PyTorch v1.13 반영, pytorch/tutorials@db34a77 (#615)

Author: 9bow

.build/validate_tutorials_built.py

@@ -0,0 +1,97 @@
+from pathlib import Path
+from typing import List
+
+from bs4 import BeautifulSoup
+
+REPO_ROOT = Path(__file__).parent.parent
+
+# For every tutorial on this list, we should determine if it is ok to not run the tutorial (add a comment after
+# the file name to explain why, like intro.html), or fix the tutorial and remove it from this list).
+
+NOT_RUN = [
+    "basics/intro",  # no code
+    "translation_transformer",
+    "profiler",
+    "saving_loading_models",
+    "introyt/captumyt",
+    "introyt/trainingyt",
+    "examples_nn/polynomial_module",
+    "examples_nn/dynamic_net",
+    "examples_nn/polynomial_optim",
+    "former_torchies/autograd_tutorial_old",
+    "former_torchies/tensor_tutorial_old",
+    "examples_autograd/polynomial_autograd",
+    "examples_autograd/polynomial_custom_function",
+    "parametrizations",
+    "mnist_train_nas",  # used by ax_multiobjective_nas_tutorial.py
+    "fx_conv_bn_fuser",
+    "super_resolution_with_onnxruntime",
+    "ddp_pipeline",  # requires 4 gpus
+    "fx_graph_mode_ptq_dynamic",
+    "vmap_recipe",
+    "torchscript_freezing",
+    "nestedtensor",
+    "recipes/saving_and_loading_models_for_inference",
+    "recipes/saving_multiple_models_in_one_file",
+    "recipes/loading_data_recipe",
+    "recipes/tensorboard_with_pytorch",
+    "recipes/what_is_state_dict",
+    "recipes/profiler_recipe",
+    "recipes/save_load_across_devices",
+    "recipes/warmstarting_model_using_parameters_from_a_different_model",
+    "recipes/dynamic_quantization",
+    "recipes/saving_and_loading_a_general_checkpoint",
+    "recipes/benchmark",
+    "recipes/tuning_guide",
+    "recipes/zeroing_out_gradients",
+    "recipes/defining_a_neural_network",
+    "recipes/timer_quick_start",
+    "recipes/amp_recipe",
+    "recipes/Captum_Recipe",
+    "hyperparameter_tuning_tutorial",
+    "flask_rest_api_tutorial",
+    "text_to_speech_with_torchaudio",
+]
+
+
+def tutorial_source_dirs() -> List[Path]:
+    return [
+        p.relative_to(REPO_ROOT).with_name(p.stem[:-7])
+        for p in REPO_ROOT.glob("*_source")
+    ]
+
+
+def main() -> None:
+    docs_dir = REPO_ROOT / "docs"
+    html_file_paths = []
+    for tutorial_source_dir in tutorial_source_dirs():
+        glob_path = f"{tutorial_source_dir}/**/*.html"
+        html_file_paths += docs_dir.glob(glob_path)
+
+    did_not_run = []
+    for html_file_path in html_file_paths:
+        with open(html_file_path, "r", encoding="utf-8") as html_file:
+            html = html_file.read()
+        html_soup = BeautifulSoup(html, "html.parser")
+        elems = html_soup.find_all("p", {"class": "sphx-glr-timing"})
+        for elem in elems:
+            if (
+                "Total running time of the script: ( 0 minutes  0.000 seconds)"
+                in elem.text
+                and not any(
+                    html_file_path.match(file) for file in NOT_RUN
+                )
+            ):
+                did_not_run.append(html_file_path.as_posix())
+
+    if len(did_not_run) != 0:
+        raise RuntimeError(
+            "The following file(s) are not known bad but ran in 0.000 sec, meaning that any "
+            + "python code in this tutorial probably didn't run:\n{}".format(
+                "\n".join(did_not_run)
+            )
+        )
+
+
+if __name__ == "__main__":
+    main()

