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Merged
peytondmurray merged 1 commit into from
Nov 16, 2023
Merged

[Doc] Refactor tab widgets #9

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85 changes: 53 additions & 32 deletions doc/source/cluster/vms/getting-started.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -29,43 +29,50 @@ Setup

Before we start, you will need to install some Python dependencies as follows:

.. tabs::
.. tab-set::

.. tab:: Ray Team Supported
.. tab-item:: Ray Team Supported
:sync: Ray Team Supported

.. tabs::
.. tab-set::

.. tab:: AWS
.. tab-item:: AWS
:sync: AWS

.. code-block:: shell

$ pip install -U "ray[default]" boto3

.. tab:: GCP
.. tab-item:: GCP
:sync: GCP

.. code-block:: shell

$ pip install -U "ray[default]" google-api-python-client

.. tab:: Community Supported
.. tab-item:: Community Supported
:sync: Community Supported

.. tabs::
.. tab-set::

.. tab:: Azure
.. tab-item:: Azure
:sync: Azure

.. code-block:: shell

$ pip install -U "ray[default]" azure-cli azure-core

.. tab:: Aliyun
.. tab-item:: Aliyun
:sync: Aliyun

.. code-block:: shell

$ pip install -U "ray[default]" aliyun-python-sdk-core aliyun-python-sdk-ecs

Aliyun Cluster Launcher Maintainers (GitHub handles): @zhuangzhuang131419, @chenk008

.. tab:: vSphere
.. tab-item:: vSphere
:sync: vSphere

.. code-block:: shell

Expand All @@ -76,36 +83,43 @@ Before we start, you will need to install some Python dependencies as follows:

Next, if you're not set up to use your cloud provider from the command line, you'll have to configure your credentials:

.. tabs::
.. tab-set::

.. tab:: Ray Team Supported
.. tab-item:: Ray Team Supported
:sync: Ray Team Supported

.. tabs::
.. tab-set::

.. tab:: AWS
.. tab-item:: AWS
:sync: AWS

Configure your credentials in ``~/.aws/credentials`` as described in `the AWS docs <https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html>`_.

.. tab:: GCP
.. tab-item:: GCP
:sync: GCP

Set the ``GOOGLE_APPLICATION_CREDENTIALS`` environment variable as described in `the GCP docs <https://cloud.google.com/docs/authentication/getting-started>`_.

.. tab:: Community Supported
.. tab-item:: Community Supported
:sync: Community Supported

.. tabs::
.. tab-set::

.. tab:: Azure
.. tab-item:: Azure
:sync: Azure

Log in using ``az login``, then configure your credentials with ``az account set -s <subscription_id>``.

.. tab:: Aliyun
.. tab-item:: Aliyun
:sync: Aliyun

Obtain and set the AccessKey pair of the Aliyun account as described in `the docs <https://www.alibabacloud.com/help/en/doc-detail/175967.htm>`__.

Make sure to grant the necessary permissions to the RAM user and set the AccessKey pair in your cluster config file.
Refer to the provided `aliyun/example-full.yaml </ray/python/ray/autoscaler/aliyun/example-full.yaml>`__ for a sample cluster config.

.. tab:: vSphere
.. tab-item:: vSphere
:sync: vSphere

.. code-block:: shell

Expand Down Expand Up @@ -205,18 +219,21 @@ To start a Ray Cluster, first we need to define the cluster configuration. The c

A minimal sample cluster configuration file looks as follows:

.. tabs::
.. tab-set::

.. tab:: Ray Team Supported
.. tab-item:: Ray Team Supported
:sync: Ray Team Supported

.. tabs::
.. tab-set::

.. tab:: AWS
.. tab-item:: AWS
:sync: AWS

.. literalinclude:: ../../../../python/ray/autoscaler/aws/example-minimal.yaml
:language: yaml

.. tab:: GCP
.. tab-item:: GCP
:sync: GCP

.. code-block:: yaml

Expand All @@ -228,11 +245,13 @@ A minimal sample cluster configuration file looks as follows:
type: gcp
region: us-west1

.. tab:: Community Supported
.. tab-item:: Community Supported
:sync: Community Supported

.. tabs::
.. tab-set::

.. tab:: Azure
.. tab-item:: Azure
:sync: Azure

.. code-block:: yaml

Expand All @@ -254,13 +273,15 @@ A minimal sample cluster configuration file looks as follows:
# changes to this should match what is specified in file_mounts
ssh_public_key: ~/.ssh/id_rsa.pub

.. tab:: Aliyun
.. tab-item:: Aliyun
:sync: Aliyun

Please refer to `example-full.yaml </ray/python/ray/autoscaler/aliyun/example-full.yaml>`__.
Please refer to `example-full.yaml </ray/python/ray/autoscaler/aliyun/example-full.yaml>`__.

