Polish Orca Doc (#6266)
* fix doc * add tutorial index * remove * fix * remove * update
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Kai Huang
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9 changed files with 38 additions and 21 deletions
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@ -26,7 +26,7 @@ subtrees:
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- entries:
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- file: doc/Orca/Overview/orca
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title: "Orca in 5 miniutes"
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title: "Orca in 5 minutes"
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- file: doc/Orca/Overview/install
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title: "Installation"
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- file: doc/Orca/Overview/index
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@ -39,7 +39,7 @@ subtrees:
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- file: doc/Orca/Overview/distributed-tuning
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- file: doc/Orca/Overview/ray
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- file: doc/Orca/QuickStart/index
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title: "Tutorials"
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title: "Quick Examples"
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subtrees:
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- entries:
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- file: doc/UseCase/spark-dataframe
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@ -48,6 +48,11 @@ subtrees:
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- file: doc/Orca/QuickStart/orca-pytorch-distributed-quickstart
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- file: doc/Orca/QuickStart/orca-autoestimator-pytorch-quickstart
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- file: doc/Orca/QuickStart/orca-autoxgboost-quickstart
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- file: doc/Orca/Tutorial/index
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title: "Tutorials"
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subtrees:
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- entries:
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- file: doc/Orca/Tutorial/yarn
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- file: doc/Orca/Overview/known_issues
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title: "Tips and Known Issues"
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- file: doc/PythonAPI/Orca/index
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@ -1,2 +0,0 @@
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Orca Key Features
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=================================
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@ -1,7 +1,7 @@
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# Installation
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## To use Distributed Data processing, training, and/or inference
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## To use basic Orca features
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We recommend using [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/) to prepare the Python environment.
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```bash
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conda create -n py37 python=3.7 # "py37" is conda environment name, you can use any name you like.
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@ -14,32 +14,38 @@ You can install bigdl-orca nightly build version using
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pip install --pre --upgrade bigdl-orca
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```
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## To use RayOnSpark
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## To additionally use RayOnSpark
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There're some additional dependencies required for running [RayOnSpark](ray.md). Use extra key `[ray]` to install.
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If you wish to run [RayOnSpark](ray.md) or [sklearn-style Estimator APIs in Orca](distributed-training-inference.md) with "ray" backend, use the extra key `[ray]` during the installation above:
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```bash
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pip install bigdl-orca[ray]
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```
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or to install nightly build, use
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or for the nightly build version, use
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```bash
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pip install --pre --upgrade bigdl-orca[ray]
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```
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## To use Orca AutoML
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Note that with the extra key of [ray], `pip` will automatically install the additional dependencies for RayOnSpark,
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including `ray[default]==1.9.2`, `aiohttp==3.8.1`, `async-timeout==4.0.1`, `aioredis==1.3.1`, `hiredis==2.0.0`, `prometheus-client==0.11.0`, `psutil`, `setproctitle`.
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There're some additional dependencies required for Orca AutoML support. Use extra key `[automl]` to install.
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## To additionally use AutoML
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If you wish to run AutoML, use the extra key `[automl]` during the installation above:
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```bash
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pip install bigdl-orca[automl]
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````
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or for the nightly build version, use
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```bash
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pip install --pre --upgrade bigdl-orca[automl]
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```
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_Note that with extra key of [automl], `pip` will automatically install the additional dependencies for distributed hyper-parameter tuning,
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including `ray[tune]==1.9.2`, `scikit-learn`, `tensorboard`, `xgboost`._
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Note that with the extra key of [automl], `pip` will automatically install the additional dependencies for distributed hyper-parameter tuning,
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including `ray[tune]==1.9.2`, `scikit-learn`, `tensorboard`, `xgboost` together with the dependencies given by the extra key [ray].
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To use [Pytorch Estimator](#pytorch-autoestimator), you need to install Pytorch with `pip install torch==1.8.1`.
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To use [TensorFlow/Keras AutoEstimator](#tensorflow-keras-autoestimator), you need to install Tensorflow with `pip install tensorflow==1.15.0`.
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- To use [Pytorch Estimator](#pytorch-autoestimator), you need to install Pytorch with `pip install torch==1.8.1`.
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- To use [TensorFlow/Keras AutoEstimator](#tensorflow-keras-autoestimator), you need to install TensorFlow with `pip install tensorflow==1.15.0`.
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@ -6,9 +6,11 @@ Most AI projects start with a Python notebook running on a single laptop; howeve
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---
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### Tensorflow Bite-sized Example
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### TensorFlow Bite-sized Example
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This section uses TensorFlow 1.15, and you should install TensorFlow before running this example:
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First of all, follow the steps [here](install.md#to-use-basic-orca-features) to install Orca in your environment.
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This section uses TensorFlow 1.15, and you should also install TensorFlow before running this example:
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```bash
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pip install tensorflow==1.15
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```
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@ -14,7 +14,7 @@ _**Note:** BigDL has been tested on Ray 1.9.2 and you are highly recommended to
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We recommend using [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/) to prepare the Python environment.
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When installing bigdl-orca with pip, you can specify the extras key `[ray]` to install the additional dependencies
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for running Ray (i.e. `ray==1.9.2`, `psutil`, `aiohttp==3.7.0`, `aioredis==1.1.0`, `setproctitle`, `hiredis==1.1.0`, `async-timeout==3.0.1`):
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for running Ray (i.e. `ray[default]==1.9.2`, `aiohttp==3.8.1`, `async-timeout==4.0.1`, `aioredis==1.3.1`, `hiredis==2.0.0`, `prometheus-client==0.11.0`, `psutil`, `setproctitle`):
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```bash
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conda create -n py37 python=3.7 # "py37" is conda environment name, you can use any name you like.
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# Orca Tutorial
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# Orca Quickstarts
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- [**Orca TensorFlow 1.15 Quickstart**](./orca-tf-quickstart.html)
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6
docs/readthedocs/source/doc/Orca/Tutorial/index.rst
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6
docs/readthedocs/source/doc/Orca/Tutorial/index.rst
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Orca Tutorials
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=================================
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* `Run on Hadoop/YARN clusters <yarn.html>`_
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* `Run on Azure Databricks <../../UserGuide/databricks.html>`_
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* `Run on Google Colab <../../UserGuide/colab.html>`_
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# Running BigDL-Orca on Hadoop/YARN Clusters
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# Run on Hadoop/YARN Clusters
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This tutorial provides a step-by-step guide on how to run BigDL-Orca programs on Apache Hadoop/YARN clusters, using a [PyTorch Fashin-MNIST program](https://github.com/intel-analytics/BigDL/blob/main/python/orca/tutorial/pytorch/FashionMNIST/) as a working example.
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# Use Spark Dataframe for Deep Learning
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# Use Spark DataFrames for Deep Learning
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---
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