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import colorsys
import contextlib
import dataclasses
import enum
import functools
import gzip
import importlib
import importlib.util
import itertools
import json
import logging
import math
import numbers
import os
import pathlib
import platform
import queue
import random
import re
import secrets
import shlex
import socket
import string
import sys
import tarfile
import tempfile
import threading
import time
import types
import urllib
from dataclasses import asdict, is_dataclass
from datetime import date, datetime, timedelta
from importlib import import_module
from sys import getsizeof
from types import ModuleType
from typing import (
IO,
TYPE_CHECKING,
Callable,
Dict,
Iterable,
List,
Mapping,
Optional,
Sequence,
TextIO,
Tuple,
Union,
)
import requests
import yaml
from typing_extensions import Any, Generator, TypeGuard, TypeVar
import wandb
import wandb.env
from wandb.errors import (
AuthenticationError,
CommError,
UsageError,
WandbCoreNotAvailableError,
term,
)
from wandb.sdk.internal.thread_local_settings import _thread_local_api_settings
from wandb.sdk.lib import filesystem, runid
from wandb.sdk.lib.json_util import dump, dumps
from wandb.sdk.lib.paths import FilePathStr, StrPath
if TYPE_CHECKING:
import wandb.sdk.internal.settings_static
import wandb.sdk.wandb_settings
from wandb.sdk.artifacts.artifact import Artifact
CheckRetryFnType = Callable[[Exception], Union[bool, timedelta]]
T = TypeVar("T")
logger = logging.getLogger(__name__)
_not_importable = set()
LAUNCH_JOB_ARTIFACT_SLOT_NAME = "_wandb_job"
MAX_LINE_BYTES = (10 << 20) - (100 << 10) # imposed by back end
IS_GIT = os.path.exists(os.path.join(os.path.dirname(__file__), "..", ".git"))
# From https://docs.docker.com/engine/reference/commandline/tag/
# "Name components may contain lowercase letters, digits and separators.
# A separator is defined as a period, one or two underscores, or one or more dashes.
# A name component may not start or end with a separator."
DOCKER_IMAGE_NAME_SEPARATOR = "(?:__|[._]|[-]+)"
RE_DOCKER_IMAGE_NAME_SEPARATOR_START = re.compile("^" + DOCKER_IMAGE_NAME_SEPARATOR)
RE_DOCKER_IMAGE_NAME_SEPARATOR_END = re.compile(DOCKER_IMAGE_NAME_SEPARATOR + "$")
RE_DOCKER_IMAGE_NAME_SEPARATOR_REPEAT = re.compile(DOCKER_IMAGE_NAME_SEPARATOR + "{2,}")
RE_DOCKER_IMAGE_NAME_CHARS = re.compile(r"[^a-z0-9._\-]")
# these match the environments for gorilla
if IS_GIT:
SENTRY_ENV = "development"
else:
SENTRY_ENV = "production"
POW_10_BYTES = [
("B", 10**0),
("KB", 10**3),
("MB", 10**6),
("GB", 10**9),
("TB", 10**12),
("PB", 10**15),
("EB", 10**18),
]
POW_2_BYTES = [
("B", 2**0),
("KiB", 2**10),
("MiB", 2**20),
("GiB", 2**30),
("TiB", 2**40),
("PiB", 2**50),
("EiB", 2**60),
]
def vendor_setup() -> Callable:
"""Create a function that restores user paths after vendor imports.
This enables us to use the vendor directory for packages we don't depend on. Call
the returned function after imports are complete. If you don't you may modify the
user's path which is never good.
Usage:
```python
reset_path = vendor_setup()
# do any vendor imports...
reset_path()
```
"""
original_path = [directory for directory in sys.path]
def reset_import_path() -> None:
sys.path = original_path
parent_dir = os.path.abspath(os.path.dirname(__file__))
vendor_dir = os.path.join(parent_dir, "vendor")
vendor_packages = (
"gql-0.2.0",
"graphql-core-1.1",
"watchdog_0_9_0",
"promise-2.3.0",
)
package_dirs = [os.path.join(vendor_dir, p) for p in vendor_packages]
for p in [vendor_dir] + package_dirs:
if p not in sys.path:
sys.path.insert(1, p)
return reset_import_path
def vendor_import(name: str) -> Any:
reset_path = vendor_setup()
module = import_module(name)
reset_path()
return module
class LazyModuleState:
def __init__(self, module: types.ModuleType) -> None:
self.module = module
self.load_started = False
self.lock = threading.RLock()
def load(self) -> None:
with self.lock:
if self.load_started:
return
self.load_started = True
assert self.module.__spec__ is not None
assert self.module.__spec__.loader is not None
self.module.__spec__.loader.exec_module(self.module)
self.module.__class__ = types.ModuleType
# Set the submodule as an attribute on the parent module
# This enables access to the submodule via normal attribute access.
parent, _, child = self.module.__name__.rpartition(".")
if parent:
parent_module = sys.modules[parent]
setattr(parent_module, child, self.module)
class LazyModule(types.ModuleType):
def __getattribute__(self, name: str) -> Any:
state = object.__getattribute__(self, "__lazy_module_state__")
state.load()
return object.__getattribute__(self, name)
def __setattr__(self, name: str, value: Any) -> None:
state = object.__getattribute__(self, "__lazy_module_state__")
state.load()
object.__setattr__(self, name, value)
def __delattr__(self, name: str) -> None:
state = object.__getattribute__(self, "__lazy_module_state__")
state.load()
object.__delattr__(self, name)
def import_module_lazy(name: str) -> types.ModuleType:
"""Import a module lazily, only when it is used.
Inspired by importlib.util.LazyLoader, but improved so that the module loading is
thread-safe. Circular dependency between modules can lead to a deadlock if the two
modules are loaded from different threads.
:param (str) name: Dot-separated module path. E.g., 'scipy.stats'.
"""
try:
return sys.modules[name]
except KeyError:
spec = importlib.util.find_spec(name)
if spec is None:
raise ModuleNotFoundError
module = importlib.util.module_from_spec(spec)
module.__lazy_module_state__ = LazyModuleState(module) # type: ignore
module.__class__ = LazyModule
sys.modules[name] = module
return module
def get_module(
name: str,
required: Optional[Union[str, bool]] = None,
lazy: bool = True,
) -> Any:
"""Return module or None. Absolute import is required.
:param (str) name: Dot-separated module path. E.g., 'scipy.stats'.
:param (str) required: A string to raise a ValueError if missing
:param (bool) lazy: If True, return a lazy loader for the module.
:return: (module|None) If import succeeds, the module will be returned.
"""
if name not in _not_importable:
try:
if not lazy:
return import_module(name)
else:
return import_module_lazy(name)
except Exception:
_not_importable.add(name)
msg = f"Error importing optional module {name}"
if required:
logger.exception(msg)
if required and name in _not_importable:
raise wandb.Error(required)
def get_optional_module(name) -> Optional["importlib.ModuleInterface"]: # type: ignore
return get_module(name)
np = get_module("numpy")
pd_available = False
pandas_spec = importlib.util.find_spec("pandas")
if pandas_spec is not None:
pd_available = True
# TODO: Revisit these limits
VALUE_BYTES_LIMIT = 100000
def app_url(api_url: str) -> str:
"""Return the frontend app url without a trailing slash."""
