From 7e43f29d5269858729509c0de83a124c4a6ee650 Mon Sep 17 00:00:00 2001 From: Patrick Labatut Date: Tue, 22 Jun 2021 03:44:27 -0700 Subject: [PATCH] Lint codebase Summary: Lint codebase Reviewed By: bottler Differential Revision: D29263057 fbshipit-source-id: ac97f01d2a79fead3b09c2cbb21b50ce688a577d --- .github/CONTRIBUTING.md | 2 +- .github/ISSUE_TEMPLATE/bugs.md | 2 +- .github/ISSUE_TEMPLATE/questions-help.md | 4 ++-- docs/README.md | 3 +-- docs/notes/why_pytorch3d.md | 3 +-- docs/tutorials/data/cow_mesh/README.md | 1 - tests/common_testing.py | 2 +- 7 files changed, 7 insertions(+), 10 deletions(-) diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md index 784dcfde..e9fb69c2 100644 --- a/.github/CONTRIBUTING.md +++ b/.github/CONTRIBUTING.md @@ -43,7 +43,7 @@ Facebook has a [bounty program](https://www.facebook.com/whitehat/) for the safe disclosure of security bugs. In those cases, please go through the process outlined on that page and do not file a public issue. -## Coding Style +## Coding Style We follow these [python](http://google.github.io/styleguide/pyguide.html) and [C++](https://google.github.io/styleguide/cppguide.html) style guides. For the linter to work, you will need to install `black`, `flake`, `isort` and `clang-format`, and diff --git a/.github/ISSUE_TEMPLATE/bugs.md b/.github/ISSUE_TEMPLATE/bugs.md index beb4d621..bbba16af 100644 --- a/.github/ISSUE_TEMPLATE/bugs.md +++ b/.github/ISSUE_TEMPLATE/bugs.md @@ -27,4 +27,4 @@ Please include the following (depending on what the issue is): ``` Please also simplify the steps as much as possible so they do not require additional resources to - run, such as a private dataset. + run, such as a private dataset. diff --git a/.github/ISSUE_TEMPLATE/questions-help.md b/.github/ISSUE_TEMPLATE/questions-help.md index bb5a81e8..639d0ff8 100644 --- a/.github/ISSUE_TEMPLATE/questions-help.md +++ b/.github/ISSUE_TEMPLATE/questions-help.md @@ -17,5 +17,5 @@ Also note the following: please use the "Bugs / Unexpected behaviors" issue template. 2. We do not answer general machine learning / computer vision questions that are not specific to - PyTorch3D, such as how a model works or what algorithm/methods can be - used to achieve X. + PyTorch3D, such as how a model works or what algorithm/methods can be + used to achieve X. diff --git a/docs/README.md b/docs/README.md index 3ef8ba77..0d138783 100644 --- a/docs/README.md +++ b/docs/README.md @@ -1,4 +1,3 @@ - ## Setup ### Install dependencies @@ -12,7 +11,7 @@ pip install -U recommonmark mock sphinx sphinx_rtd_theme sphinx_markdown_tables We want to include the root readme as an overview. Before generating the docs create a symlink to the root readme. ``` -cd docs +cd docs ln -s ../README.md overview.md ``` diff --git a/docs/notes/why_pytorch3d.md b/docs/notes/why_pytorch3d.md index 4e32449d..6d11e659 100644 --- a/docs/notes/why_pytorch3d.md +++ b/docs/notes/why_pytorch3d.md @@ -7,7 +7,6 @@ sidebar_label: Why PyTorch3D # Why PyTorch3D -Our goal with PyTorch3D is to help accelerate research at the intersection of deep learning and 3D. 3D data is more complex than 2D images and while working on projects such as [Mesh R-CNN](https://github.com/facebookresearch/meshrcnn) and [C3DPO](https://github.com/facebookresearch/c3dpo_nrsfm), we encountered several challenges including 3D data representation, batching, and speed. We have developed many useful operators and abstractions for working on 3D deep learning and want to share this with the community to drive novel research in this area. +Our goal with PyTorch3D is to help accelerate research at the intersection of deep learning and 3D. 3D data is more complex than 2D images and while working on projects such as [Mesh R-CNN](https://github.com/facebookresearch/meshrcnn) and [C3DPO](https://github.com/facebookresearch/c3dpo_nrsfm), we encountered several challenges including 3D data representation, batching, and speed. We have developed many useful operators and abstractions for working on 3D deep learning and want to share this with the community to drive novel research in this area. In PyTorch3D we have included efficient 3D operators, heterogeneous batching capabilities, and a modular differentiable rendering API, to equip researchers in this field with a much needed toolkit to implement cutting-edge research with complex 3D inputs. - diff --git a/docs/tutorials/data/cow_mesh/README.md b/docs/tutorials/data/cow_mesh/README.md index 27c1a6e0..c7ff345e 100644 --- a/docs/tutorials/data/cow_mesh/README.md +++ b/docs/tutorials/data/cow_mesh/README.md @@ -1,4 +1,3 @@ - # Acknowledgements Thank you to Keenen Crane for allowing the cow mesh model to be used freely in the public domain. diff --git a/tests/common_testing.py b/tests/common_testing.py index b1026257..b0ffdf6b 100644 --- a/tests/common_testing.py +++ b/tests/common_testing.py @@ -110,7 +110,7 @@ class TestCaseMixin(unittest.TestCase): diff = norm_fn(input - other) other_ = norm_fn(other) - # We want to generalise allclose(input, output), which is essentially + # We want to generalize allclose(input, output), which is essentially # all(diff <= atol + rtol * other) # but with a sophisticated handling non-finite values. # We work that around by calling allclose() with the following arguments: