two version of R2R are hereHEADmaster

1 files changed, 387 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/huggingface_hub/serialization/_dduf.py b/.venv/lib/python3.12/site-packages/huggingface_hub/serialization/_dduf.py
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+import json
+import logging
+import mmap
+import os
+import shutil
+import zipfile
+from contextlib import contextmanager
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any, Dict, Generator, Iterable, Tuple, Union
+
+from ..errors import DDUFCorruptedFileError, DDUFExportError, DDUFInvalidEntryNameError
+
+
+logger = logging.getLogger(__name__)
+
+DDUF_ALLOWED_ENTRIES = {
+    # Allowed file extensions in a DDUF file
+    ".json",
+    ".model",
+    ".safetensors",
+    ".txt",
+}
+
+DDUF_FOLDER_REQUIRED_ENTRIES = {
+    # Each folder must contain at least one of these entries
+    "config.json",
+    "tokenizer_config.json",
+    "preprocessor_config.json",
+    "scheduler_config.json",
+}
+
+
+@dataclass
+class DDUFEntry:
+    """Object representing a file entry in a DDUF file.
+
+    See [`read_dduf_file`] for how to read a DDUF file.
+
+    Attributes:
+        filename (str):
+            The name of the file in the DDUF archive.
+        offset (int):
+            The offset of the file in the DDUF archive.
+        length (int):
+            The length of the file in the DDUF archive.
+        dduf_path (str):
+            The path to the DDUF archive (for internal use).
+    """
+
+    filename: str
+    length: int
+    offset: int
+
+    dduf_path: Path = field(repr=False)
+
+    @contextmanager
+    def as_mmap(self) -> Generator[bytes, None, None]:
+        """Open the file as a memory-mapped file.
+
+        Useful to load safetensors directly from the file.
+
+        Example:
+            ```py
+            >>> import safetensors.torch
+            >>> with entry.as_mmap() as mm:
+            ...     tensors = safetensors.torch.load(mm)
+            ```
+        """
+        with self.dduf_path.open("rb") as f:
+            with mmap.mmap(f.fileno(), length=0, access=mmap.ACCESS_READ) as mm:
+                yield mm[self.offset : self.offset + self.length]
+
+    def read_text(self, encoding: str = "utf-8") -> str:
+        """Read the file as text.
+
+        Useful for '.txt' and '.json' entries.
+
+        Example:
+            ```py
+            >>> import json
+            >>> index = json.loads(entry.read_text())
+            ```
+        """
+        with self.dduf_path.open("rb") as f:
+            f.seek(self.offset)
+            return f.read(self.length).decode(encoding=encoding)
+
+
+def read_dduf_file(dduf_path: Union[os.PathLike, str]) -> Dict[str, DDUFEntry]:
+    """
+    Read a DDUF file and return a dictionary of entries.
+
+    Only the metadata is read, the data is not loaded in memory.
+
+    Args:
+        dduf_path (`str` or `os.PathLike`):
+            The path to the DDUF file to read.
+
+    Returns:
+        `Dict[str, DDUFEntry]`:
+            A dictionary of [`DDUFEntry`] indexed by filename.
+
+    Raises:
+        - [`DDUFCorruptedFileError`]: If the DDUF file is corrupted (i.e. doesn't follow the DDUF format).
+
+    Example:
+        ```python
+        >>> import json
+        >>> import safetensors.torch
+        >>> from huggingface_hub import read_dduf_file
+
+        # Read DDUF metadata
+        >>> dduf_entries = read_dduf_file("FLUX.1-dev.dduf")
+
+        # Returns a mapping filename <> DDUFEntry
+        >>> dduf_entries["model_index.json"]
+        DDUFEntry(filename='model_index.json', offset=66, length=587)
+
+        # Load model index as JSON
+        >>> json.loads(dduf_entries["model_index.json"].read_text())
+        {'_class_name': 'FluxPipeline', '_diffusers_version': '0.32.0.dev0', '_name_or_path': 'black-forest-labs/FLUX.1-dev', ...
