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#
# Copyright (c) 2017-2021 NVIDIA CORPORATION. All rights reserved.
# This file is part of the WebDataset library.
# See the LICENSE file for licensing terms (BSD-style).
#
"""Classes and functions for writing tar files and WebDataset files."""
import gzip
import io
import json
import pickle
import re
import tarfile
import time
from typing import Any, Callable, Dict, Optional, Union
import numpy as np
from . import gopen
def imageencoder(image: Any, format: str = "PNG"): # skipcq: PYL-W0622
"""Compress an image using PIL and return it as a string.
Can handle float or uint8 images.
Args:
image: ndarray representing an image
format: compression format (PNG, JPEG, PPM)
Returns:
bytes: Compressed image data
Raises:
ValueError: If image values are out of range
"""
import PIL
import PIL.Image
assert isinstance(image, (PIL.Image.Image, np.ndarray)), type(image)
if isinstance(image, np.ndarray):
if image.dtype in [np.dtype("f"), np.dtype("d")]:
if np.amin(image) <= -0.001 or np.amax(image) >= 1.001:
raise ValueError(f"image values out of range {np.amin(image)} {np.amax(image)}")
image = np.clip(image, 0.0, 1.0)
image = np.array(image * 255.0, "uint8")
assert image.ndim in [2, 3]
if image.ndim == 3:
assert image.shape[2] in [1, 3]
image = PIL.Image.fromarray(image)
if format.upper() == "JPG":
format = "JPEG"
elif format.upper() in {"IMG", "IMAGE"}:
format = "PPM"
if format in {"JPEG", "tiff"}:
opts = dict(quality=100)
else:
opts = {}
with io.BytesIO() as result:
image.save(result, format=format, **opts)
return result.getvalue()
def bytestr(data: Any):
"""Convert data into a bytestring.
Uses str and ASCII encoding for data that isn't already in string format.
Args:
data: Data to be converted
Returns:
bytes: Converted bytestring
"""
if isinstance(data, bytes):
return data
if isinstance(data, str):
return data.encode("ascii")
return str(data).encode("ascii")
def torch_dumps(data: Any):
"""Dump data into a bytestring using torch.dumps.
This delays importing torch until needed.
Args:
data: Data to be dumped
Returns:
bytes: Dumped data as bytestring
"""
import io
import torch
stream = io.BytesIO()
torch.save(data, stream)
return stream.getvalue()
def numpy_dumps(data: np.ndarray):
"""Dump data into a bytestring using numpy npy format.
Args:
data: Data to be dumped
Returns:
bytes: Dumped data as bytestring
"""
import io
import numpy.lib.format
stream = io.BytesIO()
numpy.lib.format.write_array(stream, data)
return stream.getvalue()
def numpy_npz_dumps(data: Dict[str, np.ndarray]):
"""Dump data into a bytestring using numpy npz format.
Args:
data: Dictionary of numpy arrays to be dumped
Returns:
bytes: Dumped data as bytestring
Raises:
AssertionError: If input is not a dictionary of numpy arrays
"""
import io
assert isinstance(data, dict)
for k, v in list(data.items()):
assert isinstance(k, str)
assert isinstance(v, np.ndarray)
stream = io.BytesIO()
np.savez_compressed(stream, **data)
return stream.getvalue()
def tenbin_dumps(x):
"""Dump data into a bytestring using tenbin format.
Args:
x: Data to be dumped (list or single item)
Returns:
memoryview: Dumped data as memoryview
"""
from . import tenbin
if isinstance(x, list):
return memoryview(tenbin.encode_buffer(x))
else:
return memoryview(tenbin.encode_buffer([x]))
def cbor_dumps(x):
"""Dump data into a bytestring using CBOR format.
Args:
x: Data to be dumped
Returns:
bytes: Dumped data as bytestring
"""
import cbor # type: ignore
return cbor.dumps(x)
def mp_dumps(x):
"""Dump data into a bytestring using MessagePack format.