# TODO: move me to settings
app_url = wandb.env.get_app_url()
if app_url is not None:
return str(app_url.strip("/"))
if "://api.wandb.test" in api_url:
# dev mode
return api_url.replace("://api.", "://app.").strip("/")
elif "://api.wandb." in api_url:
# cloud
return api_url.replace("://api.", "://").strip("/")
elif "://api." in api_url:
# onprem cloud
return api_url.replace("://api.", "://app.").strip("/")
# wandb/local
return api_url
def get_full_typename(o: Any) -> Any:
"""Determine types based on type names.
Avoids needing to to import (and therefore depend on) PyTorch, TensorFlow, etc.
"""
instance_name = o.__class__.__module__ + "." + o.__class__.__name__
if instance_name in ["builtins.module", "__builtin__.module"]:
return o.__name__
else:
return instance_name
def get_h5_typename(o: Any) -> Any:
typename = get_full_typename(o)
if is_tf_tensor_typename(typename):
return "tensorflow.Tensor"
elif is_pytorch_tensor_typename(typename):
return "torch.Tensor"
else:
return o.__class__.__module__.split(".")[0] + "." + o.__class__.__name__
def is_uri(string: str) -> bool:
parsed_uri = urllib.parse.urlparse(string)
return len(parsed_uri.scheme) > 0
def local_file_uri_to_path(uri: str) -> str:
"""Convert URI to local filesystem path.
No-op if the uri does not have the expected scheme.
"""
path = urllib.parse.urlparse(uri).path if uri.startswith("file:") else uri
return urllib.request.url2pathname(path)
def get_local_path_or_none(path_or_uri: str) -> Optional[str]:
"""Return path if local, None otherwise.
Return None if the argument is a local path (not a scheme or file:///). Otherwise
return `path_or_uri`.
"""
parsed_uri = urllib.parse.urlparse(path_or_uri)
if (
len(parsed_uri.scheme) == 0
or parsed_uri.scheme == "file"
and len(parsed_uri.netloc) == 0
):
return local_file_uri_to_path(path_or_uri)
else:
return None
def make_tarfile(
output_filename: str,
source_dir: str,
archive_name: str,
custom_filter: Optional[Callable] = None,
) -> None:
# Helper for filtering out modification timestamps
def _filter_timestamps(tar_info: "tarfile.TarInfo") -> Optional["tarfile.TarInfo"]:
tar_info.mtime = 0
return tar_info if custom_filter is None else custom_filter(tar_info)
descriptor, unzipped_filename = tempfile.mkstemp()
try:
with tarfile.open(unzipped_filename, "w") as tar:
tar.add(source_dir, arcname=archive_name, filter=_filter_timestamps)
# When gzipping the tar, don't include the tar's filename or modification time in the
# zipped archive (see https://docs.python.org/3/library/gzip.html#gzip.GzipFile)
with gzip.GzipFile(
filename="", fileobj=open(output_filename, "wb"), mode="wb", mtime=0
) as gzipped_tar, open(unzipped_filename, "rb") as tar_file:
gzipped_tar.write(tar_file.read())
finally:
os.close(descriptor)
os.remove(unzipped_filename)
def is_tf_tensor(obj: Any) -> bool:
import tensorflow # type: ignore
return isinstance(obj, tensorflow.Tensor)
def is_tf_tensor_typename(typename: str) -> bool:
return typename.startswith("tensorflow.") and (
"Tensor" in typename or "Variable" in typename
)
def is_tf_eager_tensor_typename(typename: str) -> bool:
return typename.startswith("tensorflow.") and ("EagerTensor" in typename)
def is_pytorch_tensor(obj: Any) -> bool:
import torch # type: ignore
return isinstance(obj, torch.Tensor)
def is_pytorch_tensor_typename(typename: str) -> bool:
return typename.startswith("torch.") and (
"Tensor" in typename or "Variable" in typename
)
def is_jax_tensor_typename(typename: str) -> bool:
return typename.startswith("jaxlib.") and "Array" in typename
def get_jax_tensor(obj: Any) -> Optional[Any]:
import jax # type: ignore
return jax.device_get(obj)
def is_fastai_tensor_typename(typename: str) -> bool:
return typename.startswith("fastai.") and ("Tensor" in typename)
def is_pandas_data_frame_typename(typename: str) -> bool:
return typename.startswith("pandas.") and "DataFrame" in typename
def is_matplotlib_typename(typename: str) -> bool:
return typename.startswith("matplotlib.")
def is_plotly_typename(typename: str) -> bool:
return typename.startswith("plotly.")
def is_plotly_figure_typename(typename: str) -> bool:
return typename.startswith("plotly.") and typename.endswith(".Figure")
def is_numpy_array(obj: Any) -> bool:
return np and isinstance(obj, np.ndarray)
def is_pandas_data_frame(obj: Any) -> bool:
if pd_available:
import pandas as pd
return isinstance(obj, pd.DataFrame)
else:
return is_pandas_data_frame_typename(get_full_typename(obj))
def ensure_matplotlib_figure(obj: Any) -> Any:
"""Extract the current figure from a matplotlib object.
Return the object itself if it's a figure.
Raises ValueError if the object can't be converted.
"""
import matplotlib # type: ignore
from matplotlib.figure import Figure # type: ignore
# there are combinations of plotly and matplotlib versions that don't work well together,
# this patches matplotlib to add a removed method that plotly assumes exists
from matplotlib.spines import Spine # type: ignore
def is_frame_like(self: Any) -> bool:
"""Return True if directly on axes frame.
This is useful for determining if a spine is the edge of an
old style MPL plot. If so, this function will return True.
"""
position = self._position or ("outward", 0.0)
if isinstance(position, str):
if position == "center":
position = ("axes", 0.5)
elif position == "zero":
position = ("data", 0)
if len(position) != 2:
raise ValueError("position should be 2-tuple")
position_type, amount = position # type: ignore
if position_type == "outward" and amount == 0:
return True
else:
return False
Spine.is_frame_like = is_frame_like
if obj == matplotlib.pyplot:
obj = obj.gcf()
elif not isinstance(obj, Figure):
if hasattr(obj, "figure"):
obj = obj.figure
# Some matplotlib objects have a figure function
if not isinstance(obj, Figure):
raise ValueError(
"Only matplotlib.pyplot or matplotlib.pyplot.Figure objects are accepted."
)
return obj
def matplotlib_to_plotly(obj: Any) -> Any:
obj = ensure_matplotlib_figure(obj)
tools = get_module(
"plotly.tools",
required=(
"plotly is required to log interactive plots, install with: "
"`pip install plotly` or convert the plot to an image with `wandb.Image(plt)`"
),
)
return tools.mpl_to_plotly(obj)
def matplotlib_contains_images(obj: Any) -> bool:
obj = ensure_matplotlib_figure(obj)
return any(len(ax.images) > 0 for ax in obj.axes)
def _numpy_generic_convert(obj: Any) -> Any:
obj = obj.item()
if isinstance(obj, float) and math.isnan(obj):
obj = None
elif isinstance(obj, np.generic) and (
obj.dtype.kind == "f" or obj.dtype == "bfloat16"
):
# obj is a numpy float with precision greater than that of native python float
# (i.e., float96 or float128) or it is of custom type such as bfloat16.
# in these cases, obj.item() does not return a native
# python float (in the first case - to avoid loss of precision,
# so we need to explicitly cast this down to a 64bit float)
obj = float(obj)
return obj
def _sanitize_numpy_keys(
d: Dict,
visited: Optional[Dict[int, Dict]] = None,
) -> Tuple[Dict, bool]:
"""Returns a dictionary where all NumPy keys are converted.
