diff --git a/.actions/assistant.py b/.actions/assistant.py index 66fedcf49..912c13882 100644 --- a/.actions/assistant.py +++ b/.actions/assistant.py @@ -514,7 +514,7 @@ def group_folders( # unique folders dirs = set(dirs) # drop folder with skip folder - dirs = [pd for pd in dirs if not any(nd in AssistantCLI._SKIP_DIRS for nd in pd.split(os.path.sep))] + dirs = [pdir for pdir in dirs if not any(ndir in AssistantCLI._SKIP_DIRS for ndir in pdir.split(os.path.sep))] # valid folder has meta dirs_exist = [d for d in dirs if os.path.isdir(d)] dirs_invalid = [d for d in dirs_exist if not AssistantCLI._find_meta(d)] diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 27caece5c..3d3da9722 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -34,7 +34,7 @@ repos: hooks: - id: codespell additional_dependencies: [tomli] - args: ["--write-changes"] + #args: ["--write-changes"] - repo: https://github.com/PyCQA/docformatter rev: v1.7.3 @@ -45,6 +45,13 @@ repos: - "--wrap-summaries=119" - "--wrap-descriptions=120" + - repo: https://github.com/pre-commit/mirrors-prettier + rev: v3.0.3 + hooks: + - id: prettier + # https://prettier.io/docs/en/options.html#print-width + args: ["--print-width=120"] + - repo: https://github.com/psf/black rev: 23.3.0 hooks: diff --git a/course_UvA-DL/09-normalizing-flows/NF_image_modeling.py b/course_UvA-DL/09-normalizing-flows/NF_image_modeling.py index 3f5fdaba4..eb9ad4900 100644 --- a/course_UvA-DL/09-normalizing-flows/NF_image_modeling.py +++ b/course_UvA-DL/09-normalizing-flows/NF_image_modeling.py @@ -359,7 +359,7 @@ def test_step(self, batch, batch_idx): # ### Dequantization # # Normalizing flows rely on the rule of change of variables, which is naturally defined in continuous space. -# Applying flows directly on discrete data leads to undesired density models where arbitrarly high likelihood are placed on a few, particular values. +# Applying flows directly on discrete data leads to undesired density models where arbitrarily high likelihood are placed on a few, particular values. # See the illustration below: # #