venv/lib/python3.11/site-packages/webdataset/tenbin.py

#
# 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).
#

"""
Binary tensor encodings for PyTorch and NumPy.

This defines efficient binary encodings for tensors. The format is 8 byte
aligned and can be used directly for computations when transmitted, say,
via RDMA. The format is supported by WebDataset with the `.ten` filename
extension. It is also used by Tensorcom, Tensorcom RDMA, and can be used
for fast tensor storage with LMDB and in disk files (which can be memory
mapped)

Data is encoded as a series of chunks:

- magic number (int64)
- length in bytes (int64)
- bytes (multiple of 64 bytes long)

Arrays are a header chunk followed by a data chunk.
Header chunks have the following structure:

- dtype (int64)
- 8 byte array name
- ndim (int64)
- dim[0]
- dim[1]
- ...
"""

import struct
import sys

import numpy as np


def bytelen(a):
    """Determine the length of a in bytes."""
    if hasattr(a, "nbytes"):
        return a.nbytes
    elif isinstance(a, (bytearray, bytes)):
        return len(a)
    else:
        raise ValueError(a, "cannot determine nbytes")


def bytedata(a):
    """Return a the raw data corresponding to a."""
    if isinstance(a, (bytearray, bytes, memoryview)):
        return a
    elif hasattr(a, "data"):
        return a.data
    else:
        raise ValueError(a, "cannot return bytedata")


# tables for converting between long/short NumPy dtypes

long_to_short = """
float16 f2
float32 f4
float64 f8
int8 i1
int16 i2
int32 i4
int64 i8
uint8 u1
uint16 u2
unit32 u4
uint64 u8
""".strip()
long_to_short = [x.split() for x in long_to_short.split("\n")]
long_to_short = {x[0]: x[1] for x in long_to_short}
short_to_long = {v: k for k, v in long_to_short.items()}


def check_acceptable_input_type(data, allow64):
    """Check that the data has an acceptable type for tensor encoding.

    :param data: array
    :param allow64: allow 64 bit types
    """
    for a in data:
        if a.dtype.name not in long_to_short:
            raise ValueError("unsupported dataypte")
        if not allow64 and a.dtype.name not in ["float64", "int64", "uint64"]:
            raise ValueError("64 bit datatypes not allowed unless explicitly enabled")


def str64(s):
    """Convert a string to an int64."""
    s = s + "\0" * (8 - len(s))
    s = s.encode("ascii")
    return struct.unpack("@q", s)[0]


def unstr64(i):
    """Convert an int64 to a string."""
    b = struct.pack("@q", i)
    return b.decode("ascii").strip("\0")


def check_infos(data, infos, required_infos=None):
    """Verify the info strings."""
    if required_infos is False or required_infos is None:
        return data
    if required_infos is True:
        return data, infos
    if not isinstance(required_infos, (tuple, list)):
        raise ValueError("required_infos must be tuple or list")
    for required, actual in zip(required_infos, infos):
        raise ValueError(f"actual info {actual} doesn't match required info {required}")
    return data


def encode_header(a, info=""):
    """Encode an array header as a byte array."""
    if a.ndim >= 10:
        raise ValueError("too many dimensions")
    if a.nbytes != np.prod(a.shape) * a.itemsize:
        raise ValueError("mismatch between size and shape")
    if a.dtype.name not in long_to_short:
        raise ValueError("unsupported array type")
    header = [str64(long_to_short[a.dtype.name]), str64(info), len(a.shape)] + list(a.shape)
    return bytedata(np.array(header, dtype="i8"))


def decode_header(h):
    """Decode a byte array into an array header."""
    h = np.frombuffer(h, dtype="i8")
    if unstr64(h[0]) not in short_to_long:
        raise ValueError("unsupported array type")
    dtype = np.dtype(short_to_long[unstr64(h[0])])
    info = unstr64(h[1])
    rank = int(h[2])
    shape = tuple(h[3 : 3 + rank])
    return shape, dtype, info


def encode_list(l, infos=None):
    """Given a list of arrays, encode them into a list of byte arrays."""
    if infos is None:
        infos = [""]
    elif len(l) != len(infos):
        raise ValueError(f"length of list {l} must match length of infos {infos}")
    result = []
    for i, a in enumerate(l):
        header = encode_header(a, infos[i % len(infos)])
        result += [header, bytedata(a)]
    return result