Args:
d: The dictionary to sanitize.
Returns:
A sanitized dictionary, and a boolean indicating whether anything was
changed.
"""
out: Dict[Any, Any] = dict()
converted = False
# Work with recursive dictionaries: if a dictionary has already been
# converted, reuse its converted value to retain the recursive structure
# of the input.
if visited is None:
visited = {id(d): out}
elif id(d) in visited:
return visited[id(d)], False
visited[id(d)] = out
for key, value in d.items():
if isinstance(value, dict):
value, converted_value = _sanitize_numpy_keys(value, visited)
converted |= converted_value
if isinstance(key, np.generic):
key = _numpy_generic_convert(key)
converted = True
out[key] = value
return out, converted
def json_friendly( # noqa: C901
obj: Any,
) -> Union[Tuple[Any, bool], Tuple[Union[None, str, float], bool]]:
"""Convert an object into something that's more becoming of JSON."""
converted = True
typename = get_full_typename(obj)
if is_tf_eager_tensor_typename(typename):
obj = obj.numpy()
elif is_tf_tensor_typename(typename):
try:
obj = obj.eval()
except RuntimeError:
obj = obj.numpy()
elif is_pytorch_tensor_typename(typename) or is_fastai_tensor_typename(typename):
try:
if obj.requires_grad:
obj = obj.detach()
except AttributeError:
pass # before 0.4 is only present on variables
try:
obj = obj.data
except RuntimeError:
pass # happens for Tensors before 0.4
if obj.size():
obj = obj.cpu().detach().numpy()
else:
return obj.item(), True
elif is_jax_tensor_typename(typename):
obj = get_jax_tensor(obj)
if is_numpy_array(obj):
if obj.size == 1:
obj = obj.flatten()[0]
elif obj.size <= 32:
obj = obj.tolist()
elif np and isinstance(obj, np.generic):
obj = _numpy_generic_convert(obj)
elif isinstance(obj, bytes):
obj = obj.decode("utf-8")
elif isinstance(obj, (datetime, date)):
obj = obj.isoformat()
elif callable(obj):
obj = (
f"{obj.__module__}.{obj.__qualname__}"
if hasattr(obj, "__qualname__") and hasattr(obj, "__module__")
else str(obj)
)
elif isinstance(obj, float) and math.isnan(obj):
obj = None
elif isinstance(obj, dict) and np:
obj, converted = _sanitize_numpy_keys(obj)
elif isinstance(obj, set):
# set is not json serializable, so we convert it to tuple
obj = tuple(obj)
elif isinstance(obj, enum.Enum):
obj = obj.name
else:
converted = False
if getsizeof(obj) > VALUE_BYTES_LIMIT:
wandb.termwarn(
f"Serializing object of type {type(obj).__name__} that is {getsizeof(obj)} bytes"
)
return obj, converted
def json_friendly_val(val: Any) -> Any:
"""Make any value (including dict, slice, sequence, dataclass) JSON friendly."""
converted: Union[dict, list]
if isinstance(val, dict):
converted = {}
for key, value in val.items():
converted[key] = json_friendly_val(value)
return converted
if isinstance(val, slice):
converted = dict(
slice_start=val.start, slice_step=val.step, slice_stop=val.stop
)
return converted
val, _ = json_friendly(val)
if isinstance(val, Sequence) and not isinstance(val, str):
converted = []
for value in val:
converted.append(json_friendly_val(value))
return converted
if is_dataclass(val) and not isinstance(val, type):
converted = asdict(val)
return converted
else:
if val.__class__.__module__ not in ("builtins", "__builtin__"):
val = str(val)
return val
def alias_is_version_index(alias: str) -> bool:
return len(alias) >= 2 and alias[0] == "v" and alias[1:].isnumeric()
def convert_plots(obj: Any) -> Any:
if is_matplotlib_typename(get_full_typename(obj)):
tools = get_module(
"plotly.tools",
required=(
"plotly is required to log interactive plots, install with: "
"`pip install plotly` or convert the plot to an image with `wandb.Image(plt)`"
),
)
obj = tools.mpl_to_plotly(obj)
if is_plotly_typename(get_full_typename(obj)):
return {"_type": "plotly", "plot": obj.to_plotly_json()}
else:
return obj
def maybe_compress_history(obj: Any) -> Tuple[Any, bool]:
if np and isinstance(obj, np.ndarray) and obj.size > 32:
return wandb.Histogram(obj, num_bins=32).to_json(), True
else:
return obj, False
def maybe_compress_summary(obj: Any, h5_typename: str) -> Tuple[Any, bool]:
if np and isinstance(obj, np.ndarray) and obj.size > 32:
return (
{
"_type": h5_typename, # may not be ndarray
"var": np.var(obj).item(),
"mean": np.mean(obj).item(),
"min": np.amin(obj).item(),
"max": np.amax(obj).item(),
"10%": np.percentile(obj, 10),
"25%": np.percentile(obj, 25),
"75%": np.percentile(obj, 75),
"90%": np.percentile(obj, 90),
"size": obj.size,
},
True,
)
else:
return obj, False
def launch_browser(attempt_launch_browser: bool = True) -> bool:
"""Decide if we should launch a browser."""
_display_variables = ["DISPLAY", "WAYLAND_DISPLAY", "MIR_SOCKET"]
_webbrowser_names_blocklist = ["www-browser", "lynx", "links", "elinks", "w3m"]
import webbrowser
launch_browser = attempt_launch_browser
if launch_browser:
if "linux" in sys.platform and not any(
os.getenv(var) for var in _display_variables
):
launch_browser = False
try:
browser = webbrowser.get()
if hasattr(browser, "name") and browser.name in _webbrowser_names_blocklist:
launch_browser = False
except webbrowser.Error:
launch_browser = False
return launch_browser
def generate_id(length: int = 8) -> str:
# Do not use this; use wandb.sdk.lib.runid.generate_id instead.
# This is kept only for legacy code.
return runid.generate_id(length)
def parse_tfjob_config() -> Any:
"""Attempt to parse TFJob config, returning False if it can't find it."""
if os.getenv("TF_CONFIG"):
try:
return json.loads(os.environ["TF_CONFIG"])
except ValueError:
return False
else:
return False
class WandBJSONEncoder(json.JSONEncoder):
"""A JSON Encoder that handles some extra types."""
def default(self, obj: Any) -> Any:
if hasattr(obj, "json_encode"):
return obj.json_encode()
# if hasattr(obj, 'to_json'):
# return obj.to_json()
tmp_obj, converted = json_friendly(obj)
if converted:
return tmp_obj
return json.JSONEncoder.default(self, obj)
class WandBJSONEncoderOld(json.JSONEncoder):
"""A JSON Encoder that handles some extra types."""
def default(self, obj: Any) -> Any:
tmp_obj, converted = json_friendly(obj)
tmp_obj, compressed = maybe_compress_summary(tmp_obj, get_h5_typename(obj))
if converted:
return tmp_obj
return json.JSONEncoder.default(self, tmp_obj)
class WandBHistoryJSONEncoder(json.JSONEncoder):
"""A JSON Encoder that handles some extra types.