+
+        # Load VAE weights using safetensors
+        >>> with dduf_entries["vae/diffusion_pytorch_model.safetensors"].as_mmap() as mm:
+        ...     state_dict = safetensors.torch.load(mm)
+        ```
+    """
+    entries = {}
+    dduf_path = Path(dduf_path)
+    logger.info(f"Reading DDUF file {dduf_path}")
+    with zipfile.ZipFile(str(dduf_path), "r") as zf:
+        for info in zf.infolist():
+            logger.debug(f"Reading entry {info.filename}")
+            if info.compress_type != zipfile.ZIP_STORED:
+                raise DDUFCorruptedFileError("Data must not be compressed in DDUF file.")
+
+            try:
+                _validate_dduf_entry_name(info.filename)
+            except DDUFInvalidEntryNameError as e:
+                raise DDUFCorruptedFileError(f"Invalid entry name in DDUF file: {info.filename}") from e
+
+            offset = _get_data_offset(zf, info)
+
+            entries[info.filename] = DDUFEntry(
+                filename=info.filename, offset=offset, length=info.file_size, dduf_path=dduf_path
+            )
+
+    # Consistency checks on the DDUF file
+    if "model_index.json" not in entries:
+        raise DDUFCorruptedFileError("Missing required 'model_index.json' entry in DDUF file.")
+    index = json.loads(entries["model_index.json"].read_text())
+    _validate_dduf_structure(index, entries.keys())
+
+    logger.info(f"Done reading DDUF file {dduf_path}. Found {len(entries)} entries")
+    return entries
+
+
+def export_entries_as_dduf(
+    dduf_path: Union[str, os.PathLike], entries: Iterable[Tuple[str, Union[str, Path, bytes]]]
+) -> None:
+    """Write a DDUF file from an iterable of entries.
+
+    This is a lower-level helper than [`export_folder_as_dduf`] that allows more flexibility when serializing data.
+    In particular, you don't need to save the data on disk before exporting it in the DDUF file.
+
+    Args:
+        dduf_path (`str` or `os.PathLike`):
+            The path to the DDUF file to write.
+        entries (`Iterable[Tuple[str, Union[str, Path, bytes]]]`):
+            An iterable of entries to write in the DDUF file. Each entry is a tuple with the filename and the content.
+            The filename should be the path to the file in the DDUF archive.
+            The content can be a string or a pathlib.Path representing a path to a file on the local disk or directly the content as bytes.
+
+    Raises:
+        - [`DDUFExportError`]: If anything goes wrong during the export (e.g. invalid entry name, missing 'model_index.json', etc.).
+
+    Example:
+        ```python
+        # Export specific files from the local disk.
+        >>> from huggingface_hub import export_entries_as_dduf
+        >>> export_entries_as_dduf(
+        ...     dduf_path="stable-diffusion-v1-4-FP16.dduf",
+        ...     entries=[ # List entries to add to the DDUF file (here, only FP16 weights)
+        ...         ("model_index.json", "path/to/model_index.json"),
+        ...         ("vae/config.json", "path/to/vae/config.json"),
+        ...         ("vae/diffusion_pytorch_model.fp16.safetensors", "path/to/vae/diffusion_pytorch_model.fp16.safetensors"),
+        ...         ("text_encoder/config.json", "path/to/text_encoder/config.json"),
+        ...         ("text_encoder/model.fp16.safetensors", "path/to/text_encoder/model.fp16.safetensors"),
+        ...         # ... add more entries here
+        ...     ]
+        ... )
+        ```
+
+        ```python
+        # Export state_dicts one by one from a loaded pipeline
+        >>> from diffusers import DiffusionPipeline
+        >>> from typing import Generator, Tuple
+        >>> import safetensors.torch
+        >>> from huggingface_hub import export_entries_as_dduf
+        >>> pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
+        ... # ... do some work with the pipeline
+
+        >>> def as_entries(pipe: DiffusionPipeline) -> Generator[Tuple[str, bytes], None, None]:
+        ...     # Build an generator that yields the entries to add to the DDUF file.
+        ...     # The first element of the tuple is the filename in the DDUF archive (must use UNIX separator!). The second element is the content of the file.