Make sure your account balance is not less than 100 RMB, otherwise you will receive the error `InvalidAccountStatus.NotEnoughBalance`.

.. tab:: vSphere
.. tab-item:: vSphere
:sync: vSphere

.. literalinclude:: ../../../../python/ray/autoscaler/vsphere/example-minimal.yaml
:language: yaml
Expand Down
32 changes: 19 additions & 13 deletions doc/source/data/batch_inference.rst
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Expand Up @@ -34,9 +34,10 @@ Using Ray Data for offline inference involves four basic steps:
For more in-depth examples for your use case, see :ref:`the batch inference examples<batch_inference_examples>`.
For how to configure batch inference, see :ref:`the configuration guide<batch_inference_configuration>`.

.. tabs::
.. tab-set::

.. group-tab:: HuggingFace
.. tab-item:: HuggingFace
:sync: HuggingFace

.. testcode::

Expand Down Expand Up @@ -84,7 +85,8 @@ For how to configure batch inference, see :ref:`the configuration guide<batch_in
{'data': 'Complete this', 'output': 'Complete this information or purchase any item from this site.\n\nAll purchases are final and non-'}


.. group-tab:: PyTorch
.. tab-item:: PyTorch
:sync: PyTorch

.. testcode::

Expand Down Expand Up @@ -133,7 +135,8 @@ For how to configure batch inference, see :ref:`the configuration guide<batch_in

{'output': array([0.5590901], dtype=float32)}

.. group-tab:: TensorFlow
.. tab-item:: TensorFlow
:sync: TensorFlow

.. testcode::

Expand Down Expand Up @@ -204,9 +207,10 @@ To use GPUs for inference, make the following changes to your code:

The remaining is the same as the :ref:`Quickstart <batch_inference_quickstart>`.

.. tabs::
.. tab-set::

.. group-tab:: HuggingFace
.. tab-item:: HuggingFace
:sync: HuggingFace

.. testcode::

Expand Down Expand Up @@ -246,7 +250,8 @@ The remaining is the same as the :ref:`Quickstart <batch_inference_quickstart>`.
{'data': 'Complete this', 'output': 'Complete this poll. Which one do you think holds the most promise for you?\n\nThank you'}


.. group-tab:: PyTorch
.. tab-item:: PyTorch
:sync: PyTorch

.. testcode::

Expand Down Expand Up @@ -292,7 +297,8 @@ The remaining is the same as the :ref:`Quickstart <batch_inference_quickstart>`.

{'output': array([0.5590901], dtype=float32)}

.. group-tab:: TensorFlow
.. tab-item:: TensorFlow
:sync: TensorFlow

.. testcode::

Expand Down Expand Up @@ -471,7 +477,7 @@ In this case, use :meth:`XGBoostTrainer.get_model() <ray.train.xgboost.XGBoostTr
The rest of the logic looks the same as in the `Quickstart <#quickstart>`_.

.. testcode::

from typing import Dict
import pandas as pd
import numpy as np
Expand All @@ -485,18 +491,18 @@ The rest of the logic looks the same as in the `Quickstart <#quickstart>`_.
class XGBoostPredictor:
def __init__(self, checkpoint: Checkpoint):
self.model = XGBoostTrainer.get_model(checkpoint)

def __call__(self, data: pd.DataFrame) -> Dict[str, np.ndarray]:
dmatrix = xgboost.DMatrix(data)
return {"predictions": self.model.predict(dmatrix)}


# Use 2 parallel actors for inference. Each actor predicts on a
# different partition of data.
scale = ray.data.ActorPoolStrategy(size=2)
# Map the Predictor over the Dataset to get predictions.
predictions = test_dataset.map_batches(
XGBoostPredictor,
XGBoostPredictor,
compute=scale,
batch_format="pandas",
# Pass in the Checkpoint to the XGBoostPredictor constructor.
Expand Down
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