This encoder turns numpy like objects with a size > 32 into histograms.
"""
def default(self, obj: Any) -> Any:
obj, converted = json_friendly(obj)
obj, compressed = maybe_compress_history(obj)
if converted:
return obj
return json.JSONEncoder.default(self, obj)
class JSONEncoderUncompressed(json.JSONEncoder):
"""A JSON Encoder that handles some extra types.
This encoder turns numpy like objects with a size > 32 into histograms.
"""
def default(self, obj: Any) -> Any:
if is_numpy_array(obj):
return obj.tolist()
elif np and isinstance(obj, np.number):
return obj.item()
elif np and isinstance(obj, np.generic):
obj = obj.item()
return json.JSONEncoder.default(self, obj)
def json_dump_safer(obj: Any, fp: IO[str], **kwargs: Any) -> None:
"""Convert obj to json, with some extra encodable types."""
return dump(obj, fp, cls=WandBJSONEncoder, **kwargs)
def json_dumps_safer(obj: Any, **kwargs: Any) -> str:
"""Convert obj to json, with some extra encodable types."""
return dumps(obj, cls=WandBJSONEncoder, **kwargs)
# This is used for dumping raw json into files
def json_dump_uncompressed(obj: Any, fp: IO[str], **kwargs: Any) -> None:
"""Convert obj to json, with some extra encodable types."""
return dump(obj, fp, cls=JSONEncoderUncompressed, **kwargs)
def json_dumps_safer_history(obj: Any, **kwargs: Any) -> str:
"""Convert obj to json, with some extra encodable types, including histograms."""
return dumps(obj, cls=WandBHistoryJSONEncoder, **kwargs)
def make_json_if_not_number(
v: Union[int, float, str, Mapping, Sequence],
) -> Union[int, float, str]:
"""If v is not a basic type convert it to json."""
if isinstance(v, (float, int)):
return v
return json_dumps_safer(v)
def make_safe_for_json(obj: Any) -> Any:
"""Replace invalid json floats with strings. Also converts to lists and dicts."""
if isinstance(obj, Mapping):
return {k: make_safe_for_json(v) for k, v in obj.items()}
elif isinstance(obj, str):
# str's are Sequence, so we need to short-circuit
return obj
elif isinstance(obj, Sequence):
return [make_safe_for_json(v) for v in obj]
elif isinstance(obj, float):
# W&B backend and UI handle these strings
if obj != obj: # standard way to check for NaN
return "NaN"
elif obj == float("+inf"):
return "Infinity"
elif obj == float("-inf"):
return "-Infinity"
return obj
def no_retry_4xx(e: Exception) -> bool:
if not isinstance(e, requests.HTTPError):
return True
assert e.response is not None
if not (400 <= e.response.status_code < 500) or e.response.status_code == 429:
return True
body = json.loads(e.response.content)
raise UsageError(body["errors"][0]["message"])
def parse_backend_error_messages(response: requests.Response) -> List[str]:
"""Returns error messages stored in a backend response.
If the response is not in an expected format, an empty list is returned.
Args:
response: A response to an HTTP request to the W&B server.
"""
try:
data = response.json()
except requests.JSONDecodeError:
return []
if not isinstance(data, dict):
return []
# Backend error values are returned in one of two ways:
# - A string containing the error message
# - A JSON object with a "message" field that is a string
def get_message(error: Any) -> Optional[str]:
if isinstance(error, str):
return error
elif (
isinstance(error, dict)
and (message := error.get("message"))
and isinstance(message, str)
):
return message
else:
return None
# The response can contain an "error" field with a single error
# or an "errors" field with a list of errors.
if error := data.get("error"):
message = get_message(error)
return [message] if message else []
elif (errors := data.get("errors")) and isinstance(errors, list):
messages: List[str] = []
for error in errors:
message = get_message(error)
if message:
messages.append(message)
return messages
else:
return []
def no_retry_auth(e: Any) -> bool:
if hasattr(e, "exception"):
e = e.exception
if not isinstance(e, requests.HTTPError):
return True
if e.response is None:
return True
# Don't retry bad request errors; raise immediately
if e.response.status_code in (400, 409):
return False
# Retry all non-forbidden/unauthorized/not-found errors.
if e.response.status_code not in (401, 403, 404):
return True
# Crash with more informational message on forbidden/unauthorized errors.
# UnauthorizedError
if e.response.status_code == 401:
raise AuthenticationError(
"The API key you provided is either invalid or missing. "
f"If the `{wandb.env.API_KEY}` environment variable is set, make sure it is correct. "
"Otherwise, to resolve this issue, you may try running the 'wandb login --relogin' command. "
"If you are using a local server, make sure that you're using the correct hostname. "
"If you're not sure, you can try logging in again using the 'wandb login --relogin --host [hostname]' command."
f"(Error {e.response.status_code}: {e.response.reason})"
)
# ForbiddenError
if e.response.status_code == 403:
if wandb.run:
raise CommError(f"Permission denied to access {wandb.run.path}")
else:
raise CommError(
"It appears that you do not have permission to access the requested resource. "
"Please reach out to the project owner to grant you access. "
"If you have the correct permissions, verify that there are no issues with your networking setup."
f"(Error {e.response.status_code}: {e.response.reason})"
)
# NotFoundError
if e.response.status_code == 404:
# If error message is empty, raise a more generic NotFoundError message.
if parse_backend_error_messages(e.response):
return False
else:
raise LookupError(
f"Failed to find resource. Please make sure you have the correct resource path. "
f"(Error {e.response.status_code}: {e.response.reason})"
)
return False
def check_retry_conflict(e: Any) -> Optional[bool]:
"""Check if the exception is a conflict type so it can be retried.
Returns:
True - Should retry this operation
False - Should not retry this operation
None - No decision, let someone else decide
"""
if hasattr(e, "exception"):
e = e.exception
if isinstance(e, requests.HTTPError) and e.response is not None:
if e.response.status_code == 409:
return True
return None
def check_retry_conflict_or_gone(e: Any) -> Optional[bool]:
"""Check if the exception is a conflict or gone type, so it can be retried or not.
Returns:
True - Should retry this operation
False - Should not retry this operation
None - No decision, let someone else decide
"""
if hasattr(e, "exception"):
e = e.exception
if isinstance(e, requests.HTTPError) and e.response is not None:
if e.response.status_code == 409:
return True
if e.response.status_code == 410:
return False
return None
def make_check_retry_fn(
fallback_retry_fn: CheckRetryFnType,
check_fn: Callable[[Exception], Optional[bool]],
check_timedelta: Optional[timedelta] = None,
) -> CheckRetryFnType:
"""Return a check_retry_fn which can be used by lib.Retry().