+        ...     # Entries will be evaluated lazily when the DDUF file is created (only 1 entry is loaded in memory at a time)
+        ...     yield "vae/config.json", pipe.vae.to_json_string().encode()
+        ...     yield "vae/diffusion_pytorch_model.safetensors", safetensors.torch.save(pipe.vae.state_dict())
+        ...     yield "text_encoder/config.json", pipe.text_encoder.config.to_json_string().encode()
+        ...     yield "text_encoder/model.safetensors", safetensors.torch.save(pipe.text_encoder.state_dict())
+        ...     # ... add more entries here
+
+        >>> export_entries_as_dduf(dduf_path="stable-diffusion-v1-4.dduf", entries=as_entries(pipe))
+        ```
+    """
+    logger.info(f"Exporting DDUF file '{dduf_path}'")
+    filenames = set()
+    index = None
+    with zipfile.ZipFile(str(dduf_path), "w", zipfile.ZIP_STORED) as archive:
+        for filename, content in entries:
+            if filename in filenames:
+                raise DDUFExportError(f"Can't add duplicate entry: {filename}")
+            filenames.add(filename)
+
+            if filename == "model_index.json":
+                try:
+                    index = json.loads(_load_content(content).decode())
+                except json.JSONDecodeError as e:
+                    raise DDUFExportError("Failed to parse 'model_index.json'.") from e
+
+            try:
+                filename = _validate_dduf_entry_name(filename)
+            except DDUFInvalidEntryNameError as e:
+                raise DDUFExportError(f"Invalid entry name: {filename}") from e
+            logger.debug(f"Adding entry '{filename}' to DDUF file")
+            _dump_content_in_archive(archive, filename, content)
+
+    # Consistency checks on the DDUF file
+    if index is None:
+        raise DDUFExportError("Missing required 'model_index.json' entry in DDUF file.")
+    try:
+        _validate_dduf_structure(index, filenames)
+    except DDUFCorruptedFileError as e:
+        raise DDUFExportError("Invalid DDUF file structure.") from e
+
+    logger.info(f"Done writing DDUF file {dduf_path}")
+
+
+def export_folder_as_dduf(dduf_path: Union[str, os.PathLike], folder_path: Union[str, os.PathLike]) -> None:
+    """
+    Export a folder as a DDUF file.
+
+    AUses [`export_entries_as_dduf`] under the hood.
+
+    Args:
+        dduf_path (`str` or `os.PathLike`):
+            The path to the DDUF file to write.
+        folder_path (`str` or `os.PathLike`):
+            The path to the folder containing the diffusion model.
+
+    Example:
+        ```python
+        >>> from huggingface_hub import export_folder_as_dduf
+        >>> export_folder_as_dduf(dduf_path="FLUX.1-dev.dduf", folder_path="path/to/FLUX.1-dev")
+        ```
+    """
+    folder_path = Path(folder_path)
+
+    def _iterate_over_folder() -> Iterable[Tuple[str, Path]]:
+        for path in Path(folder_path).glob("**/*"):
+            if not path.is_file():
+                continue
+            if path.suffix not in DDUF_ALLOWED_ENTRIES:
+                logger.debug(f"Skipping file '{path}' (file type not allowed)")
+                continue
+            path_in_archive = path.relative_to(folder_path)
+            if len(path_in_archive.parts) >= 3:
+                logger.debug(f"Skipping file '{path}' (nested directories not allowed)")
+                continue
+            yield path_in_archive.as_posix(), path
+
+    export_entries_as_dduf(dduf_path, _iterate_over_folder())
+
+
+def _dump_content_in_archive(archive: zipfile.ZipFile, filename: str, content: Union[str, os.PathLike, bytes]) -> None:
+    with archive.open(filename, "w", force_zip64=True) as archive_fh:
+        if isinstance(content, (str, Path)):
+            content_path = Path(content)
+            with content_path.open("rb") as content_fh:
+                shutil.copyfileobj(content_fh, archive_fh, 1024 * 1024 * 8)  # type: ignore[misc]
+        elif isinstance(content, bytes):
+            archive_fh.write(content)
+        else:
+            raise DDUFExportError(f"Invalid content type for {filename}. Must be str, Path or bytes.")