Args:
x: Data to be dumped
Returns:
bytes: Dumped data as bytestring
"""
import msgpack
return msgpack.packb(x)
def add_handlers(d, keys, value):
"""Add handlers to a dictionary for given keys.
Args:
d: Dictionary to add handlers to
keys: String of space-separated keys or list of keys
value: Handler function to be added
"""
if isinstance(keys, str):
keys = keys.split()
for k in keys:
d[k] = value
def make_handlers():
"""Create a list of handlers for encoding data.
Returns:
dict: Dictionary of handlers for different data types
"""
handlers = {}
add_handlers(handlers, "cls cls2 class count index inx id", lambda x: str(x).encode("ascii"))
add_handlers(handlers, "txt text transcript", lambda x: x.encode("utf-8"))
add_handlers(handlers, "html htm", lambda x: x.encode("utf-8"))
add_handlers(handlers, "pyd pickle", pickle.dumps)
add_handlers(handlers, "pth", torch_dumps)
add_handlers(handlers, "npy", numpy_dumps)
add_handlers(handlers, "npz", numpy_npz_dumps)
add_handlers(handlers, "ten tenbin tb", tenbin_dumps)
add_handlers(handlers, "json jsn", lambda x: json.dumps(x).encode("utf-8"))
add_handlers(handlers, "mp msgpack msg", mp_dumps)
add_handlers(handlers, "cbor", cbor_dumps)
add_handlers(handlers, "jpg jpeg img image", lambda data: imageencoder(data, "jpg"))
add_handlers(handlers, "png", lambda data: imageencoder(data, "png"))
add_handlers(handlers, "pbm", lambda data: imageencoder(data, "pbm"))
add_handlers(handlers, "pgm", lambda data: imageencoder(data, "pgm"))
add_handlers(handlers, "ppm", lambda data: imageencoder(data, "ppm"))
add_handlers(handlers, "tiff tif", lambda data: imageencoder(data, "tiff"))
return handlers
default_handlers = make_handlers()
def encode_based_on_extension1(data: Any, tname: str, handlers: dict):
"""Encode data based on its extension and a dict of handlers.
Args:
data: Data to be encoded
tname: File extension
handlers: Dictionary of handlers for different data types
Raises:
ValueError: If no handler is found for the given extension or if metadata values are not strings
"""
if tname[0] == "_":
if not isinstance(data, str):
raise ValueError("the values of metadata must be of string type")
return data
compress = False
if tname.endswith(".gz"):
compress = True
tname = tname[:-3]
extension = re.sub(r".*\.", "", tname).lower()
if isinstance(data, bytes):
if compress:
data = gzip.compress(data)
return data
if isinstance(data, str):
data = data.encode("utf-8")
if compress:
data = gzip.compress(data)
return data
handler = handlers.get(extension)
if handler is None:
raise ValueError(f"no handler found for {extension}")
result = handler(data)
if compress:
result = gzip.compress(result)
return result
def encode_based_on_extension(sample: dict, handlers: dict):
"""Encode an entire sample with a collection of handlers.
Args:
sample: Data sample (a dict)
handlers: Handlers for encoding
Returns:
dict: Encoded sample
"""
return {k: encode_based_on_extension1(v, k, handlers) for k, v in list(sample.items())}
def make_encoder(spec: Union[bool, str, dict, Callable]):
"""Make an encoder function from a specification.
Args:
spec: Specification for the encoder
Returns:
Callable: Encoder function
Raises:
ValueError: If the specification is invalid or doesn't yield a callable encoder
"""
if spec is False or spec is None:
def encoder(x):
"""Do not encode at all."""
return x
elif callable(spec):
encoder = spec
elif isinstance(spec, dict):
def f(sample):
"""Encode based on extension."""
return encode_based_on_extension(sample, spec)
encoder = f
elif spec is True:
handlers = default_handlers
def g(sample):
"""Encode based on extension."""
return encode_based_on_extension(sample, handlers)
encoder = g
else:
raise ValueError(f"{spec}: unknown decoder spec")
if not callable(encoder):
raise ValueError(f"{spec} did not yield a callable encoder")
return encoder
class TarWriter:
"""A class for writing dictionaries to tar files.
