From 5f456edce9f05f38bbeecf295ede1713f2a9d9b4 Mon Sep 17 00:00:00 2001 From: Max Pumperla Date: Tue, 18 Apr 2023 22:24:15 +0200 Subject: [PATCH] Revert "Revert "[docs] new landing page"" (#34534) Signed-off-by: elliottower --- doc/source/_includes/_contribute.md | 28 -- doc/source/_static/css/custom.css | 114 +++++- doc/source/_static/img/AIR.png | Bin 0 -> 732 bytes doc/source/_static/img/Core.png | Bin 0 -> 425 bytes doc/source/_static/img/LandingPageBG.jpg | Bin 0 -> 35876 bytes doc/source/_static/img/chat.png | Bin 0 -> 218 bytes doc/source/_static/img/code.png | Bin 0 -> 3046 bytes doc/source/_static/img/colab.png | Bin 0 -> 1486 bytes doc/source/_static/img/download.png | Bin 0 -> 3035 bytes doc/source/_static/img/github-fill.png | Bin 0 -> 481 bytes doc/source/_static/img/mail.png | Bin 0 -> 263 bytes doc/source/_static/img/meetup.png | Bin 0 -> 931 bytes doc/source/_static/img/pen.png | Bin 0 -> 207 bytes doc/source/_static/img/ray_logo.png | Bin 0 -> 3504 bytes doc/source/_static/img/rayclusters.png | Bin 0 -> 279 bytes doc/source/_static/img/slack-fill.png | Bin 0 -> 490 bytes doc/source/_static/img/twitter-fill.png | Bin 0 -> 394 bytes doc/source/_static/js/custom.js | 20 -- doc/source/conf.py | 2 +- doc/source/index.md | 431 ++++++++++++++++++++--- 20 files changed, 494 insertions(+), 101 deletions(-) delete mode 100644 doc/source/_includes/_contribute.md create mode 100644 doc/source/_static/img/AIR.png create mode 100644 doc/source/_static/img/Core.png create mode 100644 doc/source/_static/img/LandingPageBG.jpg create mode 100644 doc/source/_static/img/chat.png create mode 100644 doc/source/_static/img/code.png create mode 100644 doc/source/_static/img/colab.png create mode 100644 doc/source/_static/img/download.png create mode 100644 doc/source/_static/img/github-fill.png create mode 100644 doc/source/_static/img/mail.png create mode 100644 doc/source/_static/img/meetup.png create mode 100644 doc/source/_static/img/pen.png create mode 100644 doc/source/_static/img/ray_logo.png create mode 100644 doc/source/_static/img/rayclusters.png create mode 100644 doc/source/_static/img/slack-fill.png create mode 100644 doc/source/_static/img/twitter-fill.png diff --git a/doc/source/_includes/_contribute.md b/doc/source/_includes/_contribute.md deleted file mode 100644 index 971c677d6a4e..000000000000 --- a/doc/source/_includes/_contribute.md +++ /dev/null @@ -1,28 +0,0 @@ -```{admonition} Get involved and become part of the Ray community -:class: tip - -πŸ’¬ [Join our community](https://forms.gle/9TSdDYUgxYs8SA9e8): -Discuss all things Ray with us in our community Slack channel or use our -[discussion board](https://discuss.ray.io/) to ask questions and get answers. - -πŸ’‘ [Open an issue](https://github.com/ray-project/ray/issues/new/choose): -Help us improve Ray by submitting feature requests, bug-reports, or simply ask for help and get support via GitHub issues. - -πŸ‘©β€πŸ’» [Create a pull request](https://github.com/ray-project/ray/pulls): -Found a typo in the documentation? Want to add a new feature? Submit a pull request to help us improve Ray. - -πŸ“° [Subscribe to the Ray newsletter](https://share.hsforms.com/1Ee3Gh8c9TY69ZQib-yZJvgc7w85): -Get the latest news from Ray in a monthly email: Ray updates, community highlights, events, useful tutorials, and more! - -🐦 [Follow us on Twitter](https://twitter.com/raydistributed): -Stay up to date with the latest news and updates on Ray. - -⭐ [Star and follow us on GitHub](https://github.com/ray-project/ray): -Support Ray by following its development on GitHub and give us a boost by starring the project. - -🀝🏿 [Join our Meetup Group](https://www.meetup.com/Bay-Area-Ray-Meetup/): -Join one of our community events to learn more about Ray and get a chance to meet the team behind Ray. - -πŸ™Œ [Discuss on Stack Overflow](https://stackoverflow.com/questions/tagged/ray): -Use the `[ray]` tag on Stack Overflow to ask and answer questions about Ray usage. -``` diff --git a/doc/source/_static/css/custom.css b/doc/source/_static/css/custom.css index caae0617fcc8..d2e920761432 100644 --- a/doc/source/_static/css/custom.css +++ b/doc/source/_static/css/custom.css @@ -79,6 +79,19 @@ div.navbar-brand-box { } } +@media screen and (max-width: 767px) { + .remove-mobile { + display: none; + } + } + + @media screen and (max-width: 767px) { + .row-2-column { + flex-direction: column; + margin-top: 20px; + } + } + /* Make Algolia search box scrollable */ .algolia-autocomplete .ds-dropdown-menu { height: 60vh !important; @@ -520,4 +533,103 @@ span.rst-current-version > span.fa.fa-book { /* Adjustment to Version block */ .rst-versions { z-index: 1200 !important; -} \ No newline at end of file +} + +.image-header { + display: flex; + flex-direction: row; + align-items: center; + padding-left: 16px; + padding-right:16px; + gap: 16px; +} + +.info-box { + box-shadow: 0px 4px 20px rgba(0, 0, 0, 0.05); + border-radius: 8px; + padding: 20px; +} + +.info-box:hover{ + box-shadow: 0px 4px 20px rgba(0, 0, 0, 0.1); +} + +.no-underline{ + text-decoration: none; +} +.no-underline:hover{ + text-decoration: none; +} + +.icon-hover:hover{ + height: 30px ; + width: 30px; +} + +.info-box-2 { + background-color: #F9FAFB; + border-radius: 8px; + padding-right: 16px; + padding-left: 16px; + padding-bottom: 24px; + padding-top: 4px; +} + + +.bold-link { + color: #000000 !important; + font-weight: 600; +} + +.community-box { + border: 1px solid #D2DCE6; + border-radius: 8px; + display: flex; + margin-bottom: 16px; +} + +.community-box:hover { + box-shadow: 0px 4px 20px rgba(0, 0, 0, 0.05); + text-decoration: none; +} + +.community-box p { + margin-top: 1rem !important; +} + +.tab-pane pre { + margin: 0; + padding: 0; + max-height: 252px; + overflow-y: auto; +} + +.grid-container { + display: grid; + grid-template-columns: repeat(auto-fit, minmax(300px,1fr)); + grid-gap: 16px; +} + +.grid-item { +padding: 20px; +} + + +.nav-pills { + background-color: #F9FAFB; + color: #000000; + padding: 8px; + border-bottom:none; + border-radius: 8px; +} + +.nav-pills .nav-link.active { + background-color: #FFFFFF !important; + box-shadow: 0px 3px 14px 2px rgba(3,28,74,0.12); + border-radius: 8px; + padding: 20px; + color: #000000; + font-weight: 500; +} + + diff --git a/doc/source/_static/img/AIR.png b/doc/source/_static/img/AIR.png new file mode 100644 index 0000000000000000000000000000000000000000..885225eb742c03001c85e6585c20b3329c1b0a20 GIT binary patch literal 732 zcmV<20wev2P))_I=SG}o2kmir$tGl%Cwu>i^UBt)BZ&;*kX%_Jky z5%(#u0>Kv!r)jFIs?t#uHG=otKf_8KZbVCJ4Rn@eU3V!ZG6X1VbD_|yv1YQ>=|C+O zsKcKT7^l+-o6QDgSz-wU7koaSYc7Skf=lL9{6#sOMg9Y2bLL+tVCwDw O0000fr literal 0 HcmV?d00001 diff --git a/doc/source/_static/img/Core.png b/doc/source/_static/img/Core.png new file mode 100644 index 0000000000000000000000000000000000000000..f76c57c6a56b0dc43acf896b479ff36c27c8b593 GIT binary patch literal 425 zcmV;a0apHrP)B_II_<&!^1r)5}R6E#~Du^l-b5<{qd!2fyDy6H! z^V*gzdcfx#1x#BO5vkDaNO7>mdGpt(^N?@!QdC=34`Gdaq7-mGS0Xev|z|F<^1jHTSD7Skv( 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version : "latest"; - -home.href = "https://docs.ray.io/en/" + res + "/index.html"; -home.textContent = "Ray Docs Home"; - -home.style = firstLink.style; -home.style.color = "#5a5a5a"; -firstLink.appendChild(home); diff --git a/doc/source/conf.py b/doc/source/conf.py index d3a36145b791..28c50db32e28 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -257,7 +257,7 @@ "use_issues_button": True, "use_edit_page_button": True, "path_to_docs": "doc/source", - "home_page_in_toc": False, + "home_page_in_toc": True, "show_navbar_depth": 1, "announcement": "
", } diff --git a/doc/source/index.md b/doc/source/index.md index 313daa4eb143..cb33f3860e65 100644 --- a/doc/source/index.md +++ b/doc/source/index.md @@ -1,79 +1,408 @@ ```{include} /_includes/overview/announcement.md ``` -# Welcome to the Ray documentation +```{title} Welcome to Ray! +``` -````{panels} -:container: text-center -:column: col-lg-6 px-2 py-2 -:card: +```{raw} html ---- -getting_started + + + + -**Getting started** -^^^^^^^^^^^^^^^ -Learn how to install Ray, compute an example with the Ray Core API, and use Ray's ML libraries. + -+++ +Welcome to Ray! -{link-badge}`ray-overview/index.html,"Overview",cls=badge-light` -{link-badge}`ray-overview/getting-started.html,"Getting started",cls=badge-light` +
+
+
+
+

