Update overview.rst, data_science_job.rst, and 11 more files...

Author: qiuosier

docs/source/user_guide/jobs/components/overview.rst

@@ -23,7 +23,7 @@ For example, you may want to experiment with how different model classes perform
 by using the ADSTuner to perform hyperparameter tuning on each model class.
 You could do this in parallel by having a different job run for each class of models.
 For a given job run, you could pass an environment variable that identifies the model class that you want to use.
-Each model cab write its results to the Logging service or Object Storage.
+Each model can write its results to the Logging service or Object Storage.
 Then you can run a final sequential job that uses the best model class, and trains the final model on the entire dataset.
 
 The following sections provides details on running training workloads with OCI Data Science Jobs using ADS Jobs APIs.

docs/source/user_guide/jobs/data_science_job.rst

@@ -155,4 +155,8 @@ and ``output_uri`` based on the environment variables ``JOB_RUN_OCID``:
 
 Note that ``JOB_RUN_OCID`` is an environment variable provided by the service after the job run is created.
 It is available for the ``output_uri`` but cannot be used in the job name.
-See also :ref:`Saving Outputs <_runtime_outputs>`
+
+See also:
+
+* :ref:`Saving Outputs <runtime_outputs>`
+* `Service Provided Environment Variables <https://docs.oracle.com/en-us/iaas/data-science/using/jobs-env-vars.htm>`_

docs/source/user_guide/jobs/run_container.rst

@@ -1,129 +1,26 @@
 Run a Container
 ***************
 
-The ADS ``ContainerRuntime`` class allows you to run a container image using OCI data science jobs.
+The :py:class:`~ads.jobs.ContainerRuntime` class allows you to run a container image using OCI data science jobs.
 
-To use the ``ContainerRuntime``, you need to first push the image to `OCI container registry <https://docs.oracle.com/en-us/iaas/Content/Registry/Concepts/registryoverview.htm>`_. See `Creating a Repository <https://docs.oracle.com/en-us/iaas/Content/Registry/Tasks/registrycreatingarepository.htm>`_ and `Pushing Images Using the Docker CLI <https://docs.oracle.com/en-us/iaas/Content/Registry/Tasks/registrycreatingarepository.htm>`_ for more details.
+.. admonition:: OCI Container Registry
 
-Python
-======
+  To use the :py:class:`~ads.jobs.ContainerRuntime`, you need to first push the image to
+  `OCI container registry <https://docs.oracle.com/en-us/iaas/Content/Registry/Concepts/registryoverview.htm>`_.
+  For more details, see:
+  
+  * `Creating a Repository <https://docs.oracle.com/en-us/iaas/Content/Registry/Tasks/registrycreatingarepository.htm>`_
+  * `Pushing Images Using the Docker CLI <https://docs.oracle.com/en-us/iaas/Content/Registry/Tasks/registrycreatingarepository.htm>`_.
 
-To configure ``ContainerRuntime``, you must specify the container ``image``. Similar to other runtime, you can add environment variables. You can optionally specify the `entrypoint` and `cmd` for running the container (See `Understand how CMD and ENTRYPOINT interact <https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact>`_).
+Here is an example to create and run a container job:
 
-.. code-block:: python3
+.. include:: ../jobs/tabs/container_runtime.rst
 
-    from ads.jobs import Job, DataScienceJob, ContainerRuntime
+To configure ``ContainerRuntime``, you must specify the container ``image``.
+Similar to other runtime, you can add environment variables.
+You can optionally specify the `entrypoint` and `cmd` for running the container.
 
-    job = (
-        Job()
-        .with_infrastructure(
-            DataScienceJob()
-            .with_log_group_id("<log_group_ocid>")
-            .with_log_id("<log_ocid>")
-            # The following infrastructure configurations are optional
-            # if you are in an OCI data science notebook session.
-            # The configurations of the notebook session will be used as defaults
-            .with_compartment_id("<compartment_ocid>")
-            .with_project_id("<project_ocid>")
-            .with_subnet_id("<subnet_ocid>")
-            .with_shape_name("VM.Standard.E3.Flex")
-            .with_shape_config_details(memory_in_gbs=16, ocpus=1) # Applicable only for the flexible shapes
-            .with_block_storage_size(50)
-        )
-        .with_runtime(
-            ContainerRuntime()
-            .with_image("<region>.ocir.io/<your_tenancy>/<your_image>")
-            .with_environment_variable(GREETINGS="Welcome to OCI Data Science")
-            .with_entrypoint(["/bin/sh", "-c"])
-            .with_cmd("sleep 5 && echo $GREETINGS")
-        )
-    )
-
-    # Create the job with OCI
-    job.create()
-    # Run the job and stream the outputs
-    job_run = job.run().watch()
-
-YAML
-====
-
-You could use the following YAML to create the same job:
-
-.. code-block:: yaml
-
-    kind: job
-    spec:
-      name: container-job
-      infrastructure:
-        kind: infrastructure
-        type: dataScienceJob
-        spec:
-          logGroupId: <log_group_ocid>
-          logId: <log_ocid>
-          compartmentId: <compartment_ocid>
-          projectId: <project_ocid>
-          subnetId: <subnet_ocid>
-          shapeName: VM.Standard.E3.Flex
-          shapeConfigDetails:
-            memoryInGBs: 16
-            ocpus: 1
-          blockStorageSize: 50
-      runtime:
-        kind: runtime
-        type: container
-        spec:
-          image: iad.ocir.io/<your_tenancy>/<your_image>
-          cmd:
-          - sleep 5 && echo $GREETINGS
-          entrypoint:
-          - /bin/sh
-          - -c
-          env:
-          - name: GREETINGS
-            value: Welcome to OCI Data Science
-
-**ContainerRuntime Schema**
-
-.. code-block:: yaml
-
-    kind:
-      required: true
-      type: string
-      allowed:
-        - runtime
-    type:
-      required: true
-      type: string
-      allowed:
-        - container
-    spec:
-      type: dict
-      required: true
-      schema:
-        image:
-          required: true
-          type: string
-        entrypoint:
-          required: false
-          type:
-          - string
-          - list
-        cmd:
-          required: false
-          type:
-          - string
-          - list
-        env:
-          nullable: true
-          required: false
-          type: list
-          schema:
-            type: dict
-            schema:
-              name:
-                type: string
-              value:
-                type:
-                - number
-                - string
+See also:
 
+* `Understand how CMD and ENTRYPOINT interact <https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact>`_
+* `Bring Your Own Container <https://docs.oracle.com/en-us/iaas/data-science/using/jobs-byoc.htm>`_