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| <div class="section" id="google-cloud-vertexai-operators"> |
| <h1>Google Cloud VertexAI Operators<a class="headerlink" href="#google-cloud-vertexai-operators" title="Permalink to this heading">¶</a></h1> |
| <p>The <a class="reference external" href="https://cloud.google.com/vertex-ai/docs">Google Cloud VertexAI</a> |
| brings AutoML and AI Platform together into a unified API, client library, and user |
| interface. AutoML lets you train models on image, tabular, text, and video datasets |
| without writing code, while training in AI Platform lets you run custom training code. |
| With Vertex AI, both AutoML training and custom training are available options. |
| Whichever option you choose for training, you can save models, deploy models, and |
| request predictions with Vertex AI.</p> |
| <div class="section" id="creating-datasets"> |
| <h2>Creating Datasets<a class="headerlink" href="#creating-datasets" title="Permalink to this heading">¶</a></h2> |
| <p>To create a Google VertexAI dataset you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/dataset/index.html#airflow.providers.google.cloud.operators.vertex_ai.dataset.CreateDatasetOperator" title="airflow.providers.google.cloud.operators.vertex_ai.dataset.CreateDatasetOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateDatasetOperator</span></code></a>. |
| The operator returns dataset id in <a class="reference external" href="/docs/apache-airflow/stable/concepts/xcoms.html#concepts-xcom" title="(in apache-airflow v2.4.0.dev0)"><span class="xref std std-ref">XCom</span></a> under <code class="docutils literal notranslate"><span class="pre">dataset_id</span></code> key.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_image_dataset_job</span> <span class="o">=</span> <span class="n">CreateDatasetOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"image_dataset"</span><span class="p">,</span> |
| <span class="n">dataset</span><span class="o">=</span><span class="n">IMAGE_DATASET</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| <span class="n">create_tabular_dataset_job</span> <span class="o">=</span> <span class="n">CreateDatasetOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"tabular_dataset"</span><span class="p">,</span> |
| <span class="n">dataset</span><span class="o">=</span><span class="n">TABULAR_DATASET</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| <span class="n">create_text_dataset_job</span> <span class="o">=</span> <span class="n">CreateDatasetOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"text_dataset"</span><span class="p">,</span> |
| <span class="n">dataset</span><span class="o">=</span><span class="n">TEXT_DATASET</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| <span class="n">create_video_dataset_job</span> <span class="o">=</span> <span class="n">CreateDatasetOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"video_dataset"</span><span class="p">,</span> |
| <span class="n">dataset</span><span class="o">=</span><span class="n">VIDEO_DATASET</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| <span class="n">create_time_series_dataset_job</span> <span class="o">=</span> <span class="n">CreateDatasetOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"time_series_dataset"</span><span class="p">,</span> |
| <span class="n">dataset</span><span class="o">=</span><span class="n">TIME_SERIES_DATASET</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>After creating a dataset you can use it to import some data using |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/dataset/index.html#airflow.providers.google.cloud.operators.vertex_ai.dataset.ImportDataOperator" title="airflow.providers.google.cloud.operators.vertex_ai.dataset.ImportDataOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ImportDataOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">import_data_job</span> <span class="o">=</span> <span class="n">ImportDataOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"import_data"</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">create_image_dataset_job</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'dataset_id'</span><span class="p">],</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">import_configs</span><span class="o">=</span><span class="n">TEST_IMPORT_CONFIG</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To export dataset you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/dataset/index.html#airflow.providers.google.cloud.operators.vertex_ai.dataset.ExportDataOperator" title="airflow.providers.google.cloud.operators.vertex_ai.dataset.ExportDataOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ExportDataOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">export_data_job</span> <span class="o">=</span> <span class="n">ExportDataOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"export_data"</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">create_image_dataset_job</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'dataset_id'</span><span class="p">],</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">export_config</span><span class="o">=</span><span class="n">TEST_EXPORT_CONFIG</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To delete dataset you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/dataset/index.html#airflow.providers.google.cloud.operators.vertex_ai.dataset.DeleteDatasetOperator" title="airflow.providers.google.cloud.operators.vertex_ai.dataset.DeleteDatasetOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DeleteDatasetOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">delete_dataset_job</span> <span class="o">=</span> <span class="n">DeleteDatasetOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"delete_dataset"</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">create_text_dataset_job</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'dataset_id'</span><span class="p">],</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To get dataset you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/dataset/index.html#airflow.providers.google.cloud.operators.vertex_ai.dataset.GetDatasetOperator" title="airflow.providers.google.cloud.operators.vertex_ai.dataset.GetDatasetOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">GetDatasetOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">get_dataset</span> <span class="o">=</span> <span class="n">GetDatasetOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"get_dataset"</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">create_tabular_dataset_job</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'dataset_id'</span><span