Args:
fallback_fn: Use this function if check_fn didn't decide if a retry should happen.
check_fn: Function which returns bool if retry should happen or None if unsure.
check_timedelta: Optional retry timeout if we check_fn matches the exception
"""
def check_retry_fn(e: Exception) -> Union[bool, timedelta]:
check = check_fn(e)
if check is None:
return fallback_retry_fn(e)
if check is False:
return False
if check_timedelta:
return check_timedelta
return True
return check_retry_fn
def find_runner(program: str) -> Union[None, list, List[str]]:
"""Return a command that will run program.
Args:
program: The string name of the program to try to run.
Returns:
commandline list of strings to run the program (eg. with subprocess.call()) or None
"""
if os.path.isfile(program) and not os.access(program, os.X_OK):
# program is a path to a non-executable file
try:
opened = open(program)
except OSError: # PermissionError doesn't exist in 2.7
return None
first_line = opened.readline().strip()
if first_line.startswith("#!"):
return shlex.split(first_line[2:])
if program.endswith(".py"):
return [sys.executable]
return None
def downsample(values: Sequence, target_length: int) -> list:
"""Downsample 1d values to target_length, including start and end.
Algorithm just rounds index down.
Values can be any sequence, including a generator.
"""
if not target_length > 1:
raise UsageError("target_length must be > 1")
values = list(values)
if len(values) < target_length:
return values
ratio = float(len(values) - 1) / (target_length - 1)
result = []
for i in range(target_length):
result.append(values[int(i * ratio)])
return result
def has_num(dictionary: Mapping, key: Any) -> bool:
return key in dictionary and isinstance(dictionary[key], numbers.Number)
def docker_image_regex(image: str) -> Any:
"""Regex match for valid docker image names."""
if image:
return re.match(
r"^(?:(?=[^:\/]{1,253})(?!-)[a-zA-Z0-9-]{1,63}(?<!-)(?:\.(?!-)[a-zA-Z0-9-]{1,63}(?<!-))*(?::[0-9]{1,5})?/)?((?![._-])(?:[a-z0-9._-]*)(?<![._-])(?:/(?![._-])[a-z0-9._-]*(?<![._-]))*)(?::(?![.-])[a-zA-Z0-9_.-]{1,128})?$",
image,
)
return None
def image_from_docker_args(args: List[str]) -> Optional[str]:
"""Scan docker run args and attempt to find the most likely docker image argument.
It excludes any arguments that start with a dash, and the argument after it if it
isn't a boolean switch. This can be improved, we currently fallback gracefully when
this fails.
"""
bool_args = [
"-t",
"--tty",
"--rm",
"--privileged",
"--oom-kill-disable",
"--no-healthcheck",
"-i",
"--interactive",
"--init",
"--help",
"--detach",
"-d",
"--sig-proxy",
"-it",
"-itd",
]
last_flag = -2
last_arg = ""
possible_images = []
if len(args) > 0 and args[0] == "run":
args.pop(0)
for i, arg in enumerate(args):
if arg.startswith("-"):
last_flag = i
last_arg = arg
elif "@sha256:" in arg:
# Because our regex doesn't match digests
possible_images.append(arg)
elif docker_image_regex(arg):
if last_flag == i - 2:
possible_images.append(arg)
elif "=" in last_arg:
possible_images.append(arg)
elif last_arg in bool_args and last_flag == i - 1:
possible_images.append(arg)
most_likely = None
for img in possible_images:
if ":" in img or "@" in img or "/" in img:
most_likely = img
break
if most_likely is None and len(possible_images) > 0:
most_likely = possible_images[0]
return most_likely
def load_yaml(file: Any) -> Any:
return yaml.safe_load(file)
def image_id_from_k8s() -> Optional[str]:
"""Ping the k8s metadata service for the image id.
Specify the KUBERNETES_NAMESPACE environment variable if your pods are not in the
default namespace:
- name: KUBERNETES_NAMESPACE valueFrom:
fieldRef:
fieldPath: metadata.namespace
"""
token_path = "/var/run/secrets/kubernetes.io/serviceaccount/token"
if not os.path.exists(token_path):
return None
try:
with open(token_path) as token_file:
token = token_file.read()
except FileNotFoundError:
logger.warning(f"Token file not found at {token_path}.")
return None
except PermissionError as e:
current_uid = os.getuid()
warning = (
f"Unable to read the token file at {token_path} due to permission error ({e})."
f"The current user id is {current_uid}. "
"Consider changing the securityContext to run the container as the current user."
)
logger.warning(warning)
wandb.termwarn(warning)
return None
if not token:
return None
k8s_server = "https://{}:{}/api/v1/namespaces/{}/pods/{}".format(
os.getenv("KUBERNETES_SERVICE_HOST"),
os.getenv("KUBERNETES_PORT_443_TCP_PORT"),
os.getenv("KUBERNETES_NAMESPACE", "default"),
os.getenv("HOSTNAME"),
)
try:
res = requests.get(
k8s_server,
verify="/var/run/secrets/kubernetes.io/serviceaccount/ca.crt",
timeout=3,
headers={"Authorization": f"Bearer {token}"},
)
res.raise_for_status()
except requests.RequestException:
return None
try:
return str( # noqa: B005
res.json()["status"]["containerStatuses"][0]["imageID"]
).strip("docker-pullable://")
except (ValueError, KeyError, IndexError):
logger.exception("Error checking kubernetes for image id")
return None
def async_call(
target: Callable, timeout: Optional[Union[int, float]] = None
) -> Callable:
"""Wrap a method to run in the background with an optional timeout.
Returns a new method that will call the original with any args, waiting for upto
timeout seconds. This new method blocks on the original and returns the result or
None if timeout was reached, along with the thread. You can check thread.is_alive()
to determine if a timeout was reached. If an exception is thrown in the thread, we
reraise it.
"""
q: queue.Queue = queue.Queue()
def wrapped_target(q: "queue.Queue", *args: Any, **kwargs: Any) -> Any:
try:
q.put(target(*args, **kwargs))
except Exception as e:
q.put(e)
def wrapper(
*args: Any, **kwargs: Any
) -> Union[Tuple[Exception, "threading.Thread"], Tuple[None, "threading.Thread"]]:
thread = threading.Thread(
target=wrapped_target, args=(q,) + args, kwargs=kwargs
)
thread.daemon = True
thread.start()
try:
result = q.get(True, timeout)
except queue.Empty:
return None, thread
if isinstance(result, Exception):
raise result.with_traceback(sys.exc_info()[2])
return result, thread
return wrapper
def read_many_from_queue(
q: "queue.Queue", max_items: int, queue_timeout: Union[int, float]
) -> list:
try:
item = q.get(True, queue_timeout)
except queue.Empty:
return []
items = [item]
for _ in range(max_items):
try:
item = q.get_nowait()
except queue.Empty:
return items
items.append(item)
return items
def stopwatch_now() -> float:
"""Get a time value for interval comparisons.
When possible it is a monotonic clock to prevent backwards time issues.