Args:
fileobj: File name for tar file (.tgz/.tar) or open file descriptor.
encoder: Sample encoding. Defaults to True.
compress: Compression flag. Defaults to None.
user: User for tar files. Defaults to "bigdata".
group: Group for tar files. Defaults to "bigdata".
mode: Mode for tar files. Defaults to 0o0444.
keep_meta: Flag to keep metadata (entries starting with "_"). Defaults to False.
mtime: Modification time. Defaults to None.
format: Tar format. Defaults to None.
Returns:
TarWriter object.
Raises:
ValueError: If the encoder doesn't yield bytes for a key.
`True` will use an encoder that behaves similar to the automatic
decoder for `Dataset`. `False` disables encoding and expects byte strings
(except for metadata, which must be strings). The `encoder` argument can
also be a `callable`, or a dictionary mapping extensions to encoders.
The following code will add two file to the tar archive: `a/b.png` and
`a/b.output.png`.
tarwriter = TarWriter(stream)
image = imread("b.jpg")
image2 = imread("b.out.jpg")
sample = {"__key__": "a/b", "png": image, "output.png": image2}
tarwriter.write(sample)
"""
def __init__(
self,
fileobj,
user: str = "bigdata",
group: str = "bigdata",
mode: int = 0o0444,
compress: Optional[Union[bool, str]] = None,
encoder: Union[None, bool, Callable] = True,
keep_meta: bool = False,
mtime: Optional[float] = None,
format: Any = None,
): # sourcery skip: avoid-builtin-shadow
"""Create a tar writer.
Args:
fileobj: Stream to write data to.
user: User for tar files.
group: Group for tar files.
mode: Mode for tar files.
compress: Desired compression.
encoder: Encoder function.
keep_meta: Keep metadata (entries starting with "_").
mtime: Modification time (set this to some fixed value to get reproducible tar files).
format: Tar format.
"""
format = getattr(tarfile, format, format) if format else tarfile.USTAR_FORMAT
self.mtime = mtime
tarmode = self.tarmode(fileobj, compress)
if isinstance(fileobj, str):
fileobj = gopen(fileobj, "wb")
self.own_fileobj = fileobj
else:
self.own_fileobj = None
self.encoder = make_encoder(encoder)
self.keep_meta = keep_meta
self.stream = fileobj
self.tarstream = tarfile.open(fileobj=fileobj, mode=tarmode)
self.user = user
self.group = group
self.mode = mode
self.compress = compress
def __enter__(self):
"""Enter context.
Returns:
self: The TarWriter object.
"""
return self
def __exit__(self, exc_type, exc_val, exc_tb):
"""Exit context."""
self.close()
def close(self):
"""Close the tar file."""
self.tarstream.close()
if self.own_fileobj is not None:
self.own_fileobj.close()
self.own_fileobj = None
def write(self, obj):
"""Write a dictionary to the tar file.
Args:
obj: Dictionary of objects to be stored.
Returns:
int: Size of the entry.
Raises:
ValueError: If the object doesn't contain a __key__ or if a key doesn't map to bytes after encoding.