.github/ISSUE_TEMPLATE/1_TRANSLATE_REQUEST.md

@@ -15,4 +15,4 @@ _(반드시 지키셔야 하는 일정이 아닙니다 - 일정이 너무 늦어
 ## 관련 이슈
 _현재 번역 요청 / 진행 내역을 보기 위해 각 버전의 메인 이슈를 참조합니다._ <br />
 _(특별한 일이 없다면 변경하지 않으셔도 됩니다.)_
-* 관련 이슈: #483 (v1.12)
+* 관련 이슈: #615 (v1.13)

Makefile

@@ -33,7 +33,7 @@ download:
 
 	# NOTE: Please consider using the Step1 and one of Step2 for new dataset,
 	# [something] should be replaced with the actual value.
-	# Step1. DOWNLOAD: wget -N [SOURCE_FILE] -P $(DATADIR)
+	# Step1. DOWNLOAD: wget -nv -N [SOURCE_FILE] -P $(DATADIR)
 	# Step2-1. UNZIP: unzip -o $(DATADIR)/[SOURCE_FILE] -d [*_source/data/]
 	# Step2-2. UNTAR: tar -xzf $(DATADIR)/[SOURCE_FILE] -C [*_source/data/]
 	# Step2-3. AS-IS: cp $(DATADIR)/[SOURCE_FILE] [*_source/data/]
@@ -46,18 +46,18 @@ download:
 	mkdir -p prototype_source/data
 
 	# transfer learning tutorial data
-	wget -N https://download.pytorch.org/tutorial/hymenoptera_data.zip -P $(DATADIR)
+	wget -nv -N https://download.pytorch.org/tutorial/hymenoptera_data.zip -P $(DATADIR)
 	unzip $(ZIPOPTS) $(DATADIR)/hymenoptera_data.zip -d beginner_source/data/
 
 	# nlp tutorial data
-	wget -N https://download.pytorch.org/tutorial/data.zip -P $(DATADIR)
+	wget -nv -N https://download.pytorch.org/tutorial/data.zip -P $(DATADIR)
 	unzip $(ZIPOPTS) $(DATADIR)/data.zip -d intermediate_source/  # This will unzip all files in data.zip to intermediate_source/data/ folder
 
 	# data loader tutorial
-	wget -N https://download.pytorch.org/tutorial/faces.zip -P $(DATADIR)
+	wget -nv -N https://download.pytorch.org/tutorial/faces.zip -P $(DATADIR)
 	unzip $(ZIPOPTS) $(DATADIR)/faces.zip -d beginner_source/data/
 
-	wget -N https://download.pytorch.org/models/tutorials/4000_checkpoint.tar -P $(DATADIR)
+	wget -nv -N https://download.pytorch.org/models/tutorials/4000_checkpoint.tar -P $(DATADIR)
 	cp $(DATADIR)/4000_checkpoint.tar beginner_source/data/
 
 	# neural style images
@@ -66,41 +66,45 @@ download:
 	cp -r _static/img/neural-style/ advanced_source/data/images/
 
 	# Download dataset for beginner_source/dcgan_faces_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/img_align_celeba.zip -P $(DATADIR)
+	wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/img_align_celeba.zip -P $(DATADIR)
 	unzip $(ZIPOPTS) $(DATADIR)/img_align_celeba.zip -d beginner_source/data/celeba
 
 	# Download dataset for beginner_source/hybrid_frontend/introduction_to_hybrid_frontend_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/iris.data -P $(DATADIR)
+	wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/iris.data -P $(DATADIR)
 	cp $(DATADIR)/iris.data beginner_source/data/
 
 	# Download dataset for beginner_source/chatbot_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/cornell_movie_dialogs_corpus.zip -P $(DATADIR)
-	unzip $(ZIPOPTS) $(DATADIR)/cornell_movie_dialogs_corpus.zip -d beginner_source/data/
+	wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/cornell_movie_dialogs_corpus_v2.zip -P $(DATADIR)
+	unzip $(ZIPOPTS) $(DATADIR)/cornell_movie_dialogs_corpus_v2.zip -d beginner_source/data/
 
