from __future__ import annotations import json import logging import os import pathlib import platform import re import shutil import socket import sys import traceback from datetime import datetime # Optional and Union are used for type hinting instead of | because # the latter is not supported in pydantic<2.6 and Python<3.10. # Dict, List, and Tuple are used for backwards compatibility # with pydantic v1 and Python<3.9. from typing import Any, Dict, List, Literal, Optional, Sequence, Tuple, Union from urllib.parse import quote, unquote from google.protobuf.wrappers_pb2 import BoolValue, DoubleValue, Int32Value, StringValue from pydantic import BaseModel, ConfigDict, Field from typing_extensions import Self import wandb from wandb import env, util from wandb._pydantic import ( IS_PYDANTIC_V2, AliasChoices, ValidationError, computed_field, field_validator, model_validator, ) from wandb.errors import UsageError from wandb.proto import wandb_settings_pb2 from wandb.sdk.lib import deprecation, settings_file, urls from .lib import credentials, filesystem, ipython from .lib.run_moment import RunMoment if not IS_PYDANTIC_V2: from pydantic import root_validator def _path_convert(*args: str) -> str: """Join path and apply os.path.expanduser to it.""" return os.path.expanduser(os.path.join(*args)) CLIENT_ONLY_SETTINGS = ( "anonymous", "app_url_override", "files_dir", "max_end_of_run_history_metrics", "max_end_of_run_summary_metrics", "reinit", "x_files_dir", "x_sync_dir_suffix", ) """Python-only keys that are not fields on the settings proto.""" class Settings(BaseModel, validate_assignment=True): """Settings for the W&B SDK. This class manages configuration settings for the W&B SDK, ensuring type safety and validation of all settings. Settings are accessible as attributes and can be initialized programmatically, through environment variables (`WANDB_ prefix`), and with configuration files. The settings are organized into three categories: 1. Public settings: Core configuration options that users can safely modify to customize W&B's behavior for their specific needs. 2. Internal settings: Settings prefixed with 'x_' that handle low-level SDK behavior. These settings are primarily for internal use and debugging. While they can be modified, they are not considered part of the public API and may change without notice in future versions. 3. Computed settings: Read-only settings that are automatically derived from other settings or the environment. """ # Pydantic Model configuration. model_config = ConfigDict( extra="forbid", # throw an error if extra fields are provided validate_default=True, # validate default values use_attribute_docstrings=True, # for field descriptions revalidate_instances="always", ) # Public settings. allow_offline_artifacts: bool = True """Flag to allow table artifacts to be synced in offline mode. To revert to the old behavior, set this to False. """ allow_val_change: bool = False """Flag to allow modification of `Config` values after they've been set.""" anonymous: deprecation.DoNotSet = Field( default=deprecation.UNSET, exclude=True, ) """Deprecated and will be removed.""" api_key: Optional[str] = None """The W&B API key.""" azure_account_url_to_access_key: Optional[Dict[str, str]] = None """Mapping of Azure account URLs to their corresponding access keys for Azure integration.""" app_url_override: Optional[str] = None """Override for the 'app' URL for the W&B UI. The `app_url` is normally computed based on `base_url`, but this can be used to set it explicitly. WANDB_APP_URL is the corresponding environment variable. """ base_url: str = "https://api.wandb.ai" """The URL of the W&B backend for data synchronization.""" code_dir: Optional[str] = None """Directory containing the code to be tracked by W&B.""" config_paths: Optional[Sequence[str]] = None """Paths to files to load configuration from into the `Config` object.""" console: Literal["auto", "off", "wrap", "redirect", "wrap_raw", "wrap_emu"] = Field( default="auto", validate_default=True, ) """The type of console capture to be applied. Possible values are: - "auto" - Automatically selects the console capture method based on the system environment and settings. - "off" - Disables console capture. - "redirect" - Redirects low-level file descriptors for capturing output. - "wrap" - Overrides the write methods of sys.stdout/sys.stderr. Will be mapped to either "wrap_raw" or "wrap_emu" based on the state of the system. - "wrap_raw" - Same as "wrap" but captures raw output directly instead of through an emulator. Derived from the `wrap` setting and should not be set manually. - "wrap_emu" - Same as "wrap" but captures output through an emulator. Derived from the `wrap` setting and should not be set manually. """ console_multipart: bool = False """Enable multipart console logging. When True, the SDK writes console output to timestamped files under the `logs/` directory instead of a single `output.log`. Each part is uploaded as soon as it is closed, giving users live access to logs while the run is active. Rollover cadence is controlled by `console_chunk_max_bytes` and/or `console_chunk_max_seconds`. If both limits are `0`, all logs are uploaded once at run finish. Note: Uploaded chunks are immutable; terminal control sequences that modify previous lines (e.g., progress bars using carriage returns) only affect the current chunk. """ console_chunk_max_bytes: int = 0 """Size-based rollover threshold for multipart console logs, in bytes. Starts a new console log file when the current part reaches this size. Has an effect only when `console_multipart` is `True`. Can be combined with `console_chunk_max_seconds`; whichever limit is hit first triggers the rollover. A value of `0` disables the size-based limit. """ console_chunk_max_seconds: int = 0 """Time-based rollover threshold for multipart console logs, in seconds. Starts a new console log file after this many seconds have elapsed since the current part began. Requires `console_multipart` to be `True`. May be used with `console_chunk_max_bytes`; the first limit reached closes the part. A value of `0` disables the time-based limit. """ credentials_file: str = Field( default_factory=lambda: str(credentials.DEFAULT_WANDB_CREDENTIALS_FILE) ) """Path to file for writing temporary access tokens.""" disable_code: bool = False """Whether to disable capturing the code.""" disable_git: bool = False """Whether to disable capturing the git state.""" disable_job_creation: bool = True """Whether to disable the creation of a job artifact for W&B Launch.""" docker: Optional[str] = None """The Docker image used to execute the script.""" email: Optional[str] = None """The email address of the user.""" entity: Optional[str] = None """The W&B entity, such as a user or a team.""" organization: Optional[str] = None """The W&B organization.""" force: bool = False """Whether to pass the `force` flag to `wandb.login()`.""" fork_from: Optional[RunMoment] = None """Specifies a point in a previous execution of a run to fork from. The point is defined by the run ID, a metric, and its value. Currently, only the metric '_step' is supported. """ git_commit: Optional[str] = None """The git commit hash to associate with the run.""" git_remote: str = "origin" """The git remote to associate with the run.""" git_remote_url: Optional[str] = None """The URL of the git remote repository.""" git_root: Optional[str] = None """Root directory of the git