"""
total = 0
obj = self.encoder(obj)
if "__key__" not in obj:
raise ValueError("object must contain a __key__")
for k, v in list(obj.items()):
if k[0] == "_":
continue
if not isinstance(v, (bytes, bytearray, memoryview)):
raise ValueError(f"{k} doesn't map to a bytes after encoding ({type(v)})")
key = obj["__key__"]
for k in sorted(obj.keys()):
if k == "__key__":
continue
if not self.keep_meta and k[0] == "_":
continue
v = obj[k]
if isinstance(v, str):
v = v.encode("utf-8")
now = time.time()
ti = tarfile.TarInfo(key + "." + k)
ti.size = len(v)
ti.mtime = self.mtime if self.mtime is not None else now
ti.mode = self.mode
ti.uname = self.user
ti.gname = self.group
if not isinstance(v, (bytes, bytearray, memoryview)):
raise ValueError(f"converter didn't yield bytes: {k}, {type(v)}")
stream = io.BytesIO(v)
self.tarstream.addfile(ti, stream)
total += ti.size
return total
@staticmethod
def tarmode(fileobj, compress: Optional[Union[bool, str]] = None):
if compress is False:
return "w|"
elif compress is True or compress == "gz" or (isinstance(fileobj, str) and fileobj.endswith("gz")):
return "w|gz"
elif compress == "bz2" or (isinstance(fileobj, str) and fileobj.endswith("bz2")):
return "w|bz2"
elif compress == "xz" or (isinstance(fileobj, str) and fileobj.endswith("xz")):
return "w|xz"
else:
return "w|"
class ShardWriter:
"""Like TarWriter but splits into multiple shards.
Args:
pattern: Output file pattern.
maxcount: Maximum number of records per shard. Defaults to 100000.
maxsize: Maximum size of each shard. Defaults to 3e9.
post: Optional callable to be executed after each shard is written. Defaults to None.
start_shard: Starting shard number. Defaults to 0.
verbose: Verbosity level. Defaults to 1.
opener: Optional callable to open output files. Defaults to None.
**kw: Other options passed to TarWriter.
"""
def __init__(
self,
pattern: str,
maxcount: int = 100000,
maxsize: float = 3e9,
post: Optional[Callable] = None,
start_shard: int = 0,
verbose: int = 1,
opener: Optional[Callable] = None,
**kw,
):
"""Create a ShardWriter.
Args:
pattern: Output file pattern.
maxcount: Maximum number of records per shard.
maxsize: Maximum size of each shard.
post: Optional callable to be executed after each shard is written.
start_shard: Starting shard number.
verbose: Verbosity level.
opener: Optional callable to open output files.
**kw: Other options passed to TarWriter.
"""
self.verbose = verbose
self.kw = kw
self.maxcount = maxcount
self.maxsize = maxsize
self.post = post
self.tarstream = None
self.shard = start_shard
self.pattern = pattern
self.total = 0
self.count = 0
self.size = 0
self.fname = None
self.opener = opener
self.next_stream()
def next_stream(self):
"""Close the current stream and move to the next."""
self.finish()
self.fname = self.pattern % self.shard
if self.verbose:
print(
"# writing",
self.fname,
self.count,
"%.1f GB" % (self.size / 1e9),
self.total,
)
self.shard += 1
if self.opener:
self.tarstream = TarWriter(self.opener(self.fname), **self.kw)
else:
self.tarstream = TarWriter(self.fname, **self.kw)
self.count = 0
self.size = 0
def write(self, obj):
"""Write a sample.
Args:
obj: Sample to be written.
"""
if self.tarstream is None or self.count >= self.maxcount or self.size >= self.maxsize:
self.next_stream()
size = self.tarstream.write(obj)
self.count += 1
self.total += 1
self.size += size
def finish(self):
"""Finish all writing (use close instead)."""
if self.tarstream is not None:
self.tarstream.close()
assert self.fname is not None
if callable(self.post):
self.post(self.fname)
self.tarstream = None
def close(self):
"""Close the stream."""
self.finish()
del self.tarstream
del self.shard
del self.count
del self.size
def __enter__(self):
"""Enter context.
Returns:
self: The ShardWriter object.
"""
return self
def __exit__(self, *args, **kw):
"""Exit context."""
self.close()