class="p">],</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To get a dataset list you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/dataset/index.html#airflow.providers.google.cloud.operators.vertex_ai.dataset.ListDatasetsOperator" title="airflow.providers.google.cloud.operators.vertex_ai.dataset.ListDatasetsOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ListDatasetsOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">list_dataset_job</span> <span class="o">=</span> <span class="n">ListDatasetsOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"list_dataset"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To update dataset you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/dataset/index.html#airflow.providers.google.cloud.operators.vertex_ai.dataset.UpdateDatasetOperator" title="airflow.providers.google.cloud.operators.vertex_ai.dataset.UpdateDatasetOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">UpdateDatasetOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">update_dataset_job</span> <span class="o">=</span> <span class="n">UpdateDatasetOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"update_dataset"</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">create_video_dataset_job</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'dataset_id'</span><span class="p">],</span> |
| <span class="n">dataset</span><span class="o">=</span><span class="n">DATASET_TO_UPDATE</span><span class="p">,</span> |
| <span class="n">update_mask</span><span class="o">=</span><span class="n">TEST_UPDATE_MASK</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="creating-a-training-jobs"> |
| <h2>Creating a Training Jobs<a class="headerlink" href="#creating-a-training-jobs" title="Permalink to this heading">¶</a></h2> |
| <p>To create a Google Vertex AI training jobs you have three operators |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/custom_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomContainerTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomContainerTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateCustomContainerTrainingJobOperator</span></code></a>, |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/custom_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateCustomPythonPackageTrainingJobOperator</span></code></a>, |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/custom_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateCustomTrainingJobOperator</span></code></a>. |
| Each of them will wait for the operation to complete. The results of each operator will be a model |
| which was trained by user using these operators.</p> |
| <p>Preparation step</p> |
| <p>For each operator you must prepare and create dataset. Then put dataset id to <code class="docutils literal notranslate"><span class="pre">dataset_id</span></code> parameter in operator.</p> |
| <p>How to run Container Training Job |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/custom_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomContainerTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomContainerTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateCustomContainerTrainingJobOperator</span></code></a></p> |
| <p>Before start running this Job you should create a docker image with training script inside. Documentation how to |
| create image you can find by this link: <a class="reference external" href="https://cloud.google.com/vertex-ai/docs/training/create-custom-container">https://cloud.google.com/vertex-ai/docs/training/create-custom-container</a> |
| After that you should put link to the image in <code class="docutils literal notranslate"><span class="pre">container_uri</span></code> parameter. Also you can type executing command |
| for container which will be created from this image in <code class="docutils literal notranslate"><span class="pre">command</span></code> parameter.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_custom_container_training_job</span> <span class="o">=</span> <span class="n">CreateCustomContainerTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"custom_container_task"</span><span class="p">,</span> |
| <span class="n">staging_bucket</span><span class="o">=</span><span class="n">STAGING_BUCKET</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"train-housing-container-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">container_uri</span><span class="o">=</span><span class="n">CUSTOM_CONTAINER_URI</span><span class="p">,</span> |
| <span class="n">model_serving_container_image_uri</span><span class="o">=</span><span class="n">MODEL_SERVING_CONTAINER_URI</span><span class="p">,</span> |
| <span class="c1"># run params</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">DATASET_ID</span><span class="p">,</span> |
| <span class="n">command</span><span class="o">=</span><span class="p">[</span><span class="s2">"python3"</span><span class="p">,</span> <span class="s2">"task.py"</span><span class="p">],</span> |
| <span class="n">model_display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"container-housing-model-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">replica_count</span><span class="o">=</span><span class="n">REPLICA_COUNT</span><span class="p">,</span> |
| <span class="n">machine_type</span><span class="o">=</span><span class="n">MACHINE_TYPE</span><span class="p">,</span> |
| <span class="n">accelerator_type</span><span class="o">=</span><span class="n">ACCELERATOR_TYPE</span><span class="p">,</span> |
| <span class="n">accelerator_count</span><span class="o">=</span><span class="n">ACCELERATOR_COUNT</span><span class="p">,</span> |
| <span class="n">training_fraction_split</span><span class="o">=</span><span class="n">TRAINING_FRACTION_SPLIT</span><span class="p">,</span> |
| <span class="n">validation_fraction_split</span><span class="o">=</span><span class="n">VALIDATION_FRACTION_SPLIT</span><span class="p">,</span> |
| <span class="n">test_fraction_split</span><span class="o">=</span><span class="n">TEST_FRACTION_SPLIT</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>How to run Python Package Training Job |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/custom_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomPythonPackageTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateCustomPythonPackageTrainingJobOperator</span></code></a></p> |
| <p>Before start running this Job you should create a python package with training script inside. Documentation how to |
| create you can find by this link: <a class="reference external" href="https://cloud.google.com/vertex-ai/docs/training/create-python-pre-built-container">https://cloud.google.com/vertex-ai/docs/training/create-python-pre-built-container</a> |