repository.""" heartbeat_seconds: int = 30 """Interval in seconds between heartbeat signals sent to the W&B servers. """ host: Optional[str] = None """Hostname of the machine running the script.""" http_proxy: Optional[str] = None """Custom proxy servers for http requests to W&B.""" https_proxy: Optional[str] = None """Custom proxy servers for https requests to W&B.""" identity_token_file: Optional[str] = None """Path to file containing an identity token (JWT) for authentication.""" ignore_globs: Sequence[str] = () """Unix glob patterns relative to `files_dir` specifying files to exclude from upload.""" init_timeout: float = 90.0 """Time in seconds to wait for the `wandb.init` call to complete before timing out.""" insecure_disable_ssl: bool = False """Whether to insecurely disable SSL verification.""" job_name: Optional[str] = None """Name of the Launch job running the script.""" job_source: Optional[Literal["repo", "artifact", "image"]] = None """Source type for Launch.""" label_disable: bool = False """Whether to disable automatic labeling features.""" launch: bool = False """Flag to indicate if the run is being launched through W&B Launch. """ launch_config_path: Optional[str] = None """Path to the launch configuration file.""" login_timeout: Optional[float] = None """Time in seconds to wait for login operations before timing out.""" mode: Literal["online", "offline", "shared", "disabled", "dryrun", "run"] = Field( default="online", validate_default=True, ) """The operating mode for W&B logging and synchronization.""" notebook_name: Optional[str] = None """Name of the notebook if running in a Jupyter-like environment.""" program: Optional[str] = None """Path to the script that created the run, if available.""" program_abspath: Optional[str] = None """The absolute path from the root repository directory to the script that created the run. Root repository directory is defined as the directory containing the .git directory, if it exists. Otherwise, it's the current working directory. """ program_relpath: Optional[str] = None """The relative path to the script that created the run.""" project: Optional[str] = None """The W&B project ID.""" quiet: bool = False """Flag to suppress non-essential output.""" reinit: Union[ Literal[ "default", "return_previous", "finish_previous", "create_new", ], bool, ] = "default" """What to do when `wandb.init()` is called while a run is active. Options: - "default": Use "finish_previous" in notebooks and "return_previous" otherwise. - "return_previous": Return the most recently created run that is not yet finished. This does not update `wandb.run`; see the "create_new" option. - "finish_previous": Finish all active runs, then return a new run. - "create_new": Create a new run without modifying other active runs. Does not update `wandb.run` and top-level functions like `wandb.log`. Because of this, some older integrations that rely on the global run will not work. Can also be a boolean, but this is deprecated. False is the same as "return_previous", and True is the same as "finish_previous". """ relogin: bool = False """Flag to force a new login attempt.""" resume: Optional[Literal["allow", "must", "never", "auto"]] = None """Specifies the resume behavior for the run. Options: - "must": Resumes from an existing run with the same ID. If no such run exists, it will result in failure. - "allow": Attempts to resume from an existing run with the same ID. If none is found, a new run will be created. - "never": Always starts a new run. If a run with the same ID already exists, it will result in failure. - "auto": Automatically resumes from the most recent failed run on the same machine. """ resume_from: Optional[RunMoment] = None """Specifies a point in a previous execution of a run to resume from. The point is defined by the run ID, a metric, and its value. Currently, only the metric '_step' is supported. """ resumed: bool = False """Indication from the server about the state of the run. This is different from resume, a user provided flag. """ root_dir: str = Field(default_factory=lambda: os.path.abspath(os.getcwd())) """The root directory to use as the base for all run-related paths. In particular, this is used to derive the wandb directory and the run directory. """ run_group: Optional[str] = None """Group identifier for related runs. Used for grouping runs in the UI. """ run_id: Optional[str] = None """The ID of the run.""" run_job_type: Optional[str] = None """Type of job being run (e.g., training, evaluation).""" run_name: Optional[str] = None """Human-readable name for the run.""" run_notes: Optional[str] = None """Additional notes or description for the run.""" run_tags: Optional[Tuple[str, ...]] = None """Tags to associate with the run for organization and filtering.""" sagemaker_disable: bool = False """Flag to disable SageMaker-specific functionality.""" save_code: Optional[bool] = None """Whether to save the code associated with the run.""" settings_system: Optional[str] = None """Path to the system-wide settings file.""" max_end_of_run_history_metrics: int = 10 """Maximum number of history sparklines to display at the end of a run.""" max_end_of_run_summary_metrics: int = 10 """Maximum number of summary metrics to display at the end of a run.""" show_colors: Optional[bool] = None """Whether to use colored output in the console. """ show_emoji: Optional[bool] = None """Whether to show emoji in the console output. """ show_errors: bool = True """Whether to display error messages.""" show_info: bool = True """Whether to display informational messages.""" show_warnings: bool = True """Whether to display warning messages.""" silent: bool = False """Flag to suppress all output.""" start_method: Optional[str] = None """Method to use for starting subprocesses. This is deprecated and will be removed in a future release. """ strict: Optional[bool] = None """Whether to enable strict mode for validation and error checking.""" summary_timeout: int = 60 """Time in seconds to wait for summary operations before timing out.""" summary_warnings: int = 5 """Maximum number of summary warnings to display. """ sweep_id: Optional[str] = None """Identifier of the sweep this run belongs to.""" sweep_param_path: Optional[str] = None """Path to the sweep parameters configuration.""" symlink: bool = Field( default_factory=lambda: False if platform.system() == "Windows" else True ) """Whether to use symlinks (True by default except on Windows).""" sync_tensorboard: Optional[bool] = None """Whether to synchronize TensorBoard logs with W&B.""" table_raise_on_max_row_limit_exceeded: bool = False """Whether to raise an exception when table row limits are exceeded.""" use_dot_wandb: Optional[bool] = None """Whether to use a hidden `.wandb` or visible `wandb` directory for run data. If True, the SDK uses `.wandb`. If False, `wandb`. If not set, defaults to `.wandb` if it already exists, otherwise `wandb`. """ username: Optional[str] = None """Username.""" # Internal settings. # # These are typically not meant to be set by the user and should not be considered # a part of the public API as they may change or be removed in future versions. x_cli_only_mode: bool = False """Flag to indicate that the SDK is running in CLI-only mode. """ x_disable_meta: bool = False """Flag to disable the collection of system metadata.""" x_disable_stats: bool = False """Flag to disable the collection of system metrics.""" x_disable_viewer: bool = False """Flag to disable the early viewer query. """ x_disable_machine_info: bool = False """Flag to disable automatic machine info collection. """ x_executable: Optional[str] = None """Path to the Python executable. """ x_extra_http_headers: Optional[Dict[str, str]] = None """Additional headers to add to all outgoing HTTP requests.""" x_file_stream_max_bytes: Optional[int] = None """An approximate maximum request size for the filestream API. Its purpose is to prevent HTTP requests from failing due to containing too much data. This number is approximate: requests will be slightly larger. """ x_file_stream_max_line_bytes: Optional[int] = None """Maximum line length for filestream JSONL files. """ x_file_stream_transmit_interval: Optional[float] = None """Interval in seconds between filestream transmissions. """ # Filestream retry client configuration. x_file_stream_retry_max: Optional[int] = None """Max number of retries for filestream operations. """ x_file_stream_retry_wait_min_seconds: Optional[float] = None """Minimum wait time between retries for filestream operations. """ x_file_stream_retry_wait_max_seconds: Optional[float] = None """Maximum wait time between retries for filestream operations. """ x_file_stream_timeout_seconds: Optional[float] = None """Timeout in seconds for individual filestream HTTP requests. """ # file transfer retry client configuration x_file_transfer_retry_max: Optional[int] = None """Max number of retries for file transfer operations. """ x_file_transfer_retry_wait_min_seconds: Optional[float] = None """Minimum wait time between retries for file transfer operations. """ x_file_transfer_retry_wait_max_seconds: Optional[float] = None """Maximum wait time between retries for file transfer operations. """ x_file_transfer_timeout_seconds: Optional[float] = None """Timeout in seconds for individual file transfer HTTP requests. """ x_files_dir: Optional[str] = None """Override setting for the computed files_dir. DEPRECATED, DO NOT USE. This private setting is not respected by wandb-core but will continue to work for some legacy Python code. """ x_flow_control_custom: Optional[bool] = None """Flag indicating custom flow control for filestream. TODO: Not implemented in wandb-core. """ x_flow_control_disabled: Optional[bool] = None """Flag indicating flow control is disabled for filestream. TODO: Not implemented in wandb-core. """ # graphql retry client configuration x_graphql_retry_max: Optional[int] = None """Max number of retries for GraphQL operations. """ x_graphql_retry_wait_min_seconds: Optional[float] = None """Minimum wait time between retries for GraphQL operations. """ x_graphql_retry_wait_max_seconds: Optional[float] = None """Maximum wait time between retries for GraphQL operations. """ x_graphql_timeout_seconds: Optional[float] = None """Timeout in seconds for individual GraphQL requests. """ x_internal_check_process: float = 8.0 """Interval for internal process health checks in seconds. """ x_jupyter_name: Optional[str] = None """Name of the Jupyter notebook. """ x_jupyter_path: Optional[str] = None """Path to the Jupyter notebook. """ x_jupyter_root: Optional[str] = None """Root directory of the Jupyter notebook. """ x_label: Optional[str] = None """Label to assign to system metrics and console logs collected for the run. This is used to group data by on the frontend and can be used to distinguish data from different processes in a distributed training job. """ x_live_policy_rate_limit: Optional[int] = None """Rate limit for live policy updates in seconds. """ x_live_policy_wait_time: Optional[int] = None """Wait time between live policy updates in seconds. """ x_log_level: int = logging.INFO """Logging level for internal operations. """ x_network_buffer: Optional[int] = None """Size of the network buffer used in flow control. TODO: Not implemented in wandb-core. """ x_primary: bool = Field( default=True, validation_alias=AliasChoices("x_primary", "x_primary_node") ) """Determines whether to save internal wandb files and metadata. In a distributed setting, this is useful for avoiding file overwrites from secondary processes when only system metrics and logs are needed, as the primary process handles the main logging. """ x_proxies: Optional[Dict[str, str]] = None """Custom proxy servers for requests to W&B. This is deprecated and will be removed in a future release. Please use `http_proxy` and `https_proxy` instead. """ x_runqueue_item_id: Optional[str] = None """ID of the Launch run queue item being processed. """ x_save_requirements: bool = True """Flag to save the requirements file.""" x_server_side_derived_summary: bool = False """Flag to delegate automatic computation of summary from history to the server. This does not disable user-provided summary updates. """ x_server_side_expand_glob_metrics: bool = True """Flag to delegate glob matching of metrics in define_metric to the server. If the server does not support this, the client will perform the glob matching. """ x_service_transport: Optional[str] = None """Transport method for communication with the wandb service. """ x_service_wait: float = 30.0 """Time in seconds to wait for the wandb-core internal service to start.""" x_skip_transaction_log: bool = False """Whether to skip saving the run events to the transaction log. This is only relevant for online runs. Can be used to reduce the amount of data written to disk. Should be used with caution, as it removes the gurantees about recoverability. """ x_start_time: Optional[float] = None """The start time of the run in seconds since the Unix epoch. """ x_stats_pid: int = os.getpid() """PID of the process that started the wandb-core process to collect system stats for. """ x_stats_sampling_interval: float = Field(default=15.0) """Sampling interval for the system monitor in seconds.""" x_stats_neuron_monitor_config_path: Optional[str] = None """Path to the default config file for the neuron-monitor tool. This is used to monitor AWS Trainium devices. """ x_stats_dcgm_exporter: Optional[str] = None """Endpoint to extract Nvidia DCGM metrics from. Options: - Extract DCGM-related metrics from a query to the Prometheus `/api/v1/query` endpoint. It is a common practice to aggregate metrics reported by the instances of the DCGM Exporter running on different nodes in a cluster using Prometheus. - TODO: Parse metrics directly from the `/metrics` endpoint of the DCGM Exporter. Examples: - `http://localhost:9400/api/v1/query?query=DCGM_FI_DEV_GPU_TEMP{node="l1337", cluster="globular"}`. - TODO: `http://192.168.0.1:9400/metrics`. """ x_stats_open_metrics_endpoints: Optional[Dict[str, str]] = None """OpenMetrics `/metrics` endpoints to monitor for system metrics.""" x_stats_open_metrics_filters: Union[ Dict[str, Dict[str, str]], Sequence[str], None ] = None """Filter to apply to metrics collected from OpenMetrics `/metrics` endpoints. Supports two formats: - `{"metric regex pattern, including endpoint name as prefix": {"label": "label value regex pattern"}}` - `("metric regex pattern 1", "metric regex pattern 2", ...)