+
+
+def _load_content(content: Union[str, Path, bytes]) -> bytes:
+    """Load the content of an entry as bytes.
+
+    Used only for small checks (not to dump content into archive).
+    """
+    if isinstance(content, (str, Path)):
+        return Path(content).read_bytes()
+    elif isinstance(content, bytes):
+        return content
+    else:
+        raise DDUFExportError(f"Invalid content type. Must be str, Path or bytes. Got {type(content)}.")
+
+
+def _validate_dduf_entry_name(entry_name: str) -> str:
+    if "." + entry_name.split(".")[-1] not in DDUF_ALLOWED_ENTRIES:
+        raise DDUFInvalidEntryNameError(f"File type not allowed: {entry_name}")
+    if "\\" in entry_name:
+        raise DDUFInvalidEntryNameError(f"Entry names must use UNIX separators ('/'). Got {entry_name}.")
+    entry_name = entry_name.strip("/")
+    if entry_name.count("/") > 1:
+        raise DDUFInvalidEntryNameError(f"DDUF only supports 1 level of directory. Got {entry_name}.")
+    return entry_name
+
+
+def _validate_dduf_structure(index: Any, entry_names: Iterable[str]) -> None:
+    """
+    Consistency checks on the DDUF file structure.
+
+    Rules:
+    - The 'model_index.json' entry is required and must contain a dictionary.
+    - Each folder name must correspond to an entry in 'model_index.json'.
+    - Each folder must contain at least a config file ('config.json', 'tokenizer_config.json', 'preprocessor_config.json', 'scheduler_config.json').
+
+    Args:
+        index (Any):
+            The content of the 'model_index.json' entry.
+        entry_names (Iterable[str]):
+            The list of entry names in the DDUF file.
+
+    Raises:
+        - [`DDUFCorruptedFileError`]: If the DDUF file is corrupted (i.e. doesn't follow the DDUF format).
+    """
+    if not isinstance(index, dict):
+        raise DDUFCorruptedFileError(f"Invalid 'model_index.json' content. Must be a dictionary. Got {type(index)}.")
+
+    dduf_folders = {entry.split("/")[0] for entry in entry_names if "/" in entry}
+    for folder in dduf_folders:
+        if folder not in index:
+            raise DDUFCorruptedFileError(f"Missing required entry '{folder}' in 'model_index.json'.")
+        if not any(f"{folder}/{required_entry}" in entry_names for required_entry in DDUF_FOLDER_REQUIRED_ENTRIES):
+            raise DDUFCorruptedFileError(
+                f"Missing required file in folder '{folder}'. Must contains at least one of {DDUF_FOLDER_REQUIRED_ENTRIES}."
+            )
+
+
+def _get_data_offset(zf: zipfile.ZipFile, info: zipfile.ZipInfo) -> int:
+    """
+    Calculate the data offset for a file in a ZIP archive.
+
+    Args:
+        zf (`zipfile.ZipFile`):
+            The opened ZIP file. Must be opened in read mode.
+        info (`zipfile.ZipInfo`):
+            The file info.
+
+    Returns:
+        int: The offset of the file data in the ZIP archive.
+    """
+    if zf.fp is None:
+        raise DDUFCorruptedFileError("ZipFile object must be opened in read mode.")
+
+    # Step 1: Get the local file header offset
+    header_offset = info.header_offset
+
+    # Step 2: Read the local file header
+    zf.fp.seek(header_offset)
+    local_file_header = zf.fp.read(30)  # Fixed-size part of the local header
+
+    if len(local_file_header) < 30:
+        raise DDUFCorruptedFileError("Incomplete local file header.")
+
+    # Step 3: Parse the header fields to calculate the start of file data
+    # Local file header: https://en.wikipedia.org/wiki/ZIP_(file_format)#File_headers
+    filename_len = int.from_bytes(local_file_header[26:28], "little")
+    extra_field_len = int.from_bytes(local_file_header[28:30], "little")
+
+    # Data offset is after the fixed header, filename, and extra fields
+    data_offset = header_offset + 30 + filename_len + extra_field_len
+
+    return data_offset