def decode_list(l, infos=False):
    """Given a list of byte arrays, decode them into arrays."""
    result = []
    infos0 = []
    for header, data in zip(l[::2], l[1::2]):
        shape, dtype, info = decode_header(header)
        a = np.frombuffer(data, dtype=dtype, count=np.prod(shape)).reshape(*shape)
        result += [a]
        infos0 += [info]
    return check_infos(result, infos0, infos)


magic_str = "~TenBin~"
magic = str64(magic_str)
magic_bytes = unstr64(magic).encode("ascii")


def roundup(n, k=64):
    """Round up to the next multiple of 64."""
    return k * ((n + k - 1) // k)


def encode_chunks(l):
    """Encode a list of chunks into a single byte array, with lengths and magics.."""
    size = sum(16 + roundup(b.nbytes) for b in l)
    result = bytearray(size)
    offset = 0
    for b in l:
        result[offset : offset + 8] = magic_bytes
        offset += 8
        result[offset : offset + 8] = struct.pack("@q", b.nbytes)
        offset += 8
        result[offset : offset + bytelen(b)] = b
        offset += roundup(bytelen(b))
    return result


def decode_chunks(buf):
    """Decode a byte array into a list of chunks."""
    result = []
    offset = 0
    total = bytelen(buf)
    while offset < total:
        if magic_bytes != buf[offset : offset + 8]:
            raise ValueError("magic bytes mismatch")
        offset += 8
        nbytes = struct.unpack("@q", buf[offset : offset + 8])[0]
        offset += 8
        b = buf[offset : offset + nbytes]
        offset += roundup(nbytes)
        result.append(b)
    return result


def encode_buffer(l, infos=None):
    """Encode a list of arrays into a single byte array."""
    if not isinstance(l, list):
        raise ValueError("requires list")
    return encode_chunks(encode_list(l, infos=infos))


def decode_buffer(buf, infos=False):
    """Decode a byte array into a list of arrays."""
    return decode_list(decode_chunks(buf), infos=infos)


def write_chunk(stream, buf):
    """Write a byte chunk to the stream with magics, length, and padding."""
    nbytes = bytelen(buf)
    stream.write(magic_bytes)
    stream.write(struct.pack("@q", nbytes))
    stream.write(bytedata(buf))
    padding = roundup(nbytes) - nbytes
    if padding > 0:
        stream.write(b"\0" * padding)


def read_chunk(stream):
    """Read a byte chunk from a stream with magics, length, and padding."""
    magic = stream.read(8)
    if magic == b"":
        return None
    if magic != magic_bytes:
        raise ValueError("magic number does not match")
    nbytes = stream.read(8)
    nbytes = struct.unpack("@q", nbytes)[0]
    if nbytes < 0:
        raise ValueError("negative nbytes")
    data = stream.read(nbytes)
    padding = roundup(nbytes) - nbytes
    if padding > 0:
        stream.read(padding)
    return data


def write(stream, l, infos=None):
    """Write a list of arrays to a stream, with magics, length, and padding."""
    for chunk in encode_list(l, infos=infos):
        write_chunk(stream, chunk)


def read(stream, n=sys.maxsize, infos=False):
    """Read a list of arrays from a stream, with magics, length, and padding."""
    chunks = []
    for _ in range(n):
        header = read_chunk(stream)
        if header is None:
            break
        data = read_chunk(stream)
        if data is None:
            raise ValueError("premature EOF")
        chunks += [header, data]
    return decode_list(chunks, infos=infos)


def save(fname, *args, infos=None, nocheck=False):
    """Save a list of arrays to a file, with magics, length, and padding."""
    if not nocheck and not fname.endswith(".ten"):
        raise ValueError("file name should end in .ten")
    with open(fname, "wb") as stream:
        write(stream, args, infos=infos)


def load(fname, infos=False, nocheck=False):
    """Read a list of arrays from a file, with magics, length, and padding."""
    if not nocheck and not fname.endswith(".ten"):
        raise ValueError("file name should end in .ten")
    with open(fname, "rb") as stream:
        return read(stream, infos=infos)