| Next you should put link to the package in <code class="docutils literal notranslate"><span class="pre">python_package_gcs_uri</span></code> parameter, also <code class="docutils literal notranslate"><span class="pre">python_module_name</span></code> |
| parameter should has the name of script which will run your training task.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_custom_python_package_training_job</span> <span class="o">=</span> <span class="n">CreateCustomPythonPackageTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"python_package_task"</span><span class="p">,</span> |
| <span class="n">staging_bucket</span><span class="o">=</span><span class="n">STAGING_BUCKET</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"train-housing-py-package-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">python_package_gcs_uri</span><span class="o">=</span><span class="n">PYTHON_PACKAGE_GCS_URI</span><span class="p">,</span> |
| <span class="n">python_module_name</span><span class="o">=</span><span class="n">PYTHON_MODULE_NAME</span><span class="p">,</span> |
| <span class="n">container_uri</span><span class="o">=</span><span class="n">CONTAINER_URI</span><span class="p">,</span> |
| <span class="n">model_serving_container_image_uri</span><span class="o">=</span><span class="n">MODEL_SERVING_CONTAINER_URI</span><span class="p">,</span> |
| <span class="c1"># run params</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">DATASET_ID</span><span class="p">,</span> |
| <span class="n">model_display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"py-package-housing-model-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">replica_count</span><span class="o">=</span><span class="n">REPLICA_COUNT</span><span class="p">,</span> |
| <span class="n">machine_type</span><span class="o">=</span><span class="n">MACHINE_TYPE</span><span class="p">,</span> |
| <span class="n">accelerator_type</span><span class="o">=</span><span class="n">ACCELERATOR_TYPE</span><span class="p">,</span> |
| <span class="n">accelerator_count</span><span class="o">=</span><span class="n">ACCELERATOR_COUNT</span><span class="p">,</span> |
| <span class="n">training_fraction_split</span><span class="o">=</span><span class="n">TRAINING_FRACTION_SPLIT</span><span class="p">,</span> |
| <span class="n">validation_fraction_split</span><span class="o">=</span><span class="n">VALIDATION_FRACTION_SPLIT</span><span class="p">,</span> |
| <span class="n">test_fraction_split</span><span class="o">=</span><span class="n">TEST_FRACTION_SPLIT</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>How to run Training Job |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/custom_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.custom_job.CreateCustomTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateCustomTrainingJobOperator</span></code></a>.</p> |
| <p>For this Job you should put path to your local training script inside <code class="docutils literal notranslate"><span class="pre">script_path</span></code> parameter.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_custom_training_job</span> <span class="o">=</span> <span class="n">CreateCustomTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"custom_task"</span><span class="p">,</span> |
| <span class="n">staging_bucket</span><span class="o">=</span><span class="n">STAGING_BUCKET</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"train-housing-custom-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">script_path</span><span class="o">=</span><span class="n">LOCAL_TRAINING_SCRIPT_PATH</span><span class="p">,</span> |
| <span class="n">container_uri</span><span class="o">=</span><span class="n">CONTAINER_URI</span><span class="p">,</span> |
| <span class="n">requirements</span><span class="o">=</span><span class="p">[</span><span class="s2">"gcsfs==0.7.1"</span><span class="p">],</span> |
| <span class="n">model_serving_container_image_uri</span><span class="o">=</span><span class="n">MODEL_SERVING_CONTAINER_URI</span><span class="p">,</span> |
| <span class="c1"># run params</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">DATASET_ID</span><span class="p">,</span> |
| <span class="n">replica_count</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> |
| <span class="n">model_display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"custom-housing-model-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">sync</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>You can get a list of Training Jobs using |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/custom_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.custom_job.ListCustomTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.custom_job.ListCustomTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ListCustomTrainingJobOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">list_custom_training_job</span> <span class="o">=</span> <span class="n">ListCustomTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"list_custom_training_job"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>If you wish to delete a Custom Training Job you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/custom_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.custom_job.DeleteCustomTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.custom_job.DeleteCustomTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DeleteCustomTrainingJobOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">delete_custom_training_job</span> <span class="o">=</span> <span class="n">DeleteCustomTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"delete_custom_training_job"</span><span class="p">,</span> |
| <span class="n">training_pipeline_id</span><span class="o">=</span><span class="n">TRAINING_PIPELINE_ID</span><span class="p">,</span> |
| <span class="n">custom_job_id</span><span class="o">=</span><span class="n">CUSTOM_JOB_ID</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="creating-an-automl-training-jobs"> |
| <h2>Creating an AutoML Training Jobs<a class="headerlink" href="#creating-an-automl-training-jobs" title="Permalink to this heading">¶</a></h2> |