` """ x_stats_open_metrics_http_headers: Optional[Dict[str, str]] = None """HTTP headers to add to OpenMetrics requests.""" x_stats_disk_paths: Optional[Sequence[str]] = ("/",) """System paths to monitor for disk usage.""" x_stats_cpu_count: Optional[int] = None """System CPU count. If set, overrides the auto-detected value in the run metadata. """ x_stats_cpu_logical_count: Optional[int] = None """Logical CPU count. If set, overrides the auto-detected value in the run metadata. """ x_stats_gpu_count: Optional[int] = None """GPU device count. If set, overrides the auto-detected value in the run metadata. """ x_stats_gpu_type: Optional[str] = None """GPU device type. If set, overrides the auto-detected value in the run metadata. """ x_stats_gpu_device_ids: Optional[Sequence[int]] = None """GPU device indices to monitor. If not set, the system monitor captures metrics for all GPUs. Assumes 0-based indexing matching CUDA/ROCm device enumeration. """ x_stats_buffer_size: int = 0 """Number of system metric samples to buffer in memory in the wandb-core process. Can be accessed via run._system_metrics. """ x_stats_coreweave_metadata_base_url: str = "http://169.254.169.254" """The scheme and hostname for contacting the CoreWeave metadata server. Only accessible from within a CoreWeave cluster. """ x_stats_coreweave_metadata_endpoint: str = "/api/v2/cloud-init/meta-data" """The relative path on the CoreWeave metadata server to which to make requests. This must not include the schema and hostname prefix. Only accessible from within a CoreWeave cluster. """ x_stats_track_process_tree: bool = False """Monitor the entire process tree for resource usage, starting from `x_stats_pid`. When `True`, the system monitor aggregates the RSS, CPU%, and thread count from the process with PID `x_stats_pid` and all of its descendants. This can have a performance overhead and is disabled by default. """ x_sync: bool = False """Flag to indicate whether we are syncing a run from the transaction log. """ x_sync_dir_suffix: str = "" """Suffix to add to the run's directory name (sync_dir). This is set in wandb.init() to avoid naming conflicts. If set, it is joined to the default name with a dash. """ x_update_finish_state: bool = True """Flag to indicate whether this process can update the run's final state on the server. Set to False in distributed training when only the main process should determine the final state. """ # Model validator to catch legacy settings. @model_validator(mode="before") @classmethod def catch_private_settings(cls, values): """Check if a private field is provided and assign to the corresponding public one. This is a compatibility layer to handle previous versions of the settings. """ new_values = {} for key in values: # Internal settings are prefixed with "x_" instead of "_" # as Pydantic does not allow "_" in field names. if key.startswith("_"): new_values["x" + key] = values[key] else: new_values[key] = values[key] return new_values if IS_PYDANTIC_V2: @model_validator(mode="after") def validate_mutual_exclusion_of_branching_args(self) -> Self: """Check if `fork_from`, `resume`, and `resume_from` are mutually exclusive. """ if ( sum( o is not None for o in [self.fork_from, self.resume, self.resume_from] ) > 1 ): raise ValueError( "`fork_from`, `resume`, or `resume_from` are mutually exclusive. " "Please specify only one of them." ) return self @model_validator(mode="after") def validate_skip_transaction_log(self): """Validate x_skip_transaction_log. """ if self._offline and self.x_skip_transaction_log: raise ValueError("Cannot skip transaction log in offline mode") return self else: @root_validator(pre=False) # type: ignore [call-overload] @classmethod def validate_mutual_exclusion_of_branching_args(cls, values): if ( sum( values.get(o) is not None for o in ["fork_from", "resume", "resume_from"] ) > 1 ): raise ValueError( "`fork_from`, `resume`, or `resume_from` are mutually exclusive. " "Please specify only one of them." ) return values @root_validator(pre=False) # type: ignore [call-overload] @classmethod def validate_skip_transaction_log(cls, values): if values.get("_offline") and values.get("x_skip_transaction_log"): raise ValueError("Cannot skip transaction log in offline mode") return values # Field validators. @field_validator("anonymous", mode="after") @classmethod def validate_anonymous(cls, value: object) -> object: if value is not deprecation.UNSET: wandb.termwarn( "The anonymous setting has no effect and will be removed" + " in a future version.", repeat=False, ) return value @field_validator("api_key", mode="after") @classmethod def validate_api_key(cls, value): """Validate the API key. """ if value is not None and (len(value) > len(value.strip())): raise UsageError("API key cannot start or end with whitespace") return value @field_validator("base_url", mode="after") @classmethod def validate_base_url(cls, value): """Validate the base URL. """ urls.validate_url(value) # wandb.ai-specific checks if re.match(r".*wandb\.ai[^\.]*$", value) and "api." not in value: # user might guess app.wandb.ai or wandb.ai is the default cloud server raise ValueError( f"{value} is not a valid server address, did you mean https://api.wandb.ai?" ) elif re.match(r".*wandb\.ai[^\.]*$", value) and not value.startswith("https"): raise ValueError("http is not secure, please use https://api.wandb.ai") return value.rstrip("/") @field_validator("code_dir", mode="before") @classmethod def validate_code_dir(cls, value): """Validate the code directory. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value @field_validator("console", mode="after") @classmethod def validate_console(cls, value, values): """Validate the console capture method. """ if value != "auto": return value return "wrap" @field_validator("console_chunk_max_bytes", mode="after") @classmethod def validate_console_chunk_max_bytes(cls, value): """Validate the console_chunk_max_bytes value. """ if value < 0: raise ValueError("console_chunk_max_bytes must be non-negative") return value @field_validator("console_chunk_max_seconds", mode="after") @classmethod def validate_console_chunk_max_seconds(cls, value): """Validate the console_chunk_max_seconds value. """ if value < 0: raise ValueError("console_chunk_max_seconds must be non-negative") return value @field_validator("x_executable", mode="before") @classmethod def validate_x_executable(cls, value): """Validate the Python executable path. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value @field_validator("x_extra_http_headers", mode="before") @classmethod def validate_x_extra_http_headers(cls, value): if isinstance(value, str): return json.loads(value) return value @field_validator("x_file_stream_max_line_bytes", mode="after") @classmethod def validate_file_stream_max_line_bytes(cls, value): """Validate the maximum line length for filestream JSONL files. """ if value is not None and value < 1: raise ValueError("File stream max line bytes must be greater than 0") return value @field_validator("x_files_dir", mode="before") @classmethod def validate_x_files_dir(cls, value): """Validate the files directory. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value @field_validator("fork_from", mode="before") @classmethod def validate_fork_from(cls, value, values) -> Optional[RunMoment]: """Validate the fork_from field. """ run_moment = cls._runmoment_preprocessor(value) if hasattr(values, "data"): # pydantic v2 values = values.data else: # pydantic v1 values = values if ( run_moment and values.get("run_id") is not None and values.get("run_id") == run_moment.run ): raise ValueError( "Provided `run_id` is the same as the run to `fork_from`. " "Please provide a different `run_id` or remove the `run_id` argument. " "If you want to rewind the current run, please use `resume_from` instead." ) return run_moment @field_validator("http_proxy", mode="after") @classmethod def validate_http_proxy(cls, value): """Validate the HTTP proxy. """ if value is None: return None urls.validate_url(value) return value.rstrip("/") @field_validator("https_proxy", mode="after") @classmethod def validate_https_proxy(cls, value): """Validate the HTTPS proxy. """ if value is None: return None urls.validate_url(value) return value.rstrip("/") @field_validator("ignore_globs", mode="after") @classmethod def validate_ignore_globs(cls, value): """Validate the ignore globs. """ return tuple(value) if not isinstance(value, tuple) else value @field_validator("program", mode="before") @classmethod def validate_program(cls, value): """Validate the program path. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value @field_validator("program_abspath", mode="before") @classmethod def validate_program_abspath(cls, value): """Validate the absolute program path. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value @field_validator("program_relpath", mode="before") @classmethod def validate_program_relpath(cls, value): """Validate the relative program path. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value @field_validator("project", mode="after") @classmethod def validate_project(cls, value, values): """Validate the project name. """ if value is None: return None invalid_chars_list = list("/\\#?%:") if len(value) > 128: raise UsageError(f"Invalid project name {value!r}: exceeded 128 characters") invalid_chars = {char for char in invalid_chars_list if char in value} if invalid_chars: raise UsageError( f"Invalid project name {value!r}: " f"cannot contain characters {','.join(invalid_chars_list)!r}, " f"found {','.join(invalid_chars)!r}" ) return value @field_validator("resume", mode="before") @classmethod def validate_resume(cls, value): """Validate the resume behavior. """ if value is False: return None if value is True: return "auto" return value @field_validator("resume_from", mode="before") @classmethod def validate_resume_from(cls, value, values) -> Optional[RunMoment]: """Validate the resume_from field. """ run_moment = cls._runmoment_preprocessor(value) if hasattr(values, "data"): # pydantic v2 values = values.data else: # pydantic v1 values = values if ( run_moment and values.get("run_id") is not None and values.get("run_id") != run_moment.run ): raise ValueError( "Both `run_id` and `resume_from` have been specified with different ids." ) return run_moment @field_validator("root_dir", mode="before") @classmethod def validate_root_dir(cls, value): """Validate the root directory. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value @field_validator("run_id", mode="after") @classmethod def validate_run_id(cls, value, values): """Validate the run ID. """ if value is None: return None if len(value) == 0: raise UsageError("Run ID cannot be empty") if len(value) > len(value.strip()): raise UsageError("Run ID cannot start or end with whitespace") if not bool(value.strip()): raise UsageError("Run ID cannot contain only whitespace") # check if the run id contains any reserved characters reserved_chars = ":;,#?/'" if any(char in reserved_chars for char in value): raise UsageError(f"Run ID cannot contain the characters: {reserved_chars}") return value @field_validator("settings_system", mode="after") @classmethod def validate_settings_system(cls, value): """Validate the system settings file path. """ if value is None: return None elif isinstance(value, pathlib.Path): return str(_path_convert(value)) else: return _path_convert(value) @field_validator("x_service_wait", mode="after") @classmethod def validate_service_wait(cls, value): """Validate the service wait time. """ if value < 0: raise UsageError("Service wait time cannot be negative") return value @field_validator("start_method", mode="after") @classmethod def validate_start_method(cls, value): """Validate the start method for subprocesses. """ if value is None: return value wandb.termwarn( "`start_method` is deprecated and will be removed in a future version " "of wandb. This setting is currently non-functional and safely ignored.", repeat=False, ) return value @field_validator("x_stats_coreweave_metadata_base_url", mode="after") @classmethod def validate_x_stats_coreweave_metadata_base_url(cls, value): urls.validate_url(value) return value.rstrip("/") @field_validator("x_stats_gpu_device_ids", mode="before") @classmethod def validate_x_stats_gpu_device_ids(cls, value): """Validate the GPU device IDs. """ if isinstance(value, str): return json.loads(value) return value @field_validator("x_stats_neuron_monitor_config_path", mode="before") @classmethod def validate_x_stats_neuron_monitor_config_path(cls, value): """Validate the path to the neuron-monitor config file. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value @field_validator("x_stats_open_metrics_endpoints", mode="before") @classmethod def validate_stats_open_metrics_endpoints(cls, value): """Validate the OpenMetrics endpoints. """ if isinstance(value, str): return json.loads(value) return value @field_validator("x_stats_open_metrics_filters", mode="before") @classmethod def validate_stats_open_metrics_filters(cls, value): """Validate the OpenMetrics filters. """ if isinstance(value, str): return json.loads(value) return value @field_validator("x_stats_open_metrics_http_headers", mode="before") @classmethod def validate_stats_open_metrics_http_headers(cls, value): """Validate the OpenMetrics HTTP headers. """ if isinstance(value, str): return json.loads(value) return value @field_validator("x_stats_sampling_interval", mode="after") @classmethod def validate_stats_sampling_interval(cls, value): """Validate the stats sampling interval. """ if value < 0.1: raise UsageError("Stats sampling interval cannot be less than 0.1 seconds") return value @field_validator("sweep_id", mode="after") @classmethod def validate_sweep_id(cls, value): """Validate the sweep ID. """ if value is None: return None if len(value) == 0: raise UsageError("Sweep ID cannot be empty") if len(value) > len(value.strip()): raise UsageError("Sweep ID cannot start or end with whitespace") if not bool(value.strip()): raise UsageError("Sweep ID cannot contain only whitespace") return value @field_validator("run_tags", mode="before") @classmethod def validate_run_tags(cls, value): """Validate run tags. Validates that each tag: - Is between 1 and 64 characters in length (inclusive) - Converts single string values to tuple format - Preserves None values Args: value: A string, list, tuple, or None representing tags Returns: tuple: A tuple of validated tags, or None Raises: ValueError: If any tag is empty or exceeds 64 characters """ if value is None: return None # Convert to tuple if needed if isinstance(value, str): tags = (value,) else: tags = tuple(value) # Validate each tag and accumulate errors errors = [] for i, tag in enumerate(tags): tag_str = str(tag) if len(tag_str) == 0: errors.append( f"Tag at index {i} is empty. Tags must be between 1 and 64 characters" ) elif len(tag_str) > 64: # Truncate long tags for display display_tag = ( f"{tag_str[:20]}...