deeplearning/modulus/modulus-core/_modules/modulus/utils/filesystem.html

Source code for modulus.utils.filesystem

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import hashlib
import json
import logging
import os
import re
import urllib.request
import zipfile

import fsspec
import fsspec.implementations.cached
import requests
import s3fs
from tqdm import tqdm

logger = logging.getLogger(__name__)

try:
    LOCAL_CACHE = os.environ["LOCAL_CACHE"]
except KeyError:
    LOCAL_CACHE = os.environ["HOME"] + "/.cache/modulus"


def _cache_fs(fs):
    return fsspec.implementations.cached.CachingFileSystem(
        fs=fs, cache_storage=LOCAL_CACHE
    )


def _get_fs(path):
    if path.startswith("s3://"):
        return s3fs.S3FileSystem(client_kwargs=dict(endpoint_url="https://pbss.s8k.io"))
    else:
        return fsspec.filesystem("file")


def _download_ngc_model_file(path: str, out_path: str, timeout: int = 300) -> str:
    """Pulls files from model registry on NGC. Supports private registries when NGC
    API key is set the the `NGC_API_KEY` environment variable. If download file is a zip
    folder it will get unzipped.

    Args:
        path (str): NGC model file path of form:
            `ngc://models/<org_id/team_id/model_id>@<version>/<path/in/repo>`
            or if no team
            `ngc://models/<org_id/model_id>@<version>/<path/in/repo>`
        out_path (str): Output path to save file / folder as
        timeout (int): Time out of requests, default 5 minutes

    Raises:
        ValueError: Invlaid url

    Returns:
        str: output file / folder path
    """
    # Strip ngc model url prefix
    suffix = "ngc://models/"
    # The regex check
    pattern = re.compile(f"{suffix}[\w-]+(/[\w-]+)?/[\w-]+@[A-Za-z0-9.]+/[\w/](.*)")
    if not pattern.match(path):
        raise ValueError(
            "Invalid URL, should be of form ngc://models/<org_id/team_id/model_id>@<version>/<path/in/repo>"
        )

    path = path.replace(suffix, "")
    if len(path.split("@")[0].split("/")) == 3:
        (org, team, model_version, filename) = path.split("/", 3)
        (model, version) = model_version.split("@", 1)
    else:
        (org, model_version, filename) = path.split("/", 2)
        (model, version) = model_version.split("@", 1)
        team = None

    token = ""
    # If API key environment variable
    if "NGC_API_KEY" in os.environ:
        try:
            # SSA tokens
            if os.environ["NGC_API_KEY"].startswith("nvapi-"):
                raise NotImplementedError("New personal keys not supported yet")
            # Legacy tokens
            # https://docs.nvidia.com/ngc/gpu-cloud/ngc-catalog-user-guide/index.html#download-models-via-wget-authenticated-access
            else:
                session = requests.Session()
                session.auth = ("$oauthtoken", os.environ["NGC_API_KEY"])
                headers = {"Accept": "application/json"}
                authn_url = f"https://authn.nvidia.com/token?service=ngc&scope=group/ngc:{org}&group/ngc:{org}/{team}"
                r = session.get(authn_url, headers=headers, timeout=5)
                r.raise_for_status()
                token = json.loads(r.content)["token"]
        except requests.exceptions.RequestException:
            logger.warning(
                "Failed to get JWT using the API set in NGC_API_KEY environment variable"
            )
            raise  # Re-raise the exception

