spacy-loggers: Logging utilities for spaCy

Starting with spaCy v3.2, alternate loggers are moved into a separate package so that they can be added and updated independently from the core spaCy library.

spacy-loggers currently provides loggers for:

• Weights & Biases

If you'd like to add a new logger or logging option, please submit a PR to this repo!

Setup and installation

spacy-loggers should be installed automatically with spaCy v3.2+, so you usually don't need to install it separately. You can install it with pip or from the conda channel conda-forge:

pip install spacy-loggers

conda install -c conda-forge spacy-loggers

Loggers

WandbLogger

Installation

This logger requires wandb to be installed and configured:

pip install wandb
wandb login

Usage

spacy.WandbLogger.v3 is a logger that sends the results of each training step to the dashboard of the Weights & Biases tool. To use this logger, Weights & Biases should be installed, and you should be logged in. The logger will send the full config file to W&B, as well as various system information such as memory utilization, network traffic, disk IO, GPU statistics, etc. This will also include information such as your hostname and operating system, as well as the location of your Python executable.

Note that by default, the full (interpolated) training config is sent over to the W&B dashboard. If you prefer to exclude certain information such as path names, you can list those fields in "dot notation" in the remove_config_values parameter. These fields will then be removed from the config before uploading, but will otherwise remain in the config file stored on your local system.

Example config

[training.logger]
@loggers = "spacy.WandbLogger.v3"
project_name = "monitor_spacy_training"
remove_config_values = ["paths.train", "paths.dev", "corpora.train.path", "corpora.dev.path"]
log_dataset_dir = "corpus"
model_log_interval = 1000

Name	Type	Description
project_name	str	The name of the project in the Weights & Biases interface. The project will be created automatically if it doesn't exist yet.
remove_config_values	List[str]	A list of values to exclude from the config before it is uploaded to W&B (default: []).
model_log_interval	Optional[int]	Steps to wait between logging model checkpoints to the W&B dasboard (default: None). Added in spacy.WandbLogger.v2.
log_dataset_dir	Optional[str]	Directory containing the dataset to be logged and versioned as a W&B artifact (default: None). Added in spacy.WandbLogger.v2.
run_name	Optional[str]	The name of the run. If you don't specify a run name, the name will be created by the wandb library (default: None). Added in spacy.WandbLogger.v3.
entity	Optional[str]	An entity is a username or team name where you're sending runs. If you don't specify an entity, the run will be sent to your default entity, which is usually your username (default: None). Added in spacy.WandbLogger.v3.
log_best_dir	Optional[str]	Directory containing the best trained model as saved by Spacy (by default in training/model-best), to be logged and versioned as a W&B artifact (default: None). Added in spacy.WandbLogger.v4.
log_latest_dir	Optional[str]	Directory containing the latest trained model as saved by Spacy (by default in training/model-latest), to be logged and versioned as a W&B artifact (default: None). Added in spacy.WandbLogger.v4.