 	# Download dataset for beginner_source/audio_classifier_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/UrbanSound8K.tar.gz -P $(DATADIR)
+	wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/UrbanSound8K.tar.gz -P $(DATADIR)
 	tar $(TAROPTS) -xzf $(DATADIR)/UrbanSound8K.tar.gz -C ./beginner_source/data/
 
 	# Download model for beginner_source/fgsm_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/lenet_mnist_model.pth -P $(DATADIR)
+	wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/lenet_mnist_model.pth -P $(DATADIR)
 	cp $(DATADIR)/lenet_mnist_model.pth ./beginner_source/data/lenet_mnist_model.pth
 
 	# Download model for advanced_source/dynamic_quantization_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/word_language_model_quantize.pth -P $(DATADIR)
+	wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/word_language_model_quantize.pth -P $(DATADIR)
 	cp $(DATADIR)/word_language_model_quantize.pth advanced_source/data/word_language_model_quantize.pth
 
 	# Download data for advanced_source/dynamic_quantization_tutorial.py
-	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/wikitext-2.zip -P $(DATADIR)
+	wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/wikitext-2.zip -P $(DATADIR)
 	unzip $(ZIPOPTS) $(DATADIR)/wikitext-2.zip -d advanced_source/data/
 
 	# Download model for advanced_source/static_quantization_tutorial.py
-	wget -N https://download.pytorch.org/models/mobilenet_v2-b0353104.pth -P $(DATADIR)
+	wget -nv -N https://download.pytorch.org/models/mobilenet_v2-b0353104.pth -P $(DATADIR)
 	cp $(DATADIR)/mobilenet_v2-b0353104.pth advanced_source/data/mobilenet_pretrained_float.pth
 
 	# Download model for prototype_source/graph_mode_static_quantization_tutorial.py
-	wget -N https://download.pytorch.org/models/resnet18-5c106cde.pth -P $(DATADIR)
+	wget -nv -N https://download.pytorch.org/models/resnet18-5c106cde.pth -P $(DATADIR)
 	cp $(DATADIR)/resnet18-5c106cde.pth prototype_source/data/resnet18_pretrained_float.pth
 
+	# Download vocab for beginner_source/flava_finetuning_tutorial.py
+	wget -nv -N http://dl.fbaipublicfiles.com/pythia/data/vocab.tar.gz -P $(DATADIR)
+	tar $(TAROPTS) -xzf $(DATADIR)/vocab.tar.gz -C ./beginner_source/data/
+
 	# Download some dataset for beginner_source/translation_transformer.py
 	python -m spacy download en_core_web_sm
 	python -m spacy download de_core_news_sm

README.md

@@ -3,8 +3,8 @@
 ## 소개
 
 PyTorch에서 제공하는 튜토리얼의 한국어 번역을 위한 저장소입니다.\
-번역의 결과물은 [https://tutorials.pytorch.kr](https://tutorials.pytorch.kr)에서 확인하실 수 있습니다. (번역을 진행하며 **불규칙적으로** 업데이트합니다.)\
-현재 버전의 번역 / 변경 관련 이슈는 [#483 이슈](https://github.com/PyTorchKorea/tutorials-kr/issues/483)를 참고해주세요.
+번역의 결과물은 [https://tutorials.pytorch.kr](https://tutorials.pytorch.kr)에서 확인하실 수 있습니다. (번역을 진행하며 **비정기적으로** 반영합니다.)\
+현재 버전의 번역 / 변경 관련 이슈는 [#615 이슈](https://github.com/PyTorchKorea/tutorials-kr/issues/615)를 참고해주세요.
 