"""
return time.monotonic()
def class_colors(class_count: int) -> List[List[int]]:
# make class 0 black, and the rest equally spaced fully saturated hues
return [[0, 0, 0]] + [
colorsys.hsv_to_rgb(i / (class_count - 1.0), 1.0, 1.0) # type: ignore
for i in range(class_count - 1)
]
def _prompt_choice(
input_timeout: Union[int, float, None] = None,
jupyter: bool = False,
) -> str:
input_fn: Callable = input
prompt = term.LOG_STRING
if input_timeout is not None:
# delayed import to mitigate risk of timed_input complexity
from wandb.sdk.lib import timed_input
input_fn = functools.partial(timed_input.timed_input, timeout=input_timeout)
# timed_input doesn't handle enhanced prompts
if platform.system() == "Windows":
prompt = "wandb"
text = f"{prompt}: Enter your choice: "
if input_fn == input:
choice = input_fn(text)
else:
choice = input_fn(text, jupyter=jupyter)
return choice # type: ignore
def prompt_choices(
choices: Sequence[str],
input_timeout: Union[int, float, None] = None,
jupyter: bool = False,
) -> str:
"""Allow a user to choose from a list of options."""
for i, choice in enumerate(choices):
wandb.termlog(f"({i + 1}) {choice}")
idx = -1
while idx < 0 or idx > len(choices) - 1:
choice = _prompt_choice(input_timeout=input_timeout, jupyter=jupyter)
if not choice:
continue
idx = -1
try:
idx = int(choice) - 1
except ValueError:
pass
if idx < 0 or idx > len(choices) - 1:
wandb.termwarn("Invalid choice")
result = choices[idx]
wandb.termlog(f"You chose {result!r}")
return result
def guess_data_type(shape: Sequence[int], risky: bool = False) -> Optional[str]:
"""Infer the type of data based on the shape of the tensors.
Args:
shape (Sequence[int]): The shape of the data
risky(bool): some guesses are more likely to be wrong.
"""
# (samples,) or (samples,logits)
if len(shape) in (1, 2):
return "label"
# Assume image mask like fashion mnist: (no color channel)
# This is risky because RNNs often have 3 dim tensors: batch, time, channels
if risky and len(shape) == 3:
return "image"
if len(shape) == 4:
if shape[-1] in (1, 3, 4):
# (samples, height, width, Y \ RGB \ RGBA)
return "image"
else:
# (samples, height, width, logits)
return "segmentation_mask"
return None
def download_file_from_url(
dest_path: str, source_url: str, api_key: Optional[str] = None
) -> None:
auth = None
if not _thread_local_api_settings.cookies:
auth = ("api", api_key or "")
response = requests.get(
source_url,
auth=auth,
headers=_thread_local_api_settings.headers,
cookies=_thread_local_api_settings.cookies,
stream=True,
timeout=5,
)
response.raise_for_status()
if os.sep in dest_path:
filesystem.mkdir_exists_ok(os.path.dirname(dest_path))
with fsync_open(dest_path, "wb") as file:
for data in response.iter_content(chunk_size=1024):
file.write(data)
def download_file_into_memory(source_url: str, api_key: Optional[str] = None) -> bytes:
auth = None
if not _thread_local_api_settings.cookies:
auth = ("api", api_key or "")
response = requests.get(
source_url,
auth=auth,
headers=_thread_local_api_settings.headers,
cookies=_thread_local_api_settings.cookies,
stream=True,
timeout=5,
)
response.raise_for_status()
return response.content
def isatty(ob: IO) -> bool:
return hasattr(ob, "isatty") and ob.isatty()
def to_human_size(size: int, units: Optional[List[Tuple[str, Any]]] = None) -> str:
units = units or POW_10_BYTES
unit, value = units[0]
factor = round(float(size) / value, 1)
return (
f"{factor}{unit}"
if factor < 1024 or len(units) == 1
else to_human_size(size, units[1:])
)
def from_human_size(size: str, units: Optional[List[Tuple[str, Any]]] = None) -> int:
units = units or POW_10_BYTES
units_dict = {unit.upper(): value for (unit, value) in units}
regex = re.compile(
r"(\d+\.?\d*)\s*({})?".format("|".join(units_dict.keys())), re.IGNORECASE
)
match = re.match(regex, size)
if not match:
raise ValueError("size must be of the form `10`, `10B` or `10 B`.")
factor, unit = (
float(match.group(1)),
units_dict[match.group(2).upper()] if match.group(2) else 1,
)
return int(factor * unit)
def auto_project_name(program: Optional[str]) -> str:
# if we're in git, set project name to git repo name + relative path within repo
from wandb.sdk.lib.gitlib import GitRepo
root_dir = GitRepo().root_dir
if root_dir is None:
return "uncategorized"
# On windows, GitRepo returns paths in unix style, but os.path is windows
# style. Coerce here.
root_dir = to_native_slash_path(root_dir)
repo_name = os.path.basename(root_dir)
if program is None:
return str(repo_name)
if not os.path.isabs(program):
program = os.path.join(os.curdir, program)
prog_dir = os.path.dirname(os.path.abspath(program))
if not prog_dir.startswith(root_dir):
return str(repo_name)
project = repo_name
sub_path = os.path.relpath(prog_dir, root_dir)
if sub_path != ".":
project += "-" + sub_path
return str(project.replace(os.sep, "_"))
def are_paths_on_same_drive(path1: str, path2: str) -> bool:
"""Check if two paths are on the same drive.
This check is only relevant on Windows,
since the concept of drives only exists on Windows.
"""
if platform.system() != "Windows":
return True
try:
path1_drive = pathlib.Path(path1).resolve().drive
path2_drive = pathlib.Path(path2).resolve().drive
except OSError:
# If either path is not a valid Windows path, an OSError is raised.
return False
return path1_drive == path2_drive
# TODO(hugh): Deprecate version here and use wandb/sdk/lib/paths.py
def to_forward_slash_path(path: str) -> str:
if platform.system() == "Windows":
path = path.replace("\\", "/")
return path
# TODO(hugh): Deprecate version here and use wandb/sdk/lib/paths.py
def to_native_slash_path(path: str) -> FilePathStr:
return FilePathStr(path.replace("/", os.sep))
def check_and_warn_old(files: List[str]) -> bool:
if "wandb-metadata.json" in files:
wandb.termwarn("These runs were logged with a previous version of wandb.")
wandb.termwarn(
"Run pip install wandb<0.10.0 to get the old library and sync your runs."
