From b8894f181dd10fb93e8ffb86ad3cfdda7f4a3380 Mon Sep 17 00:00:00 2001 From: Nathan Lambert Date: Thu, 8 Sep 2022 01:08:35 -0600 Subject: [PATCH] Docs fix some typos (#408) * fix small typos * capitalize Diffusers --- docs/source/api/pipelines/overview.mdx | 2 +- docs/source/conceptual/contribution.mdx | 10 +++++----- docs/source/conceptual/philosophy.mdx | 2 +- docs/source/index.mdx | 2 +- 4 files changed, 8 insertions(+), 8 deletions(-) diff --git a/docs/source/api/pipelines/overview.mdx b/docs/source/api/pipelines/overview.mdx index 2dd2fb04a5..30519b2d17 100644 --- a/docs/source/api/pipelines/overview.mdx +++ b/docs/source/api/pipelines/overview.mdx @@ -82,7 +82,7 @@ not be used for training. If you want to store the gradients during the forward ## Contribution -We are more than happy about any contribution to the offically supported pipelines ๐Ÿค—. We aspire +We are more than happy about any contribution to the officially supported pipelines ๐Ÿค—. We aspire all of our pipelines to be **self-contained**, **easy-to-tweak**, **beginner-friendly** and for **one-purpose-only**. - **Self-contained**: A pipeline shall be as self-contained as possible. More specifically, this means that all functionality should be either directly defined in the pipeline file iteslf, should be inherited from (and only from) the [`DiffusionPipeline` class](.../diffusion_pipeline) or be directly attached to the model and scheduler components of the pipeline. diff --git a/docs/source/conceptual/contribution.mdx b/docs/source/conceptual/contribution.mdx index 26e910926a..ef6cc69468 100644 --- a/docs/source/conceptual/contribution.mdx +++ b/docs/source/conceptual/contribution.mdx @@ -35,7 +35,7 @@ You can contribute in so many ways! Just to name a few: *All are equally valuable to the community.* -### Browse github issues for suggestions +### Browse GitHub issues for suggestions If you need inspiration, you can look out for [issues](https://github.com/huggingface/diffusers/issues) you'd like to tackle to contribute to the library. There are a few filters that can be helpful: @@ -56,7 +56,7 @@ The ๐Ÿงจ Diffusers library is robust and reliable thanks to the users who notify the problems they encounter. So thank you for reporting an issue. First, we would really appreciate it if you could **make sure the bug was not -already reported** (use the search bar on Github under Issues). +already reported** (use the search bar on GitHub under Issues). ### Do you want to implement a new diffusion pipeline / diffusion model? @@ -127,7 +127,7 @@ Follow these steps to start contributing ([supported Python versions](https://gi $ pip install -e ".[dev]" ``` - (If diffusers was already installed in the virtual environment, remove + (If Diffusers was already installed in the virtual environment, remove it with `pip uninstall diffusers` before reinstalling it in editable mode with the `-e` flag.) @@ -231,7 +231,7 @@ Follow these steps to start contributing ([supported Python versions](https://gi `RUN_SLOW=1 python -m pytest tests/test_my_new_model.py`. - If you are adding a new tokenizer, write tests, and make sure `RUN_SLOW=1 python -m pytest tests/test_tokenization_{your_model_name}.py` passes. - CircleCI does not run the slow tests, but github actions does every night! + CircleCI does not run the slow tests, but GitHub actions does every night! 6. All public methods must have informative docstrings that work nicely with sphinx. See `[pipeline_latent_diffusion.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py)` for an example. 7. Due to the rapidly growing repository, it is important to make sure that no files that would significantly weigh down the repository are added. This includes images, videos and other non-text files. We prefer to leverage a hf.co hosted `dataset` like the ones hosted on [`hf-internal-testing`](https://huggingface.co/hf-internal-testing) in which to place these files and reference or [huggingface/documentation-images](https://huggingface.co/datasets/huggingface/documentation-images). @@ -274,7 +274,7 @@ $ python -m unittest discover -s examples -t examples -v To avoid pinging the upstream repository which adds reference notes to each upstream PR and sends unnecessary notifications to the developers involved in these PRs, when syncing the main branch of a forked repository, please, follow these steps: -1. When possible, avoid syncing with the upstream using a branch and PR on the forked repository. Instead merge directly into the forked main. +1. When possible, avoid syncing with the upstream using a branch and PR on the forked repository. Instead, merge directly into the forked main. 2. If a PR is absolutely necessary, use the following steps after checking out your branch: ``` $ git checkout -b your-branch-for-syncing diff --git a/docs/source/conceptual/philosophy.mdx b/docs/source/conceptual/philosophy.mdx index db1f039284..468307623c 100644 --- a/docs/source/conceptual/philosophy.mdx +++ b/docs/source/conceptual/philosophy.mdx @@ -13,5 +13,5 @@ specific language governing permissions and limitations under the License. # Philosophy - Readability and clarity are preferred over highly optimized code. A strong importance is put on providing readable, intuitive and elementary code design. *E.g.*, the provided [schedulers](https://github.com/huggingface/diffusers/tree/main/src/diffusers/schedulers) are separated from the provided [models](https://github.com/huggingface/diffusers/tree/main/src/diffusers/models) and use well-commented code that can be read alongside the original paper. -- Diffusers is **modality independent** and focuses on providing pretrained models and tools to build systems that generate **continous outputs**, *e.g.* vision and audio. This is one of the guiding goals even if the initial pipelines are devoted to vision tasks. +- Diffusers is **modality independent** and focuses on providing pretrained models and tools to build systems that generate **continuous outputs**, *e.g.* vision and audio. This is one of the guiding goals even if the initial pipelines are devoted to vision tasks. - Diffusion models and schedulers are provided as concise, elementary building blocks. In contrast, diffusion pipelines are a collection of end-to-end diffusion systems that can be used out-of-the-box, should stay as close as possible to their original implementations and can include components of other libraries, such as text encoders. Examples of diffusion pipelines are [Glide](https://github.com/openai/glide-text2im), [Latent Diffusion](https://github.com/CompVis/latent-diffusion) and [Stable Diffusion](https://github.com/compvis/stable-diffusion). diff --git a/docs/source/index.mdx b/docs/source/index.mdx index 4868dae6dd..c134925cc6 100644 --- a/docs/source/index.mdx +++ b/docs/source/index.mdx @@ -23,7 +23,7 @@ specific language governing permissions and limitations under the License. More precisely, ๐Ÿค— Diffusers offers: - State-of-the-art diffusion pipelines that can be run in inference with just a couple of lines of code (see [**Using Diffusers**](./using-diffusers/conditional_image_generation)) or have a look at [**Pipelines**](#pipelines) to get an overview of all supported pipelines and their corresponding papers. -- Various noise schedulers that can be used interchangeably for the prefered speed vs. quality trade-off in inference. For more information see [**Schedulers**](./api/schedulers). +- Various noise schedulers that can be used interchangeably for the preferred speed vs. quality trade-off in inference. For more information see [**Schedulers**](./api/schedulers). - Multiple types of models, such as UNet, can be used as building blocks in an end-to-end diffusion system. See [**Models**](./api/models) for more details - Training examples to show how to train the most popular diffusion model tasks. For more information see [**Training**](./training/overview).