| <p>To create a Google Vertex AI Auto ML training jobs you have five operators |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLForecastingTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLForecastingTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLForecastingTrainingJobOperator</span></code></a> |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLImageTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLImageTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLImageTrainingJobOperator</span></code></a> |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTabularTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTabularTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLTabularTrainingJobOperator</span></code></a> |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTextTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTextTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLTextTrainingJobOperator</span></code></a> |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLVideoTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLVideoTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLVideoTrainingJobOperator</span></code></a> |
| Each of them will wait for the operation to complete. The results of each operator will be a model |
| which was trained by user using these operators.</p> |
| <p>How to run AutoML Forecasting Training Job |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLForecastingTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLForecastingTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLForecastingTrainingJobOperator</span></code></a></p> |
| <p>Before start running this Job you must prepare and create <code class="docutils literal notranslate"><span class="pre">TimeSeries</span></code> dataset. After that you should |
| put dataset id to <code class="docutils literal notranslate"><span class="pre">dataset_id</span></code> parameter in operator.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_auto_ml_forecasting_training_job</span> <span class="o">=</span> <span class="n">CreateAutoMLForecastingTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"auto_ml_forecasting_task"</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-forecasting-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">optimization_objective</span><span class="o">=</span><span class="s2">"minimize-rmse"</span><span class="p">,</span> |
| <span class="n">column_specs</span><span class="o">=</span><span class="n">COLUMN_SPECS</span><span class="p">,</span> |
| <span class="c1"># run params</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">DATASET_ID</span><span class="p">,</span> |
| <span class="n">target_column</span><span class="o">=</span><span class="n">TEST_TARGET_COLUMN</span><span class="p">,</span> |
| <span class="n">time_column</span><span class="o">=</span><span class="n">TEST_TIME_COLUMN</span><span class="p">,</span> |
| <span class="n">time_series_identifier_column</span><span class="o">=</span><span class="n">TEST_TIME_SERIES_IDENTIFIER_COLUMN</span><span class="p">,</span> |
| <span class="n">available_at_forecast_columns</span><span class="o">=</span><span class="p">[</span><span class="n">TEST_TIME_COLUMN</span><span class="p">],</span> |
| <span class="n">unavailable_at_forecast_columns</span><span class="o">=</span><span class="p">[</span><span class="n">TEST_TARGET_COLUMN</span><span class="p">],</span> |
| <span class="n">time_series_attribute_columns</span><span class="o">=</span><span class="p">[</span><span class="s2">"city"</span><span class="p">,</span> <span class="s2">"zip_code"</span><span class="p">,</span> <span class="s2">"county"</span><span class="p">],</span> |
| <span class="n">forecast_horizon</span><span class="o">=</span><span class="mi">30</span><span class="p">,</span> |
| <span class="n">context_window</span><span class="o">=</span><span class="mi">30</span><span class="p">,</span> |
| <span class="n">data_granularity_unit</span><span class="o">=</span><span class="s2">"day"</span><span class="p">,</span> |
| <span class="n">data_granularity_count</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> |
| <span class="n">weight_column</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> |
| <span class="n">budget_milli_node_hours</span><span class="o">=</span><span class="mi">1000</span><span class="p">,</span> |
| <span class="n">model_display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-forecasting-model-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">predefined_split_column_name</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>How to run AutoML Image Training Job |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLImageTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLImageTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLImageTrainingJobOperator</span></code></a></p> |
| <p>Before start running this Job you must prepare and create <code class="docutils literal notranslate"><span class="pre">Image</span></code> dataset. After that you should |
| put dataset id to <code class="docutils literal notranslate"><span class="pre">dataset_id</span></code> parameter in operator.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_auto_ml_image_training_job</span> <span class="o">=</span> <span class="n">CreateAutoMLImageTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"auto_ml_image_task"</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-image-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">DATASET_ID</span><span class="p">,</span> |
| <span class="n">prediction_type</span><span class="o">=</span><span class="s2">"classification"</span><span class="p">,</span> |
| <span class="n">multi_label</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> |
| <span class="n">model_type</span><span class="o">=</span><span class="s2">"CLOUD"</span><span class="p">,</span> |
| <span class="n">training_fraction_split</span><span class="o">=</span><span class="mf">0.6</span><span class="p">,</span> |
| <span class="n">validation_fraction_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> |
| <span class="n">test_fraction_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> |
| <span class="n">budget_milli_node_hours</span><span class="o">=</span><span class="mi">8000</span><span class="p">,</span> |
| <span class="n">model_display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-image-model-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">disable_early_stopping</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>How to run AutoML Tabular Training Job |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTabularTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTabularTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLTabularTrainingJobOperator</span></code></a></p> |
| <p>Before start running this Job you must prepare and create <code class="docutils literal notranslate"><span class="pre">Tabular</span></code> dataset. After that you should |