{tag_str[-20:]}" if len(tag_str) > 43 else tag_str ) errors.append( f"Tag '{display_tag}' is {len(tag_str)} characters. Tags must be between 1 and 64 characters" ) # Raise combined error if any validation issues were found if errors: raise ValueError("; ".join(errors)) return tags @field_validator("sweep_param_path", mode="before") @classmethod def validate_sweep_param_path(cls, value): """Validate the sweep parameter path. """ # TODO: add native support for pathlib.Path if isinstance(value, pathlib.Path): return str(value) return value # Computed fields. @computed_field # type: ignore[prop-decorator] @property def _args(self) -> List[str]: if not self._jupyter: return sys.argv[1:] return [] @computed_field # type: ignore[prop-decorator] @property def _aws_lambda(self) -> bool: """Check if we are running in a lambda environment.""" from sentry_sdk.integrations.aws_lambda import ( # type: ignore[import-not-found] get_lambda_bootstrap, ) lambda_bootstrap = get_lambda_bootstrap() if not lambda_bootstrap or not hasattr( lambda_bootstrap, "handle_event_request" ): return False return True @computed_field # type: ignore[prop-decorator] @property def _code_path_local(self) -> Optional[str]: """The relative path from the current working directory to the code path. For example, if the code path is /home/user/project/example.py, and the current working directory is /home/user/project, then the code path local is example.py. If couldn't find the relative path, this will be an empty string. """ return self._get_program_relpath(self.program) if self.program else None @computed_field # type: ignore[prop-decorator] @property def _colab(self) -> bool: return "google.colab" in sys.modules @computed_field # type: ignore[prop-decorator] @property def _ipython(self) -> bool: return ipython.in_ipython() @computed_field # type: ignore[prop-decorator] @property def _jupyter(self) -> bool: return ipython.in_jupyter() @computed_field # type: ignore[prop-decorator] @property def _kaggle(self) -> bool: return util._is_likely_kaggle() @computed_field # type: ignore[prop-decorator] @property def _noop(self) -> bool: return self.mode == "disabled" @computed_field # type: ignore[prop-decorator] @property def _notebook(self) -> bool: return self._ipython or self._jupyter or self._colab or self._kaggle @computed_field # type: ignore[prop-decorator] @property def _offline(self) -> bool: return self.mode in ("offline", "dryrun") @computed_field # type: ignore[prop-decorator] @property def _os(self) -> str: """The operating system of the machine running the script.""" return platform.platform(aliased=True) @computed_field # type: ignore[prop-decorator] @property def _platform(self) -> str: return f"{platform.system()}-{platform.machine()}".lower() @computed_field # type: ignore[prop-decorator] @property def _python(self) -> str: return f"{platform.python_implementation()} {platform.python_version()}" @computed_field # type: ignore[prop-decorator] @property def _shared(self) -> bool: """Whether we are in shared mode. In "shared" mode, multiple processes can write to the same run, for example from different machines. """ return self.mode == "shared" @computed_field # type: ignore[prop-decorator] @property def _start_datetime(self) -> str: if self.x_start_time is None: return "" datetime_now = datetime.fromtimestamp(self.x_start_time) return datetime_now.strftime("%Y%m%d_%H%M%S") @computed_field # type: ignore[prop-decorator] @property def _tmp_code_dir(self) -> str: return _path_convert(self.sync_dir, "tmp", "code") @computed_field # type: ignore[prop-decorator] @property def _windows(self) -> bool: return platform.system() == "Windows" @computed_field # type: ignore[prop-decorator] @property def app_url(self) -> str: """The URL for the W&B UI, usually https://wandb.ai. This is different from `base_url` (like https://api.wandb.ai) which is used to access W&B APIs programmatically. """ return self.app_url_override or util.api_to_app_url(self.base_url) @computed_field # type: ignore[prop-decorator] @property def colab_url(self) -> Optional[str]: """The URL to the Colab notebook, if running in Colab.""" if not self._colab: return None if self.x_jupyter_path and self.x_jupyter_path.startswith("fileId="): unescaped = unquote(self.x_jupyter_path) return "https://colab.research.google.com/notebook#" + unescaped return None @computed_field # type: ignore[prop-decorator] @property def deployment(self) -> Literal["local", "cloud"]: return "local" if self.is_local else "cloud" @computed_field # type: ignore[prop-decorator] @property def files_dir(self) -> str: """Absolute path to the local directory where the run's files are stored.""" # Must match the logic in settings.go in the service process. return self.x_files_dir or _path_convert(self.sync_dir, "files") @computed_field # type: ignore[prop-decorator] @property def is_local(self) -> bool: return str(self.base_url) != "https://api.wandb.ai" @computed_field # type: ignore[prop-decorator] @property def log_dir(self) -> str: """The directory for storing log files.""" return _path_convert(self.sync_dir, "logs") @computed_field # type: ignore[prop-decorator] @property def log_internal(self) -> str: """The path to the file to use for internal logs.""" return _path_convert(self.log_dir, "debug-internal.log") @computed_field # type: ignore[prop-decorator] @property def log_symlink_internal(self) -> str: """The path to the symlink to the internal log file of the most recent run.""" return _path_convert(self.wandb_dir, "debug-internal.log") @computed_field # type: ignore[prop-decorator] @property def log_symlink_user(self) -> str: """The path to the symlink to the user-process log file of the most recent run.""" return _path_convert(self.wandb_dir, "debug.log") @computed_field # type: ignore[prop-decorator] @property def log_user(self) -> str: """The path to the file to use for user-process logs.""" return _path_convert(self.log_dir, "debug.log") @computed_field # type: ignore[prop-decorator] @property def project_url(self) -> str: """The W&B URL where the project can be viewed.""" project_url = self._project_url_base() if not project_url: return "" return project_url @computed_field # type: ignore[prop-decorator] @property def resume_fname(self) -> str: """The path to the resume file.""" return _path_convert(self.wandb_dir, "wandb-resume.json") @computed_field # type: ignore[prop-decorator] @property def run_mode(self) -> Literal["run", "offline-run"]: """The mode of the run. Can be either "run" or "offline-run".""" return "run" if not self._offline else "offline-run" @computed_field # type: ignore[prop-decorator] @property def run_url(self) -> str: """The W&B URL where the run can be viewed.""" project_url = self._project_url_base() if not all([project_url, self.run_id]): return "" # Exclude specific safe characters from URL encoding to prevent 404 errors safe_chars = "=+&$@" return f"{project_url}/runs/{quote(self.run_id or '', safe=safe_chars)}" @computed_field # type: ignore[prop-decorator] @property def settings_workspace(self) -> str: """The path to the workspace settings file.""" return _path_convert(self.wandb_dir, "settings") @computed_field # type: ignore[prop-decorator] @property def sweep_url(self) -> str: """The W&B URL where the sweep can be viewed.""" project_url = self._project_url_base() if not all([project_url, self.sweep_id]): return "" return f"{project_url}/sweeps/{quote(self.sweep_id or '')}" @computed_field # type: ignore[prop-decorator] @property def sync_dir(self) -> str: """The directory for storing the run's files.""" name = f"{self.run_mode}-{self.timespec}-{self.run_id}" if self.x_sync_dir_suffix: name += f"-{self.x_sync_dir_suffix}" return _path_convert(self.wandb_dir, name) @computed_field # type: ignore[prop-decorator] @property def sync_file(self) -> str: """Path to the append-only binary transaction log file.""" return _path_convert(self.sync_dir, f"run-{self.run_id}.wandb") @computed_field # type: ignore[prop-decorator] @property def sync_symlink_latest(self) -> str: """Path to the symlink to the most recent run's transaction log file.""" return _path_convert(self.wandb_dir, "latest-run") @computed_field # type: ignore[prop-decorator] @property def timespec(self) -> str: """The time specification for the run.""" return self._start_datetime @computed_field # type: ignore[prop-decorator] @property def wandb_dir(self) -> str: """Full path to the wandb directory.""" if self.use_dot_wandb is None: use_dot = pathlib.Path(self.root_dir, ".wandb").exists() else: use_dot = self.use_dot_wandb dirname = ".wandb" if use_dot else "wandb" return str(pathlib.Path(self.root_dir, dirname).expanduser()) # Methods to collect and update settings from different sources. # # The Settings class does not track the source of the settings, # so it is up to the developer to ensure that the settings are applied # in the correct order. Most of the updates are done in # wandb/sdk/wandb_setup.py::_WandbSetup._settings_setup. def read_system_settings(self) -> settings_file.SettingsFiles: """Read settings from the workspace and global settings files. The files are determined by the settings_system and settings_workspace settings. The resulting object is a snapshot of the system settings at the time this function is used and does not reflect the settings on this Settings object. It can be used to update the files, and it should be short-lived since it does not reflect external changes to the files. Updating the settings files does not update this Settings instance and vice versa. """ local_settings = pathlib.Path(self.settings_workspace) if self.settings_system: global_settings = pathlib.Path(self.settings_system) else: global_settings = None return settings_file.SettingsFiles( global_settings=global_settings, local_settings=local_settings, ) def update_from_system_settings(self) -> None: """Load settings from the settings files. If settings files contain invalid settings, prints and suppresses the error. """ system_settings = self.read_system_settings() if len(system_settings.sources) == 0: return elif len(system_settings.sources) == 1: source_string = str(system_settings.sources[0]) else: source_string = "\n" + "\n".join( f" {source}" for source in system_settings.sources ) # Print at the start so that users can diagnose uncaught exceptions. if not self.quiet: printed_sources = True wandb.termlog(f"Loading settings from {source_string}") else: printed_sources = False try: parsed_settings = _parse_system_settings(system_settings) except Exception as e: if not printed_sources: wandb.termerror(f"Failed to load settings from {source_string}") if isinstance(e, ValidationError): # Pydantic ValidationErrors have detailed messages that we can # print without a stack trace. wandb.termerror(str(e)) else: # For all other errors, we need to dump a stack trace to make # sure they're debuggable. tb = traceback.format_exception(type(e), e, e.__traceback__) wandb.termerror("".join(tb)) return # We parse and set in different steps so that we do not partially # apply a broken settings file. # # Note that this runs validation functions a second time, but we expect # them to succeed. self.update_from_settings(parsed_settings) def update_from_env_vars(self, environ: Dict[str, Any]): """Update settings from environment variables. """ env_prefix: str = "WANDB_" private_env_prefix: str = env_prefix + "_" special_env_var_names = { env.APP_URL: "app_url_override", "WANDB_SERVICE_TRANSPORT": "x_service_transport", env.DIR: "root_dir", env.NAME: "run_name", env.NOTES: "run_notes", env.TAGS: "run_tags", env.JOB_TYPE: "run_job_type", env.HTTP_TIMEOUT: "x_graphql_timeout_seconds", env.FILE_PUSHER_TIMEOUT: "x_file_transfer_timeout_seconds", env.USER_EMAIL: "email", } for setting, value in environ.items(): if not setting.startswith(env_prefix): continue if setting in special_env_var_names: key = special_env_var_names[setting] elif setting.startswith(private_env_prefix): key = "x_" + setting[len(private_env_prefix) :].lower() else: # otherwise, strip the prefix and convert to lowercase key = setting[len(env_prefix) :].lower() if key not in self.__dict__: continue if key in ("ignore_globs", "run_tags"): value = value.split(",") if value is None: continue setattr(self, key, value) def update_from_system_environment(self): """Update settings from the system environment. """ # For code saving, only allow env var override if value from server is true, or # if no preference was specified. if (self.save_code is True or self.save_code is None) and ( os.getenv(env.SAVE_CODE) is not None or os.getenv(env.DISABLE_CODE) is not None ): self.save_code = env.should_save_code() if os.getenv(env.DISABLE_GIT) is not None: self.disable_git = env.disable_git() # Attempt to get notebook information if not already set by the user if self._jupyter and (self.notebook_name is None or self.notebook_name == ""): meta = wandb.jupyter.notebook_metadata(self.silent) # type: ignore self.x_jupyter_path = meta.get("path") self.x_jupyter_name = meta.get("name") self.x_jupyter_root = meta.get("root") elif ( self._jupyter and self.notebook_name is not None and os.path.exists(self.notebook_name) ): self.x_jupyter_path = self.notebook_name self.x_jupyter_name = self.notebook_name self.x_jupyter_root = os.getcwd() elif self._jupyter: wandb.termwarn( "WANDB_NOTEBOOK_NAME should be a path to a notebook file, " f"couldn't find {self.notebook_name}.", ) # host is populated by update_from_env_vars if the corresponding env # vars exist -- but if they don't, we'll fill them in here. if self.host is None: self.host = socket.gethostname() # type: ignore _executable = ( self.x_executable or os.environ.get(env._EXECUTABLE) or sys.executable or shutil.which("python3") or "python3" ) self.x_executable = _executable if self.docker is None: self.docker = env.get_docker(util.image_id_from_k8s()) # proceed if not in CLI mode if self.x_cli_only_mode: return program = self.program or self._get_program() if program is not None: self._setup_code_paths(program) else: program = "" self.program = program def update_from_dict(self, settings: Dict[str, Any]) -> None: """Update settings from a dictionary. """ for key, value in dict(settings).items(): if value is not None: setattr(self, key, value) def update_from_settings(self, settings: Settings) -> None: """Update settings from another instance of `Settings`. """ d = {field: getattr(settings, field) for field in settings.model_fields_set} if d: self.update_from_dict(d) # Helper methods. def to_proto(self) -> wandb_settings_pb2.Settings: """Generate a protobuf representation of the settings. """ settings_proto = wandb_settings_pb2.Settings() for k, v in self.model_dump(exclude_none=True).items(): if k in CLIENT_ONLY_SETTINGS: continue # Special case for x_stats_open_metrics_filters. if k == "x_stats_open_metrics_filters": if isinstance(v, (list, set, tuple)): setting = getattr(settings_proto, k) setting.sequence.value.extend(v) elif isinstance(v, dict): setting = getattr(settings_proto, k) for key, value in v.items(): for kk, vv in value.items(): setting.mapping.value[key].value[kk] = vv else: raise TypeError(f"Unsupported type {type(v)} for setting {k}") continue # Special case for RunMoment