)
return True
return False
class ImportMetaHook:
def __init__(self) -> None:
self.modules: Dict[str, ModuleType] = dict()
self.on_import: Dict[str, list] = dict()
def add(self, fullname: str, on_import: Callable) -> None:
self.on_import.setdefault(fullname, []).append(on_import)
def install(self) -> None:
sys.meta_path.insert(0, self) # type: ignore
def uninstall(self) -> None:
sys.meta_path.remove(self) # type: ignore
def find_module(
self, fullname: str, path: Optional[str] = None
) -> Optional["ImportMetaHook"]:
if fullname in self.on_import:
return self
return None
def load_module(self, fullname: str) -> ModuleType:
self.uninstall()
mod = importlib.import_module(fullname)
self.install()
self.modules[fullname] = mod
on_imports = self.on_import.get(fullname)
if on_imports:
for f in on_imports:
f()
return mod
def get_modules(self) -> Tuple[str, ...]:
return tuple(self.modules)
def get_module(self, module: str) -> ModuleType:
return self.modules[module]
_import_hook: Optional[ImportMetaHook] = None
def add_import_hook(fullname: str, on_import: Callable) -> None:
global _import_hook
if _import_hook is None:
_import_hook = ImportMetaHook()
_import_hook.install()
_import_hook.add(fullname, on_import)
def host_from_path(path: Optional[str]) -> str:
"""Return the host of the path."""
url = urllib.parse.urlparse(path)
return str(url.netloc)
def uri_from_path(path: Optional[str]) -> str:
"""Return the URI of the path."""
url = urllib.parse.urlparse(path)
uri = url.path if url.path[0] != "/" else url.path[1:]
return str(uri)
def is_unicode_safe(stream: TextIO) -> bool:
"""Return True if the stream supports UTF-8."""
encoding = getattr(stream, "encoding", None)
return encoding.lower() in {"utf-8", "utf_8"} if encoding else False
def _has_internet() -> bool:
"""Returns whether we have internet access.
Checks for internet access by attempting to open a DNS connection to
Google's root servers.
"""
try:
s = socket.create_connection(("8.8.8.8", 53), 0.5)
s.close()
except OSError:
return False
return True
def rand_alphanumeric(
length: int = 8, rand: Optional[Union[ModuleType, random.Random]] = None
) -> str:
wandb.termerror("rand_alphanumeric is deprecated, use 'secrets.token_hex'")
rand = rand or random
return "".join(rand.choice("0123456789ABCDEF") for _ in range(length))
@contextlib.contextmanager
def fsync_open(
path: StrPath, mode: str = "w", encoding: Optional[str] = None
) -> Generator[IO[Any], None, None]:
"""Open a path for I/O and guarantee that the file is flushed and synced."""
with open(path, mode, encoding=encoding) as f:
yield f
f.flush()
os.fsync(f.fileno())
def _is_kaggle() -> bool:
return (
os.getenv("KAGGLE_KERNEL_RUN_TYPE") is not None
or "kaggle_environments" in sys.modules
)
def _is_likely_kaggle() -> bool:
# Telemetry to mark first runs from Kagglers.
return (
_is_kaggle()
or os.path.exists(
os.path.expanduser(os.path.join("~", ".kaggle", "kaggle.json"))
)
or "kaggle" in sys.modules
)
def _is_databricks() -> bool:
# check if we are running inside a databricks notebook by
# inspecting sys.modules, searching for dbutils and verifying that
# it has the appropriate structure
if "dbutils" in sys.modules:
dbutils = sys.modules["dbutils"]
if hasattr(dbutils, "shell"):
shell = dbutils.shell
if hasattr(shell, "sc"):
sc = shell.sc
if hasattr(sc, "appName"):
return bool(sc.appName == "Databricks Shell")
return False
def _is_py_requirements_or_dockerfile(path: str) -> bool:
file = os.path.basename(path)
return (
file.endswith(".py")
or file.startswith("Dockerfile")
or file == "requirements.txt"
)
def artifact_to_json(artifact: "Artifact") -> Dict[str, Any]:
return {
"_type": "artifactVersion",
"_version": "v0",
"id": artifact.id,
"version": artifact.source_version,
"sequenceName": artifact.source_name.split(":")[0],
"usedAs": artifact.use_as,
}
def check_dict_contains_nested_artifact(d: dict, nested: bool = False) -> bool:
for item in d.values():
if isinstance(item, dict):
contains_artifacts = check_dict_contains_nested_artifact(item, True)
if contains_artifacts:
return True
elif (isinstance(item, wandb.Artifact) or _is_artifact_string(item)) and nested:
return True
return False
def load_json_yaml_dict(config: str) -> Any:
ext = os.path.splitext(config)[-1]
if ext == ".json":
with open(config) as f:
return json.load(f)
elif ext == ".yaml":
with open(config) as f:
return yaml.safe_load(f)
else:
try:
return json.loads(config)
except ValueError:
return None
def _parse_entity_project_item(path: str) -> tuple:
"""Parse paths with the following formats: {item}, {project}/{item}, & {entity}/{project}/{item}.
Args:
path: `str`, input path; must be between 0 and 3 in length.
Returns:
tuple of length 3 - (item, project, entity)
Example:
alias, project, entity = _parse_entity_project_item("myproj/mymodel:best")
assert entity == ""
assert project == "myproj"
assert alias == "mymodel:best"
"""
words = path.split("/")
if len(words) > 3:
raise ValueError(
"Invalid path: must be str the form {item}, {project}/{item}, or {entity}/{project}/{item}"
)
padded_words = [""] * (3 - len(words)) + words
return tuple(reversed(padded_words))
def _resolve_aliases(aliases: Optional[Union[str, Iterable[str]]]) -> List[str]:
"""Add the 'latest' alias and ensure that all aliases are unique.
Takes in `aliases` which can be None, str, or List[str] and returns List[str].
Ensures that "latest" is always present in the returned list.
Args:
aliases: `Optional[Union[str, List[str]]]`
Returns:
List[str], with "latest" always present.
Usage:
```python
aliases = _resolve_aliases(["best", "dev"])
assert aliases == ["best", "dev", "latest"]
aliases = _resolve_aliases("boom")
assert aliases == ["boom", "latest"]
```
"""
aliases = aliases or ["latest"]
if isinstance(aliases, str):
aliases = [aliases]
try:
return list(set(aliases) | {"latest"})
except TypeError as exc:
raise ValueError("`aliases` must be Iterable or None") from exc
def _is_artifact_object(v: Any) -> "TypeGuard[wandb.Artifact]":
return isinstance(v, wandb.Artifact)
def _is_artifact_string(v: Any) -> "TypeGuard[str]":
return isinstance(v, str) and v.startswith("wandb-artifact://")
def _is_artifact_version_weave_dict(v: Any) -> "TypeGuard[dict]":
return isinstance(v, dict) and v.get("_type") == "artifactVersion"
def _is_artifact_representation(v: Any) -> bool:
return (
_is_artifact_object(v)
or _is_artifact_string(v)
or _is_artifact_version_weave_dict(v)
)
def parse_artifact_string(v: str) -> Tuple[str, Optional[str], bool]:
if not v.startswith("wandb-artifact://"):
raise ValueError(f"Invalid artifact string: {v}")
parsed_v = v[len("wandb-artifact://") :]
base_uri = None
url_info = urllib.parse.urlparse(parsed_v)
if url_info.scheme != "":
base_uri = f"{url_info.scheme}://{url_info.netloc}"
parts = url_info.path.split("/")[1:]
else:
parts = parsed_v.split("/")
if parts[0] == "_id":
# for now can't fetch paths but this will be supported in the future
# when we allow passing typed media objects, this can be extended
# to include paths
return parts[1], base_uri, True
if len(parts) < 3:
raise ValueError(f"Invalid artifact string: {v}")
# for now can't fetch paths but this will be supported in the future
# when we allow passing typed media objects, this can be extended
# to include paths
entity, project, name_and_alias_or_version = parts[:3]
return f"{entity}/{project}/{name_and_alias_or_version}", base_uri, False
def _get_max_cli_version() -> Union[str, None]:
max_cli_version = wandb.api.max_cli_version()
return str(max_cli_version) if max_cli_version is not None else None
def ensure_text(
string: Union[str, bytes], encoding: str = "utf-8", errors: str = "strict"
) -> str:
"""Coerce s to str."""
if isinstance(string, bytes):
return string.decode(encoding, errors)
elif isinstance(string, str):
return string
else:
raise TypeError(f"not expecting type {type(string)!r}")
def make_artifact_name_safe(name: str) -> str:
"""Make an artifact name safe for use in artifacts."""