| put dataset id to <code class="docutils literal notranslate"><span class="pre">dataset_id</span></code> parameter in operator.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_auto_ml_tabular_training_job</span> <span class="o">=</span> <span class="n">CreateAutoMLTabularTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"auto_ml_tabular_task"</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-tabular-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">optimization_prediction_type</span><span class="o">=</span><span class="s2">"classification"</span><span class="p">,</span> |
| <span class="n">column_transformations</span><span class="o">=</span><span class="n">COLUMN_TRANSFORMATIONS</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">DATASET_ID</span><span class="p">,</span> |
| <span class="n">target_column</span><span class="o">=</span><span class="s2">"Adopted"</span><span class="p">,</span> |
| <span class="n">training_fraction_split</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> |
| <span class="n">validation_fraction_split</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> |
| <span class="n">test_fraction_split</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> |
| <span class="n">model_display_name</span><span class="o">=</span><span class="s2">"adopted-prediction-model"</span><span class="p">,</span> |
| <span class="n">disable_early_stopping</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>How to run AutoML Text Training Job |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTextTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLTextTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLTextTrainingJobOperator</span></code></a></p> |
| <p>Before start running this Job you must prepare and create <code class="docutils literal notranslate"><span class="pre">Text</span></code> dataset. After that you should |
| put dataset id to <code class="docutils literal notranslate"><span class="pre">dataset_id</span></code> parameter in operator.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_auto_ml_text_training_job</span> <span class="o">=</span> <span class="n">CreateAutoMLTextTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"auto_ml_text_task"</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-text-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">prediction_type</span><span class="o">=</span><span class="s2">"classification"</span><span class="p">,</span> |
| <span class="n">multi_label</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">DATASET_ID</span><span class="p">,</span> |
| <span class="n">model_display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-text-model-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">training_fraction_split</span><span class="o">=</span><span class="mf">0.7</span><span class="p">,</span> |
| <span class="n">validation_fraction_split</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> |
| <span class="n">test_fraction_split</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> |
| <span class="n">sync</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>How to run AutoML Video Training Job |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLVideoTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.CreateAutoMLVideoTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateAutoMLVideoTrainingJobOperator</span></code></a></p> |
| <p>Before start running this Job you must prepare and create <code class="docutils literal notranslate"><span class="pre">Video</span></code> dataset. After that you should |
| put dataset id to <code class="docutils literal notranslate"><span class="pre">dataset_id</span></code> parameter in operator.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_auto_ml_video_training_job</span> <span class="o">=</span> <span class="n">CreateAutoMLVideoTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"auto_ml_video_task"</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-video-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">prediction_type</span><span class="o">=</span><span class="s2">"classification"</span><span class="p">,</span> |
| <span class="n">model_type</span><span class="o">=</span><span class="s2">"CLOUD"</span><span class="p">,</span> |
| <span class="n">dataset_id</span><span class="o">=</span><span class="n">DATASET_ID</span><span class="p">,</span> |
| <span class="n">model_display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"auto-ml-video-model-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>You can get a list of AutoML Training Jobs using |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.ListAutoMLTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.ListAutoMLTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ListAutoMLTrainingJobOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">list_auto_ml_training_job</span> <span class="o">=</span> <span class="n">ListAutoMLTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"list_auto_ml_training_job"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>If you wish to delete a Auto ML Training Job you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/auto_ml/index.html#airflow.providers.google.cloud.operators.vertex_ai.auto_ml.DeleteAutoMLTrainingJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.auto_ml.DeleteAutoMLTrainingJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DeleteAutoMLTrainingJobOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">delete_auto_ml_training_job</span> <span class="o">=</span> <span class="n">DeleteAutoMLTrainingJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"delete_auto_ml_training_job"</span><span class="p">,</span> |
| <span class="n">training_pipeline_id</span><span class="o">=</span><span class="n">TRAINING_PIPELINE_ID</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="creating-a-batch-prediction-jobs"> |
| <h2>Creating a Batch Prediction Jobs<a class="headerlink" href="#creating-a-batch-prediction-jobs" title="Permalink to this heading">¶</a></h2> |
| <p>To create a Google VertexAI Batch Prediction Job you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/batch_prediction_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.batch_prediction_job.CreateBatchPredictionJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.batch_prediction_job.CreateBatchPredictionJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateBatchPredictionJobOperator</span></code></a>. |