fields. if k in ("fork_from", "resume_from"): run_moment = ( v if isinstance(v, RunMoment) else RunMoment( run=v.get("run"), value=v.get("value"), metric=v.get("metric"), ) ) getattr(settings_proto, k).CopyFrom( wandb_settings_pb2.RunMoment( run=run_moment.run, value=run_moment.value, metric=run_moment.metric, ) ) continue if isinstance(v, bool): getattr(settings_proto, k).CopyFrom(BoolValue(value=v)) elif isinstance(v, int): getattr(settings_proto, k).CopyFrom(Int32Value(value=v)) elif isinstance(v, float): getattr(settings_proto, k).CopyFrom(DoubleValue(value=v)) elif isinstance(v, str): getattr(settings_proto, k).CopyFrom(StringValue(value=v)) elif isinstance(v, (list, set, tuple)): # we only support sequences of strings for now sequence = getattr(settings_proto, k) sequence.value.extend(v) elif isinstance(v, dict): mapping = getattr(settings_proto, k) for key, value in v.items(): # we only support dicts with string values for now mapping.value[key] = value elif v is None: # None means that the setting value was not set. pass else: raise TypeError(f"Unsupported type {type(v)} for setting {k}") return settings_proto def _get_program(self) -> Optional[str]: """Get the program that started the current process.""" if self._jupyter: # If in a notebook, try to get the program from the notebook metadata. if self.notebook_name: return self.notebook_name if not self.x_jupyter_path: return self.program if self.x_jupyter_path.startswith("fileId="): return self.x_jupyter_name return self.x_jupyter_path # If not in a notebook, try to get the program from the environment # or the __main__ module for scripts run as `python -m ...`. program = os.getenv(env.PROGRAM) if program is not None: return program try: import __main__ except ImportError: return None try: if __main__.__spec__ is None: python_args = __main__.__file__ else: python_args = f"-m {__main__.__spec__.name}" except AttributeError: return None return python_args @staticmethod def _get_program_relpath(program: str, root: Optional[str] = None) -> Optional[str]: """Get the relative path to the program from the root directory.""" if not program: return None root = root or os.getcwd() if not root: return None # For windows, if the root and program are on different drives, # os.path.relpath will raise a ValueError. if not filesystem.are_paths_on_same_drive( pathlib.Path(root), pathlib.Path(program) ): return None full_path_to_program = os.path.join( root, os.path.relpath(os.getcwd(), root), program ) if os.path.exists(full_path_to_program): relative_path = os.path.relpath(full_path_to_program, start=root) if "../" in relative_path: return None return relative_path return None def _project_url_base(self) -> str: """Construct the base URL for the project.""" if not all([self.entity, self.project]): return "" return f"{self.app_url}/{quote(self.entity or '')}/{quote(self.project or '')}" @staticmethod def _runmoment_preprocessor( val: Union[RunMoment, str, None], ) -> Optional[RunMoment]: """Preprocess the setting for forking or resuming a run.""" if isinstance(val, RunMoment) or val is None: return val elif isinstance(val, str): return RunMoment.from_uri(val) if not IS_PYDANTIC_V2: def model_copy(self, *args, **kwargs): return self.copy(*args, **kwargs) def model_dump(self, **kwargs): """Compatibility method for Pydantic v1 to mimic v2's model_dump. In v1, this is equivalent to dict() but also includes computed properties. Args: **kwargs: Options passed to the dict method - exclude_none: Whether to exclude fields with None values Returns: A dictionary of the model's fields and computed properties """ # Handle exclude_none separately since it's named differently in v1 exclude_none = kwargs.pop("exclude_none", False) # Start with regular fields from dict() result = self.dict(**kwargs) # Get all computed properties for name in dir(self.__class__): attr = getattr(self.__class__, name, None) if isinstance(attr, property): try: # Only include properties that don't raise errors value = getattr(self, name) result[name] = value except (AttributeError, NotImplementedError, TypeError, ValueError): # Skip properties that can't be accessed or raise errors pass elif isinstance(attr, RunMoment): value = getattr(self, name) result[name] = value # Special Pydantic attributes that should always be excluded exclude_fields = { "model_config", "model_fields", "model_fields_set", "__fields__", "__model_fields_set", "__pydantic_self__", "__pydantic_initialised__", } # Remove special Pydantic attributes for field in exclude_fields: if field in result: del result[field] if exclude_none: # Remove None values from the result return {k: v for k, v in result.items() if v is not None} return result @property def model_fields_set(self) -> set: """Return a set of fields that have been explicitly set. This is a compatibility property for Pydantic v1 to mimic v2's model_fields_set. """ return getattr(self, "__fields_set__", set()) def _setup_code_paths(self, program: str): """Sets the program_abspath and program_relpath settings.""" if self._jupyter and self.x_jupyter_root: self._infer_code_paths_for_jupyter(program) else: self._infer_code_path_for_program(program) def _infer_code_path_for_program(self, program: str): """Finds the program's absolute and relative paths.""" from .lib.gitlib import GitRepo try: root = ( GitRepo().root or os.getcwd() if not self.disable_git else os.getcwd() ) except Exception: # if the git command fails, fall back to the current working directory root = os.getcwd() self.program_relpath = self.program_relpath or self._get_program_relpath( program, root ) program_abspath = os.path.abspath( os.path.join(root, os.path.relpath(os.getcwd(), root), program) ) if os.path.exists(program_abspath): self.program_abspath = program_abspath def _infer_code_paths_for_jupyter(self, program: str): """Find the notebook's absolute and relative paths. Since the notebook's execution environment is not the same as the current working directory. We utilize the metadata provided by the jupyter server. """ if not self.x_jupyter_root or not program: return None self.program_abspath = os.path.abspath( os.path.join(self.x_jupyter_root, program) ) self.program_relpath = program def _parse_system_settings( system_settings: settings_file.SettingsFiles, ) -> Settings: """Validate settings from a settings file. Returns: A validated Settings object. Raises: ValidationError: on invalid data. Exception: arbitrary errors can occur when constructing Settings. """ fields: dict[str, Any] = dict() value: object # Can be transformed arbitrarily. for key, value in system_settings.all().items(): if key == "ignore_globs": fields[key] = value.split(",") elif key == "anonymous": wandb.termwarn( "Deprecated setting 'anonymous' has no effect and will be" + " removed in a future version of wandb." + " Please delete it manually or by running `wandb login`" + " to avoid errors.", repeat=False, ) fields[key] = deprecation.UNSET elif key in ("settings_system", "root_dir"): wandb.termwarn( f"Ignoring setting {key!r} which is not allowed in a settings file." + " Please delete it manually to avoid errors in the future." ) else: fields[key] = value # NOTE: Field validators must raise ValueError for Pydantic to wrap them # in a ValidationError. Other kinds of errors will bubble up unaltered. # # Unfortunately, some validators return a UsageError, which has special # handling in the CLI and may require care to change. return Settings(**fields)