Welcome to Ray!

+

Ray is an open-source unified framework for scaling AI and Python applications. + It provides the compute layer for parallel processing so that + you don’t need to be a distributed systems expert. +

+
+ + + + + + + + + +
+
+
+ +
+
+
+
---- -user_guide -**User guides** -^^^^^^^^^^^ +
+

Getting Started

+ +
+
+
+ +

Learn basics

+
+

Understand how the Ray framework scales your ML workflows.

+

Learn more >

+
+
+
+ +

Install Ray

+
+ 

pip install "ray[default]"

+

Installation guide >

 +
+
+
+ +

Try it out

+
+

Experiment with Ray with an introductory notebook.

+

Open the notebook>

+
+
+ +
-Learn about the key concepts and features. Get in-depth information about Ray's libraries and tooling. -+++ +

Scaling with Ray

-{link-badge}`data/user-guide.html,"Data",cls=badge-light` -{link-badge}`train/user-guides.html,"Train",cls=badge-light` -{link-badge}`tune/tutorials/overview.html,"Tune",cls=badge-light` -{link-badge}`serve/tutorials/index.html,"Serve",cls=badge-light` -{link-badge}`ray-core/user-guide.html,"Core",cls=badge-light` -{link-badge}`cluster/running-applications/index.html,"Clusters",cls=badge-light` ---- -api +
+
+ +
+
+
+
+ 

+from ray import data
 
-**API reference**
-^^^^^^^^^^^^^
+# Step 1: read 100 files in parallel from S3 directory
+dataset = data.read_csv(paths="s3://structured/data", parallelism=100)
 
-Find detailed descriptions of the Ray APIs, their functions, classes, and methods.
-The reference assumes familiarity with the key concepts.
+# Step 2: partition the dataset into blocks
+dataset = dataset.repartition(num_blocks=1000)
 
-+++
+# Step 3: preprocess the data at scale, 1000 blocks in parallel
+preprocessor = data.preprocessors.StandardScaler(columns=["value"])
+dataset_transformed = preprocessor.fit_transform(dataset=dataset)
 
-{link-badge}`ray-references/api.html,"API reference",cls=badge-light`
+
+
+
+ Learn more | API references +
+
+ + Open in colab + +
+
+
+
+ 

+from ray.air.config import ScalingConfig
+from ray.train.torch import TorchTrainer
 
----
-contribute
+# Step 1: setup PyTorch model training as you normally would
+def train_loop_per_worker():
+    model = ...
+    train_dataset = ...
+    for epoch in range(num_epochs):
+        ...  # model training logic
 
-**Developer guides**
-^^^^^^^^^^^^^^^
+# Step 2: setup Ray's PyTorch Trainer to run on 32 GPUs
+trainer = TorchTrainer(
+    train_loop_per_worker=train_loop_per_worker,
+    scaling_config=ScalingConfig(num_workers=32, use_gpu=True),
+    datasets={"train": train_dataset},
+)
 
-Find information about Ray's internals, and how to debug or profile Ray, fix a bug, or contribute a new feature.
+# Step 3: run distributed model training on 32 GPUs
+result = trainer.fit()
+
+
+
+ Learn more | API references +
+
+ + Open in colab + +
+
+
+
+ 

+from ray import tune
+from ray.air.config import ScalingConfig
+from ray.train.lightgbm import LightGBMTrainer
 
-+++
+train_dataset, eval_dataset = ...
 