| The operator returns batch prediction job id in <a class="reference external" href="/docs/apache-airflow/stable/concepts/xcoms.html#concepts-xcom" title="(in apache-airflow v2.4.0.dev0)"><span class="xref std std-ref">XCom</span></a> under <code class="docutils literal notranslate"><span class="pre">batch_prediction_job_id</span></code> key.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_batch_prediction_job</span> <span class="o">=</span> <span class="n">CreateBatchPredictionJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"create_batch_prediction_job"</span><span class="p">,</span> |
| <span class="n">job_display_name</span><span class="o">=</span><span class="n">JOB_DISPLAY_NAME</span><span class="p">,</span> |
| <span class="n">model_name</span><span class="o">=</span><span class="n">MODEL_NAME</span><span class="p">,</span> |
| <span class="n">predictions_format</span><span class="o">=</span><span class="s2">"csv"</span><span class="p">,</span> |
| <span class="n">bigquery_source</span><span class="o">=</span><span class="n">BIGQUERY_SOURCE</span><span class="p">,</span> |
| <span class="n">gcs_destination_prefix</span><span class="o">=</span><span class="n">GCS_DESTINATION_PREFIX</span><span class="p">,</span> |
| <span class="n">model_parameters</span><span class="o">=</span><span class="n">MODEL_PARAMETERS</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To delete batch prediction job you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/batch_prediction_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.batch_prediction_job.DeleteBatchPredictionJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.batch_prediction_job.DeleteBatchPredictionJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DeleteBatchPredictionJobOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">delete_batch_prediction_job</span> <span class="o">=</span> <span class="n">DeleteBatchPredictionJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"delete_batch_prediction_job"</span><span class="p">,</span> |
| <span class="n">batch_prediction_job_id</span><span class="o">=</span><span class="n">create_batch_prediction_job</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'batch_prediction_job_id'</span><span class="p">],</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To get a batch prediction job list you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/batch_prediction_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.batch_prediction_job.ListBatchPredictionJobsOperator" title="airflow.providers.google.cloud.operators.vertex_ai.batch_prediction_job.ListBatchPredictionJobsOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ListBatchPredictionJobsOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">list_batch_prediction_job</span> <span class="o">=</span> <span class="n">ListBatchPredictionJobsOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"list_batch_prediction_jobs"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="creating-an-endpoint-service"> |
| <h2>Creating an Endpoint Service<a class="headerlink" href="#creating-an-endpoint-service" title="Permalink to this heading">¶</a></h2> |
| <p>To create a Google VertexAI endpoint you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/endpoint_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.CreateEndpointOperator" title="airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.CreateEndpointOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateEndpointOperator</span></code></a>. |
| The operator returns endpoint id in <a class="reference external" href="/docs/apache-airflow/stable/concepts/xcoms.html#concepts-xcom" title="(in apache-airflow v2.4.0.dev0)"><span class="xref std std-ref">XCom</span></a> under <code class="docutils literal notranslate"><span class="pre">endpoint_id</span></code> key.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_endpoint</span> <span class="o">=</span> <span class="n">CreateEndpointOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"create_endpoint"</span><span class="p">,</span> |
| <span class="n">endpoint</span><span class="o">=</span><span class="n">ENDPOINT_CONF</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>After creating an endpoint you can use it to deploy some model using |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/endpoint_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.DeployModelOperator" title="airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.DeployModelOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DeployModelOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">deploy_model</span> <span class="o">=</span> <span class="n">DeployModelOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"deploy_model"</span><span class="p">,</span> |
| <span class="n">endpoint_id</span><span class="o">=</span><span class="n">create_endpoint</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'endpoint_id'</span><span class="p">],</span> |
| <span class="n">deployed_model</span><span class="o">=</span><span class="n">DEPLOYED_MODEL</span><span class="p">,</span> |
| <span class="n">traffic_split</span><span class="o">=</span><span class="p">{</span><span class="s1">'0'</span><span class="p">:</span> <span class="mi">100</span><span class="p">},</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To un deploy model you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/endpoint_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.UndeployModelOperator" title="airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.UndeployModelOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">UndeployModelOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">undeploy_model</span> <span class="o">=</span> <span class="n">UndeployModelOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"undeploy_model"</span><span class="p">,</span> |
| <span class="n">endpoint_id</span><span class="o">=</span><span class="n">create_endpoint</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'endpoint_id'</span><span class="p">],</span> |
| <span class="n">deployed_model_id</span><span class="o">=</span><span class="n">deploy_model</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'deployed_model_id'</span><span class="p">],</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To delete endpoint you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/endpoint_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.DeleteEndpointOperator" title="airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.DeleteEndpointOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DeleteEndpointOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">delete_endpoint</span> <span class="o">=</span> <span class="n">DeleteEndpointOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"delete_endpoint"</span><span class="p">,</span> |
