From 3f3ca45872f441f019054235bef45dfddcaea5b4 Mon Sep 17 00:00:00 2001 From: Jeff Raubitschek Date: Mon, 17 Oct 2022 06:19:57 -0700 Subject: [PATCH] chore(sdk): rename default branch to `main` (#4374) --- .circleci/config.yml | 4 ++-- CONTRIBUTING.md | 6 +++--- README.md | 4 ++-- package_readme.md | 2 +- wandb/integration/prodigy/prodigy.py | 2 +- 5 files changed, 9 insertions(+), 9 deletions(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 61334f463d4..b5d5fcfe51b 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -60,7 +60,7 @@ parameters: default: false manual_nightly_git_branch: type: string - default: master + default: main manual_nightly_slack_notify: type: boolean default: false @@ -588,7 +588,7 @@ jobs: default: "3.8" git_branch: type: string - default: "master" + default: "main" execute: type: boolean default: true diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 573d78a4013..5b802baa4c6 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -74,8 +74,8 @@ Please make sure to update the ToC when you update this page! 3. Develop you contribution. - Make sure your fork is in sync with the main repository: ```shell - git checkout master - git pull upstream master + git checkout main + git pull upstream main ``` - Create a `git` branch where you will develop your contribution. Use a sensible name for the branch, for example: @@ -510,7 +510,7 @@ We use codecov to ensure we're executing all branches of logic in our tests. Bel 1. If you want to see the lines not covered you click on the “Diff” tab. then look for any “+” lines that have a red block for the line number 2. If you want more context about the files, go to the “Files” tab, it will highlight diffs, but you have to do even more searching for the lines you might care about -3. If you don't want to use codecov, you can use local coverage (I tend to do this for speeding things up a bit, run your tests then run tox -e cover ). This will give you the old school text output of missing lines (but not based on a diff from master) +3. If you don't want to use codecov, you can use local coverage (I tend to do this for speeding things up a bit, run your tests then run tox -e cover ). This will give you the old school text output of missing lines (but not based on a diff from main) We currently have 8 categories of test coverage: diff --git a/README.md b/README.md index b69902de2fb..e85871c37d1 100644 --- a/README.md +++ b/README.md @@ -3,7 +3,7 @@ Weights & Biases

-# Weights and Biases [![PyPI](https://img.shields.io/pypi/v/wandb)](https://pypi.python.org/pypi/wandb) [![Conda (channel only)](https://img.shields.io/conda/vn/conda-forge/wandb)](https://anaconda.org/conda-forge/wandb) [![CircleCI](https://img.shields.io/circleci/build/github/wandb/wandb/master)](https://circleci.com/gh/wandb/wandb) [![Codecov](https://img.shields.io/codecov/c/gh/wandb/wandb)](https://codecov.io/gh/wandb/wandb) +# Weights and Biases [![PyPI](https://img.shields.io/pypi/v/wandb)](https://pypi.python.org/pypi/wandb) [![Conda (channel only)](https://img.shields.io/conda/vn/conda-forge/wandb)](https://anaconda.org/conda-forge/wandb) [![CircleCI](https://img.shields.io/circleci/build/github/wandb/wandb/main)](https://circleci.com/gh/wandb/wandb) [![Codecov](https://img.shields.io/codecov/c/gh/wandb/wandb)](https://codecov.io/gh/wandb/wandb) Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. @@ -230,7 +230,7 @@ Use Weights & Biases Sweeps to automate hyperparameter optimization and explore ### Benefits of using W&B Sweeps - **Quick to set up:** With just a few lines of code you can run W&B sweeps. -- **Transparent:** We cite all the algorithms we're using, and our code is [open source](https://github.com/wandb/wandb/tree/master/wandb/sweeps). +- **Transparent:** We cite all the algorithms we're using, and our code is [open source](https://github.com/wandb/sweeps). - **Powerful:** Our sweeps are completely customizable and configurable. You can launch a sweep across dozens of machines, and it's just as easy as starting a sweep on your laptop. Weights & Biases diff --git a/package_readme.md b/package_readme.md index 4b3077ce74b..2642f1cd29e 100644 --- a/package_readme.md +++ b/package_readme.md @@ -2,7 +2,7 @@

-# Weights and Biases [![PyPI](https://img.shields.io/pypi/v/wandb)](https://pypi.python.org/pypi/wandb) [![Conda (channel only)](https://img.shields.io/conda/vn/conda-forge/wandb)](https://anaconda.org/conda-forge/wandb) [![CircleCI](https://img.shields.io/circleci/build/github/wandb/wandb/master)](https://circleci.com/gh/wandb/wandb) [![Codecov](https://img.shields.io/codecov/c/gh/wandb/wandb)](https://codecov.io/gh/wandb/wandb) +# Weights and Biases [![PyPI](https://img.shields.io/pypi/v/wandb)](https://pypi.python.org/pypi/wandb) [![Conda (channel only)](https://img.shields.io/conda/vn/conda-forge/wandb)](https://anaconda.org/conda-forge/wandb) [![CircleCI](https://img.shields.io/circleci/build/github/wandb/wandb/main)](https://circleci.com/gh/wandb/wandb) [![Codecov](https://img.shields.io/codecov/c/gh/wandb/wandb)](https://codecov.io/gh/wandb/wandb) Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. diff --git a/wandb/integration/prodigy/prodigy.py b/wandb/integration/prodigy/prodigy.py index 43623bdb683..57ec6d77b56 100644 --- a/wandb/integration/prodigy/prodigy.py +++ b/wandb/integration/prodigy/prodigy.py @@ -32,7 +32,7 @@ def named_entity(docs): """Creates a named entity visualization. - Taken from https://github.com/wandb/wandb/blob/master/wandb/plots/named_entity.py + Taken from https://github.com/wandb/wandb/blob/main/wandb/plots/named_entity.py """ spacy = util.get_module(