    # Download file, apparently the URL for private registries is different than the public?
    if len(token) > 0:
        # Sloppy but works
        if team:
            file_url = f"https://api.ngc.nvidia.com/v2/org/{org}/team/{team}/models/{model}/versions/{version}/files/{filename}"
        else:
            file_url = f"https://api.ngc.nvidia.com/v2/org/{org}/models/{model}/versions/{version}/files/{filename}"
    else:
        if team:
            file_url = f"https://api.ngc.nvidia.com/v2/models/{org}/{team}/{model}/versions/{version}/files/{filename}"
        else:
            file_url = f"https://api.ngc.nvidia.com/v2/models/{org}/{model}/versions/{version}/files/{filename}"

    headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
    # Streaming here for larger files
    with requests.get(file_url, headers=headers, stream=True, timeout=timeout) as r:
        r.raise_for_status()
        total_size_in_bytes = int(r.headers.get("content-length", 0))
        chunk_size = 1024  # 1 kb
        progress_bar = tqdm(total=total_size_in_bytes, unit="iB", unit_scale=True)
        progress_bar.set_description(f"Fetching {filename}")
        with open(out_path, "wb") as f:
            for chunk in r.iter_content(chunk_size=chunk_size):
                progress_bar.update(len(chunk))
                f.write(chunk)
        progress_bar.close()

    # Unzip contents if zip file (most model files are)
    if zipfile.is_zipfile(out_path) and path.endswith(".zip"):
        temp_path = out_path + ".zip"
        os.rename(out_path, temp_path)
        with zipfile.ZipFile(temp_path, "r") as zip_ref:
            zip_ref.extractall(out_path)
        # Clean up zip
        os.remove(temp_path)

    return out_path


def _download_cached(
    path: str, recursive: bool = False, local_cache_path: str = LOCAL_CACHE
) -> str:
    sha = hashlib.sha256(path.encode())
    filename = sha.hexdigest()
    try:
        os.makedirs(local_cache_path, exist_ok=True)
    except PermissionError as error:
        logger.error(
            "Failed to create cache folder, check permissions or set a cache"
            + " location using the LOCAL_CACHE environment variable"
        )
        raise error
    except OSError as error:
        logger.error(
            "Failed to create cache folder, set a cache"
            + " location using the LOCAL_CACHE environment variable"
        )
        raise error

    cache_path = os.path.join(local_cache_path, filename)

    url = urllib.parse.urlparse(path)

    # TODO watch for race condition here
    if not os.path.exists(cache_path):
        logger.debug("Downloading %s to cache: %s", path, cache_path)
        if path.startswith("s3://"):
            fs = _get_fs(path)
            fs.get(path, cache_path, recursive=recursive)
        elif path.startswith("ngc://models/"):
            path = _download_ngc_model_file(path, cache_path)
            return path
        elif url.scheme == "http":
            # urllib.request.urlretrieve(path, cache_path)
            # TODO: Check if this supports directory fetches
            response = requests.get(path, stream=True, timeout=5)
            with open(cache_path, "wb") as output:
                for chunk in response.iter_content(chunk_size=8192):
                    if chunk:
                        output.write(chunk)
        elif url.scheme == "file":
            path = os.path.join(url.netloc, url.path)
            return path
        else:
            return path

    else:
        logger.debug("Opening from cache: %s", cache_path)

    return cache_path


[docs]class Package: """A generic file system abstraction. Can be used to represent local and remote file systems. Remote files are automatically fetched and stored in the $LOCAL_CACHE or $HOME/.cache/modulus folder. The `get` method can then be used to access files present. Presently one can use Package with the following directories: - Package("/path/to/local/directory") = local file system - Package("s3://bucket/path/to/directory") = object store file system - Package("http://url/path/to/directory") = http file system - Package("ngc://model/<org_id/team_id/model_id>@<version>") = ngc model file system Args: root (str): Root directory for file system seperator (str, optional): directory seperator. Defaults to "/". """ def __init__(self, root: str, seperator: str = "/"): self.root = root self.seperator = seperator
[docs] def get(self, path: str, recursive: bool = False) -> str: """Get a local path to the item at ``path`` ``path`` might be a remote file, in which case it is downloaded to a local cache at $LOCAL_CACHE or $HOME/.cache/modulus first. """ return _download_cached(self._fullpath(path), recursive=recursive)

def _fullpath(self, path): return self.root + self.seperator + path

© Copyright 2023, NVIDIA Modulus Team. Last updated on Apr 19, 2024.