| <span class="n">endpoint_id</span><span class="o">=</span><span class="n">create_endpoint</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s1">'endpoint_id'</span><span class="p">],</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To get an endpoint list you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/endpoint_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.ListEndpointsOperator" title="airflow.providers.google.cloud.operators.vertex_ai.endpoint_service.ListEndpointsOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ListEndpointsOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">list_endpoints</span> <span class="o">=</span> <span class="n">ListEndpointsOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"list_endpoints"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="creating-a-hyperparameter-tuning-jobs"> |
| <h2>Creating a Hyperparameter Tuning Jobs<a class="headerlink" href="#creating-a-hyperparameter-tuning-jobs" title="Permalink to this heading">¶</a></h2> |
| <p>To create a Google VertexAI hyperparameter tuning job you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/hyperparameter_tuning_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job.CreateHyperparameterTuningJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job.CreateHyperparameterTuningJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateHyperparameterTuningJobOperator</span></code></a>. |
| The operator returns hyperparameter tuning job id in <a class="reference external" href="/docs/apache-airflow/stable/concepts/xcoms.html#concepts-xcom" title="(in apache-airflow v2.4.0.dev0)"><span class="xref std std-ref">XCom</span></a> under <code class="docutils literal notranslate"><span class="pre">hyperparameter_tuning_job_id</span></code> key.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">create_hyperparameter_tuning_job</span> <span class="o">=</span> <span class="n">CreateHyperparameterTuningJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"create_hyperparameter_tuning_job"</span><span class="p">,</span> |
| <span class="n">staging_bucket</span><span class="o">=</span><span class="n">STAGING_BUCKET</span><span class="p">,</span> |
| <span class="n">display_name</span><span class="o">=</span><span class="sa">f</span><span class="s2">"horses-humans-hyptertune-</span><span class="si">{</span><span class="n">DISPLAY_NAME</span><span class="si">}</span><span class="s2">"</span><span class="p">,</span> |
| <span class="n">worker_pool_specs</span><span class="o">=</span><span class="p">[</span> |
| <span class="p">{</span> |
| <span class="s2">"machine_spec"</span><span class="p">:</span> <span class="p">{</span> |
| <span class="s2">"machine_type"</span><span class="p">:</span> <span class="n">MACHINE_TYPE</span><span class="p">,</span> |
| <span class="s2">"accelerator_type"</span><span class="p">:</span> <span class="n">ACCELERATOR_TYPE</span><span class="p">,</span> |
| <span class="s2">"accelerator_count"</span><span class="p">:</span> <span class="n">ACCELERATOR_COUNT</span><span class="p">,</span> |
| <span class="p">},</span> |
| <span class="s2">"replica_count"</span><span class="p">:</span> <span class="n">REPLICA_COUNT</span><span class="p">,</span> |
| <span class="s2">"container_spec"</span><span class="p">:</span> <span class="p">{</span> |
| <span class="s2">"image_uri"</span><span class="p">:</span> <span class="sa">f</span><span class="s2">"gcr.io/</span><span class="si">{</span><span class="n">PROJECT_ID</span><span class="si">}</span><span class="s2">/horse-human:hypertune"</span><span class="p">,</span> |
| <span class="p">},</span> |
| <span class="p">}</span> |
| <span class="p">],</span> |
| <span class="n">sync</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">parameter_spec</span><span class="o">=</span><span class="p">{</span> |
| <span class="s1">'learning_rate'</span><span class="p">:</span> <span class="n">aiplatform</span><span class="o">.</span><span class="n">hyperparameter_tuning</span><span class="o">.</span><span class="n">DoubleParameterSpec</span><span class="p">(</span> |
| <span class="nb">min</span><span class="o">=</span><span class="mf">0.01</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="s1">'log'</span> |
| <span class="p">),</span> |
| <span class="s1">'momentum'</span><span class="p">:</span> <span class="n">aiplatform</span><span class="o">.</span><span class="n">hyperparameter_tuning</span><span class="o">.</span><span class="n">DoubleParameterSpec</span><span class="p">(</span><span class="nb">min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">scale</span><span class="o">=</span><span class="s1">'linear'</span><span class="p">),</span> |
| <span class="s1">'num_neurons'</span><span class="p">:</span> <span class="n">aiplatform</span><span class="o">.</span><span class="n">hyperparameter_tuning</span><span class="o">.</span><span class="n">DiscreteParameterSpec</span><span class="p">(</span> |
| <span class="n">values</span><span class="o">=</span><span class="p">[</span><span class="mi">64</span><span class="p">,</span> <span class="mi">128</span><span class="p">,</span> <span class="mi">512</span><span class="p">],</span> <span class="n">scale</span><span class="o">=</span><span class="s1">'linear'</span> |
| <span class="p">),</span> |
| <span class="p">},</span> |
| <span class="n">metric_spec</span><span class="o">=</span><span class="p">{</span> |
| <span class="s1">'accuracy'</span><span class="p">:</span> <span class="s1">'maximize'</span><span class="p">,</span> |
| <span class="p">},</span> |
| <span class="n">max_trial_count</span><span class="o">=</span><span class="mi">15</span><span class="p">,</span> |
| <span class="n">parallel_trial_count</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To delete hyperparameter tuning job you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/hyperparameter_tuning_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job.DeleteHyperparameterTuningJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job.DeleteHyperparameterTuningJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DeleteHyperparameterTuningJobOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">delete_hyperparameter_tuning_job</span> <span class="o">=</span> <span class="n">DeleteHyperparameterTuningJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"delete_hyperparameter_tuning_job"</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">hyperparameter_tuning_job_id</span><span class="o">=</span><span class="n">create_hyperparameter_tuning_job</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s2">"hyperparameter_tuning_job_id"</span><span class="p">],</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To get hyperparameter tuning job you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/hyperparameter_tuning_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job.GetHyperparameterTuningJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job.GetHyperparameterTuningJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">GetHyperparameterTuningJobOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">get_hyperparameter_tuning_job</span> <span class="o">=</span> <span class="n">GetHyperparameterTuningJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"get_hyperparameter_tuning_job"</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">hyperparameter_tuning_job_id</span><span class="o">=</span><span class="n">create_hyperparameter_tuning_job</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s2">"hyperparameter_tuning_job_id"</span><span class="p">],</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To get a hyperparameter tuning job list you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/hyperparameter_tuning_job/index.html#airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job.ListHyperparameterTuningJobOperator" title="airflow.providers.google.cloud.operators.vertex_ai.hyperparameter_tuning_job.ListHyperparameterTuningJobOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ListHyperparameterTuningJobOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">list_hyperparameter_tuning_job</span> <span class="o">=</span> <span class="n">ListHyperparameterTuningJobOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"list_hyperparameter_tuning_job"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="creating-a-model-service"> |
| <h2>Creating a Model Service<a class="headerlink" href="#creating-a-model-service" title="Permalink to this heading">¶</a></h2> |
| <p>To upload a Google VertexAI model you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/model_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.model_service.UploadModelOperator" title="airflow.providers.google.cloud.operators.vertex_ai.model_service.UploadModelOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">UploadModelOperator</span></code></a>. |
| The operator returns model id in <a class="reference external" href="/docs/apache-airflow/stable/concepts/xcoms.html#concepts-xcom" title="(in apache-airflow v2.4.0.dev0)"><span class="xref std std-ref">XCom</span></a> under <code class="docutils literal notranslate"><span class="pre">model_id</span></code> key.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">upload_model</span> <span class="o">=</span> <span class="n">UploadModelOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"upload_model"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">model</span><span class="o">=</span><span class="n">MODEL_OBJ</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To export model you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/model_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.model_service.ExportModelOperator" title="airflow.providers.google.cloud.operators.vertex_ai.model_service.ExportModelOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ExportModelOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">export_model</span> <span class="o">=</span> <span class="n">ExportModelOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"export_model"</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">model_id</span><span class="o">=</span><span class="n">upload_model</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s2">"model_id"</span><span class="p">],</span> |
| <span class="n">output_config</span><span class="o">=</span><span class="n">MODEL_OUTPUT_CONFIG</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To delete model you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/model_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.model_service.DeleteModelOperator" title="airflow.providers.google.cloud.operators.vertex_ai.model_service.DeleteModelOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">DeleteModelOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">delete_model</span> <span class="o">=</span> <span class="n">DeleteModelOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"delete_model"</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">model_id</span><span class="o">=</span><span class="n">upload_model</span><span class="o">.</span><span class="n">output</span><span class="p">[</span><span class="s2">"model_id"</span><span class="p">],</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| <p>To get a model list you can use |
| <a class="reference internal" href="../../_api/airflow/providers/google/cloud/operators/vertex_ai/model_service/index.html#airflow.providers.google.cloud.operators.vertex_ai.model_service.ListModelsOperator" title="airflow.providers.google.cloud.operators.vertex_ai.model_service.ListModelsOperator"><code class="xref py py-class docutils literal notranslate"><span class="pre">ListModelsOperator</span></code></a>.</p> |
| <div class="example-block-wrapper compound"> |
| <p class="example-header example-header--with-button compound-first"><span class="example-title">airflow/providers/google/cloud/example_dags/example_vertex_ai.py</span><a class="example-header-button viewcode-button reference internal" href="../../_modules/airflow/providers/google/cloud/example_dags/example_vertex_ai.html"><span class="viewcode-link">[source]</span></a></p> |
| <div class="compound-last highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">list_models</span> <span class="o">=</span> <span class="n">ListModelsOperator</span><span class="p">(</span> |
| <span class="n">task_id</span><span class="o">=</span><span class="s2">"list_models"</span><span class="p">,</span> |
| <span class="n">region</span><span class="o">=</span><span class="n">REGION</span><span class="p">,</span> |
| <span class="n">project_id</span><span class="o">=</span><span class="n">PROJECT_ID</span><span class="p">,</span> |
| <span class="p">)</span> |
| </pre></div> |
| </div> |
| </div> |
| </div> |
| <div class="section" id="reference"> |
| <h2>Reference<a class="headerlink" href="#reference" title="Permalink to this heading">¶</a></h2> |
| <p>For further information, look at:</p> |
| <ul class="simple"> |
| <li><p><a class="reference external" href="https://googleapis.dev/python/aiplatform/latest/index.html">Client Library Documentation</a></p></li> |
| <li><p><a class="reference external" href="https://cloud.google.com/ai-platform/docs">Product Documentation</a></p></li> |
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