# artifact names may only contain alphanumeric characters, dashes, underscores, and dots.
cleaned = re.sub(r"[^a-zA-Z0-9_\-.]", "_", name)
if len(cleaned) <= 128:
return cleaned
# truncate with dots in the middle using regex
return re.sub(r"(^.{63}).*(.{63}$)", r"\g<1>..\g<2>", cleaned)
def make_docker_image_name_safe(name: str) -> str:
"""Make a docker image name safe for use in artifacts."""
safe_chars = RE_DOCKER_IMAGE_NAME_CHARS.sub("__", name.lower())
deduped = RE_DOCKER_IMAGE_NAME_SEPARATOR_REPEAT.sub("__", safe_chars)
trimmed_start = RE_DOCKER_IMAGE_NAME_SEPARATOR_START.sub("", deduped)
trimmed = RE_DOCKER_IMAGE_NAME_SEPARATOR_END.sub("", trimmed_start)
return trimmed if trimmed else "image"
def merge_dicts(
source: Dict[str, Any],
destination: Dict[str, Any],
) -> Dict[str, Any]:
"""Recursively merge two dictionaries.
This mutates the destination and its nested dictionaries and lists.
Instances of `dict` are recursively merged and instances of `list`
are appended to the destination. If the destination type is not
`dict` or `list`, respectively, the key is overwritten with the
source value.
For all other types, the source value overwrites the destination value.
"""
for key, value in source.items():
if isinstance(value, dict):
node = destination.get(key)
if isinstance(node, dict):
merge_dicts(value, node)
else:
destination[key] = value
elif isinstance(value, list):
dest_value = destination.get(key)
if isinstance(dest_value, list):
dest_value.extend(value)
else:
destination[key] = value
else:
destination[key] = value
return destination
def coalesce(*arg: Any) -> Any:
"""Return the first non-none value in the list of arguments.
Similar to ?? in C#.
"""
return next((a for a in arg if a is not None), None)
def recursive_cast_dictlike_to_dict(d: Dict[str, Any]) -> Dict[str, Any]:
for k, v in d.items():
if isinstance(v, dict):
recursive_cast_dictlike_to_dict(v)
elif hasattr(v, "keys"):
d[k] = dict(v)
recursive_cast_dictlike_to_dict(d[k])
return d
def remove_keys_with_none_values(
d: Union[Dict[str, Any], Any],
) -> Union[Dict[str, Any], Any]:
# otherwise iterrows will create a bunch of ugly charts
if not isinstance(d, dict):
return d
if isinstance(d, dict):
new_dict = {}
for k, v in d.items():
new_v = remove_keys_with_none_values(v)
if new_v is not None and not (isinstance(new_v, dict) and len(new_v) == 0):
new_dict[k] = new_v
return new_dict if new_dict else None
def batched(n: int, iterable: Iterable[T]) -> Generator[List[T], None, None]:
i = iter(iterable)
batch = list(itertools.islice(i, n))
while batch:
yield batch
batch = list(itertools.islice(i, n))
def random_string(length: int = 12) -> str:
"""Generate a random string of a given length.
:param length: Length of the string to generate.
:return: Random string.
"""
return "".join(
secrets.choice(string.ascii_lowercase + string.digits) for _ in range(length)
)
def sample_with_exponential_decay_weights(
xs: Union[Iterable, Iterable[Iterable]],
ys: Iterable[Iterable],
keys: Optional[Iterable] = None,
sample_size: int = 1500,
) -> Tuple[List, List, Optional[List]]:
"""Sample from a list of lists with weights that decay exponentially.
May be used with the wandb.plot.line_series function.
"""
xs_array = np.array(xs)
ys_array = np.array(ys)
keys_array = np.array(keys) if keys else None
weights = np.exp(-np.arange(len(xs_array)) / len(xs_array))
weights /= np.sum(weights)
sampled_indices = np.random.choice(len(xs_array), size=sample_size, p=weights)
sampled_xs = xs_array[sampled_indices].tolist()
sampled_ys = ys_array[sampled_indices].tolist()
sampled_keys = keys_array[sampled_indices].tolist() if keys_array else None
return sampled_xs, sampled_ys, sampled_keys
@dataclasses.dataclass(frozen=True)
class InstalledDistribution:
"""An installed distribution.
Attributes:
key: The distribution name as it would be imported.
version: The distribution's version string.
"""
key: str
version: str
def working_set() -> Iterable[InstalledDistribution]:
"""Return the working set of installed distributions."""
from importlib.metadata import distributions
for d in distributions():
try:
# In some distributions, the "Name" attribute may not be present,
# which can raise a KeyError. To handle this, we catch the exception
# and skip those distributions.
# For additional context, see: https://github.com/python/importlib_metadata/issues/371.
# From Sentry events we observed that UnicodeDecodeError can occur when
# trying to decode the metadata of a distribution. To handle this, we catch
# the exception and skip those distributions.
yield InstalledDistribution(key=d.metadata["Name"], version=d.version)
except (KeyError, UnicodeDecodeError):
pass
def get_core_path() -> str:
"""Returns the path to the wandb-core binary.
The path can be set explicitly via the _WANDB_CORE_PATH environment
variable. Otherwise, the path to the binary in the current package
is returned.
Returns:
str: The path to the wandb-core package.
Raises:
WandbCoreNotAvailableError: If wandb-core was not built for the current system.
"""
# NOTE: Environment variable _WANDB_CORE_PATH is a temporary development feature
# to assist in running the core service from a live development directory.
path_from_env: str = os.environ.get("_WANDB_CORE_PATH", "")
if path_from_env:
wandb.termwarn(
f"Using wandb-core from path `_WANDB_CORE_PATH={path_from_env}`. "
"This is a development feature and may not work as expected."
)
return path_from_env
bin_path = pathlib.Path(__file__).parent / "bin" / "wandb-core"
if not bin_path.exists():
raise WandbCoreNotAvailableError(
f"File not found: {bin_path}."
" Please contact support at support@wandb.com."
f" Your platform is: {platform.platform()}."
)
return str(bin_path)
class NonOctalStringDumper(yaml.Dumper):
"""Prevents strings containing non-octal values like "008" and "009" from being converted to numbers in in the yaml string saved as the sweep config."""
def represent_scalar(self, tag, value, style=None):
if tag == "tag:yaml.org,2002:str" and value.startswith("0") and len(value) > 1:
return super().represent_scalar(tag, value, style="'")
return super().represent_scalar(tag, value, style)