard` parameter in the constructor to control how many
elements there should be per shard.
The datasets written with this writer can be read directly with
`tfds.builder_from_directories`.
Example:
writer = SequentialWriter(ds_info=ds_info, max_examples_per_shard=1000)
writer.initialize_splits(['train', 'test'])
while (...):
# Code that generates the examples
writer.add_examples({'train': [example1, example2],
'test': [example3]})
...
writer.close_splits()
"""
# TODO(sabela): add support for beam.
# TODO(sabela): add support for build_configs.
# TODO(sabela): support non-TFRecord writers. At the moment, the FileAdapters
# API only suports writing a set of examples, so the support for other formats
# would have to be manual.
def __init__(
self,
ds_info: dataset_info.DatasetInfo,
max_examples_per_shard: int,
overwrite: bool = True,
):
"""Creates a SequentialWriter.
Args:
ds_info: DatasetInfo for this dataset.
max_examples_per_shard: maximum number of examples to write per shard.
overwrite: if True, it ignores and overwrites any existing data.
Otherwise, it loads the existing dataset and appends the new data (new
data will always be created as new shards).
"""
self._data_dir = ds_info.data_dir
self._ds_name = ds_info.name
self._ds_info = ds_info
if not overwrite:
try:
self._ds_info.read_from_directory(self._data_dir)
# read_from_directory does some checks but not on the dataset name.
if self._ds_info.name != self._ds_name:
raise ValueError(
f'Trying to append a dataset with name {ds_info.name}'
f' to an existing dataset with name {self._ds_info.name}'
)
except FileNotFoundError:
self._ds_info.set_file_format(
file_format=file_adapters.FileFormat.TFRECORD,
# if it was set, we want this to fail to warn the user
override=False,
)
else:
self._ds_info.set_file_format(
file_format=file_adapters.FileFormat.TFRECORD,
# if it was set, we want this to fail to warn the user
override=False,
)
self._filetype_suffix = ds_info.file_format.file_suffix
self._max_examples_per_shard = max_examples_per_shard
self._splits = {}
if not overwrite:
for split_name, split in ds_info.splits.items():
self._splits[split_name] = _initialize_split(
split_name=split_name,
data_directory=self._data_dir,
ds_name=self._ds_name,
filetype_suffix=self._filetype_suffix,
shard_lengths=split.shard_lengths,
num_bytes=split.num_bytes,
)
self._serializer = example_serializer.ExampleSerializer(
self._ds_info.features.get_serialized_info()
)
def initialize_splits(
self, splits: List[str], fail_if_exists: bool = True
) -> None:
"""Adds new splits to the dataset.
Args:
splits: list of split names to add.
fail_if_exists: will fail if this split already contains data.
Raises:
KeyError: if the split is already present.
"""
for split in splits:
if split in self._splits:
if fail_if_exists:
raise KeyError(f'Split {split} was already initialized.')
else:
continue
self._splits[split] = _initialize_split(
split_name=split,
data_directory=self._data_dir,
ds_name=self._ds_name,
filetype_suffix=self._filetype_suffix,
)
self._write_splits_metadata()
def add_examples(self, split_examples: Dict[str, List[Any]]) -> None:
"""Adds examples to the splits.
Args:
split_examples: dictionary of `split_name`:list_of_examples that includes
the list of examples that has to be added to each of the splits. Not all
the existing splits have to be in the dictionary
Raises:
KeyError: if any of the splits doesn't exist.
"""
# Write the example and update the shard
for split_name, examples in split_examples.items():
split = self._splits.get(split_name, None)
if not split:
raise KeyError(f'Split {split} was not initialized.')
for example in examples:
serialized_example = _serialize_example(
example, self._ds_info.features, self._serializer
)
split.add_example(serialized_example)
if split.current_shard.num_examples >= self._max_examples_per_shard:
split.close_shard()
self._write_splits_metadata()
def _write_splits_metadata(self) -> None:
self._ds_info.set_splits(_split_dict(self._splits))
# Either writes the first metadata, or overwrites it.
self._ds_info.write_to_directory(self._data_dir)
def close_splits(self, splits: List[str]) -> None:
"""Closes the given list of splits.
Args:
splits: list of split names.
Raises:
KeyError: if any of the splits doesn't exist.
"""
for split_name in splits:
if split_name not in self._splits:
raise KeyError(f'Split {split_name} was not created.')
split = self._splits[split_name]
split.close()
self._write_splits_metadata()
def close_all(self) -> None:
"""Closes all the open splits."""
for _, split in self._splits.items():
split.close()
self._write_splits_metadata()