-{link-badge}`https://docs.ray.io/en/master/ray-contribute/getting-involved.html,"Developer guides",cls=badge-light`
+# Step 1: setup Ray's LightGBM Trainer to train on 64 CPUs
+trainer = LightGBMTrainer(
+    ...
+    scaling_config=ScalingConfig(num_workers=64),
+    datasets={"train": train_dataset, "eval": eval_dataset},
+)
 
-````
+# Step 2: setup Ray Tuner to run 1000 trials
+tuner = tune.Tuner(
+    trainer=trainer,
+    param_space=hyper_param_space,
+    tune_config=tune.TuneConfig(num_sa
+    les=1000),
+)
 
-## Getting involved
+# Step 3: run distributed HPO with 1000 trials; each trial runs on 64 CPUs
+result_grid = tuner.fit()
 
-Ray is also an active community of developers, researchers, and folks that love machine learning.
-Here's how to get involved with the Ray community:
+
+
+
+ Learn more | API references +
+
+ + Open in Github + +
+
+
+
+ 

+from ray.train.batch_predictor import BatchPredictor
+from ray.train.torch import TorchPredictor
+
+dataset = ...
+
+# Step 1: create batch predictor to run inference at scale
+batch_predictor = BatchPredictor.from_checkpoint(
+    checkpoint=model_checkpoint, predictor_cls=TorchPredictor
+)
+
+# Step 2: run batch inference on 64 GPUs
+results = batch_predictor.predict(dataset, batch_size=512, num_gpus_per_worker=64)
+
+
+
+ Learn more +
+
+ + Open in colab + +
+
+
+
+ 

+from ray import serve
+from ray.serve import PredictorDeployment
+from ray.train.lightgbm import LightGBMPredictor
+
+# Deploy 50 replicas of the LightGBM model as a live endpoint.
+# Convert incoming JSON requests into a DataFrame.
+serve.run(
+    PredictorDeployment.options(
+        name="LightGBM_Service",
+        num_replicas=50,
+    ).bind(
+        predictor_cls=LightGBMPredictor,
+        checkpoint=lgbm_best_checkpoint,
+        http_adapter=serve.http_adapters.pandas_read_json,
+    )
+)
+
+
+
+ Learn more | API references +
+
+ + Open in colab + +
+
+
+
+ 

+from ray.rllib.algorithms.ppo import PPOConfig
+
+# Step 1: configure PPO to run 64 parallel workers to collect samples from the env.
+ppo_config = (
+    PPOConfig()
+    .environment(env="Taxi-v3")
+    .rollouts(num_rollout_workers=64)
+    .framework("torch")
+    .training(model=rnn_lage)
+)
+
+# Step 2: build the PPO algorithm
+ppo_algo = ppo_config.build()
+
+# Step 3: train and evaluate PPO
+for _ in range(5):
+    print(ppo_algo.train())
+
+ppo_algo.evaluate()
+
+
+
+ Learn more | API references +
+
+ + Open in Github + +
+
+
+ + +
+
+
+ +
+ + +
+

Beyond the basics

+
+ +
+
+
+ +

Ray AI Runtime

+
+

Scale the entire ML pipeline from data ingest to model serving with high-level Python APIs that integrate with popular ecosystem frameworks.

+ Learn more about AIR > +
+
+
+ +

Ray Core

+
+

Scale generic Python code with simple, foundational primitives that enable a high degree of control for building distributed applications or custom platforms.

+ Learn more about Core > +
+
+
+ +

Ray Clusters

+
+

Deploy a Ray cluster on AWS, GCP, Azure or kubernetes from a laptop to a large cluster to seamlessly scale workloads for production

+ Learn more about clusters > +
+
-```{include} _includes/_contribute.md -``` -If you're interested in contributing to Ray, see the -[contributing guide for the current release](ray-contribute/getting-involved) -or the -[latest version of our contributing guide](https://docs.ray.io/en/latest/ray-contribute/getting-involved.html) -to read about the contribution process and see what you can work on. +
+

Getting involved

+
+
+ + + +
+``` \ No newline at end of file