 ## 기여하기
 
@@ -22,7 +22,7 @@ PyTorch에서 제공하는 튜토리얼의 한국어 번역을 위한 저장소
 
 ## 원문
 
-현재 PyTorch v1.12 튜토리얼([pytorch/tutorials@0918023](https://github.com/pytorch/tutorials/commit/091802395ed6cc5563643b6b6ef54ba99d412e66) 기준) 번역이 진행 중입니다.
+현재 PyTorch v1.13 튜토리얼([pytorch/tutorials@db34a77](https://github.com/pytorch/tutorials/commit/db34a779242f1a71346db4a9e5d6ac962a8d9b77) 기준) 번역이 진행 중입니다.
 
 최신 버전의 튜토리얼(공식, 영어)은 [PyTorch tutorials 사이트](https://pytorch.org/tutorials) 및 [PyTorch tutorials 저장소](https://github.com/pytorch/tutorials)를 참고해주세요.
 
@@ -46,5 +46,5 @@ v1.0 이후 번역은 별도 저장소로 관리하지 않습니다. [이 저장
 빌드 방법은 [기여하기 문서의 `2-5. (내 컴퓨터에서) 결과 확인하기`](https://github.com/PyTorchKorea/tutorials-kr/blob/master/CONTRIBUTING.md#2-5-내-컴퓨터에서-결과-확인하기) 부분을 참고해주세요.
 
 ---
-This is a project to translate [pytorch/tutorials@0918023](https://github.com/pytorch/tutorials/commit/091802395ed6cc5563643b6b6ef54ba99d412e66) into Korean.
+This is a project to translate [pytorch/tutorials@db34a77](https://github.com/pytorch/tutorials/commit/db34a779242f1a71346db4a9e5d6ac962a8d9b77) into Korean.
 For the latest version, please visit to the [official PyTorch tutorials repo](https://github.com/pytorch/tutorials).

_static/css/custom.css

@@ -0,0 +1,73 @@
+/* sphinx-design styles for cards/tabs
+*/
+
+:root {
+    --sd-color-info: #ee4c2c;
+    --sd-color-primary: #6c6c6d;
+    --sd-color-primary-highlight: #f3f4f7;
+    --sd-color-card-border-hover: #ee4c2c;
+    --sd-color-card-border: #f3f4f7;
+    --sd-color-card-background: #fff;
+    --sd-color-card-text: inherit;
+    --sd-color-card-header: transparent;
+    --sd-color-card-footer: transparent;
+    --sd-color-tabs-label-active: hsla(231, 99%, 66%, 1);
+    --sd-color-tabs-label-hover: hsla(231, 99%, 66%, 1);
+    --sd-color-tabs-label-inactive: hsl(0, 0%, 66%);
+    --sd-color-tabs-underline-active: hsla(231, 99%, 66%, 1);
+    --sd-color-tabs-underline-hover: rgba(178, 206, 245, 0.62);
+    --sd-color-tabs-underline-inactive: transparent;
+    --sd-color-tabs-overline: rgb(222, 222, 222);
+    --sd-color-tabs-underline: rgb(222, 222, 222);
+}
+
+.sd-text-info {
+    color: #ee4c2c;
+}
+
+
+.sd-card {
+    position: relative;
+    background-color: #fff;
+    opacity: 1.0;
+    border-radius: 0px;
+    width: 30%;
+    border: none;
+    padding-bottom: 0px;
+}
+
+
+.sd-card-img {
+    opacity: 0.5;
+    width: 200px;
+    padding: 0px;
+}
+
+.sd-card-img:hover {
+    opacity: 1.0;
+    background-color: #f3f4f7;
+}
+
+
+.sd-card:after {
+    display: block;
+    opacity: 1;
+    content: '';
+    border-bottom: solid 1px #ee4c2c;  
+    background-color: #fff;
+    transform: scaleX(0);  
+    transition: transform .250s ease-in-out;
+    transform-origin:  0% 50%;
+}
+
+.sd-card:hover {
+    background-color: #fff;
+    opacity: 1;
+    border-top: 1px solid #f3f4f7;
+    border-left: 1px solid #f3f4f7;
+    border-right: 1px solid #f3f4f7;
+}
+
+.sd-card:hover:after {
+    transform: scaleX(1);
+}