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| <div class="section" id="module-airflow.providers.amazon.aws.operators.sagemaker"> |
| <span id="airflow-providers-amazon-aws-operators-sagemaker"></span><h1><a class="reference internal" href="#module-airflow.providers.amazon.aws.operators.sagemaker" title="airflow.providers.amazon.aws.operators.sagemaker"><code class="xref py py-mod docutils literal notranslate"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker</span></code></a><a class="headerlink" href="#module-airflow.providers.amazon.aws.operators.sagemaker" title="Permalink to this headline">¶</a></h1> |
| <div class="section" id="module-contents"> |
| <h2>Module Contents<a class="headerlink" href="#module-contents" title="Permalink to this headline">¶</a></h2> |
| <div class="section" id="classes"> |
| <h3>Classes<a class="headerlink" href="#classes" title="Permalink to this headline">¶</a></h3> |
| <table class="autosummary longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p></td> |
| <td><p>This is the base operator for all SageMaker operators.</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerProcessingOperator</span></code></a></p></td> |
| <td><p>Use Amazon SageMaker Processing to analyze data and evaluate machine learning</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerEndpointConfigOperator</span></code></a></p></td> |
| <td><p>Creates an endpoint configuration that Amazon SageMaker hosting</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerEndpointOperator</span></code></a></p></td> |
| <td><p>When you create a serverless endpoint, SageMaker provisions and manages</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerTransformOperator</span></code></a></p></td> |
| <td><p>Starts a transform job. A transform job uses a trained model to get inferences</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerTuningOperator</span></code></a></p></td> |
| <td><p>Starts a hyperparameter tuning job. A hyperparameter tuning job finds the</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerModelOperator</span></code></a></p></td> |
| <td><p>Creates a model in Amazon SageMaker. In the request, you name the model and</p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerTrainingOperator</span></code></a></p></td> |
| <td><p>Starts a model training job. After training completes, Amazon SageMaker saves</p></td> |
| </tr> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerDeleteModelOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerDeleteModelOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerDeleteModelOperator</span></code></a></p></td> |
| <td><p>Deletes a SageMaker model.</p></td> |
| </tr> |
| </tbody> |
| </table> |
| </div> |
| <div class="section" id="attributes"> |
| <h3>Attributes<a class="headerlink" href="#attributes" title="Permalink to this headline">¶</a></h3> |
| <table class="autosummary longtable docutils align-default"> |
| <colgroup> |
| <col style="width: 10%" /> |
| <col style="width: 90%" /> |
| </colgroup> |
| <tbody> |
| <tr class="row-odd"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.DEFAULT_CONN_ID" title="airflow.providers.amazon.aws.operators.sagemaker.DEFAULT_CONN_ID"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DEFAULT_CONN_ID</span></code></a></p></td> |
| <td><p></p></td> |
| </tr> |
| <tr class="row-even"><td><p><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.CHECK_INTERVAL_SECOND" title="airflow.providers.amazon.aws.operators.sagemaker.CHECK_INTERVAL_SECOND"><code class="xref py py-obj docutils literal notranslate"><span class="pre">CHECK_INTERVAL_SECOND</span></code></a></p></td> |
| <td><p></p></td> |
| </tr> |
| </tbody> |
| </table> |
| <dl class="py data"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.DEFAULT_CONN_ID"> |
| <span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">DEFAULT_CONN_ID</span></span><em class="property"><span class="w"> </span><span class="pre">=</span> <span class="pre">aws_default</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#DEFAULT_CONN_ID"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.DEFAULT_CONN_ID" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py data"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.CHECK_INTERVAL_SECOND"> |
| <span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">CHECK_INTERVAL_SECOND</span></span><em class="property"><span class="w"> </span><span class="pre">=</span> <span class="pre">30</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#CHECK_INTERVAL_SECOND"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.CHECK_INTERVAL_SECOND" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerBaseOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference external" href="/docs/apache-airflow/stable/_api/airflow/models/index.html#airflow.models.BaseOperator" title="(in apache-airflow v2.1.4)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">airflow.models.BaseOperator</span></code></a></p> |
| <p>This is the base operator for all SageMaker operators.</p> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><em>dict</em></a>) -- The configuration necessary to start a training job (templated)</p> |
| </dd> |
| </dl> |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.template_fields"> |
| <span class="sig-name descname"><span class="pre">template_fields</span></span><em class="property"><span class="w"> </span><span class="pre">:Sequence[str]</span> <span class="pre">=</span> <span class="pre">['config']</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.template_fields"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.template_fields" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.template_ext"> |
| <span class="sig-name descname"><span class="pre">template_ext</span></span><em class="property"><span class="w"> </span><span class="pre">:Sequence[str]</span> <span class="pre">=</span> <span class="pre">[]</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.template_ext"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.template_ext" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.template_fields_renderers"> |
| <span class="sig-name descname"><span class="pre">template_fields_renderers</span></span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.template_fields_renderers"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.template_fields_renderers" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.ui_color"> |
| <span class="sig-name descname"><span class="pre">ui_color</span></span><em class="property"><span class="w"> </span><span class="pre">=</span> <span class="pre">#ededed</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.ui_color"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.ui_color" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.integer_fields"> |
| <span class="sig-name descname"><span class="pre">integer_fields</span></span><em class="property"><span class="w"> </span><span class="pre">:List[List[Any]]</span> <span class="pre">=</span> <span class="pre">[]</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.integer_fields"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.integer_fields" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.parse_integer"> |
| <span class="sig-name descname"><span class="pre">parse_integer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">field</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.parse_integer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.parse_integer" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Recursive method for parsing string fields holding integer values to integers.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.parse_config_integers"> |
| <span class="sig-name descname"><span class="pre">parse_config_integers</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.parse_config_integers"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.parse_config_integers" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Parse the integer fields of training config to integers in case the config is rendered by Jinja and |
| all fields are str</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.expand_role"> |
| <span class="sig-name descname"><span class="pre">expand_role</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.expand_role"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.expand_role" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Placeholder for calling boto3's <cite>expand_role</cite>, which expands an IAM role name into an ARN.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.preprocess_config"> |
| <span class="sig-name descname"><span class="pre">preprocess_config</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.preprocess_config"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.preprocess_config" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Process the config into a usable form.</p> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.execute"> |
| <em class="property"><span class="pre">abstract</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.hook"> |
| <span class="sig-name descname"><span class="pre">hook</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerBaseOperator.hook"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.hook" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Return SageMakerHook</p> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerProcessingOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aws_conn_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">DEFAULT_CONN_ID</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wait_for_completion</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">print_log</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">CHECK_INTERVAL_SECOND</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_ingestion_time</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">action_if_job_exists</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'increment'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerProcessingOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p> |
| <p>Use Amazon SageMaker Processing to analyze data and evaluate machine learning |
| models on Amazon SageMake. With Processing, you can use a simplified, managed |
| experience on SageMaker to run your data processing workloads, such as feature |
| engineering, data validation, model evaluation, and model interpretation.</p> |
| <blockquote> |
| <div><div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p>For more information on how to use this operator, take a look at the guide: |
| <a class="reference internal" href="../../../../../../../operators/sagemaker.html#howto-operator-sagemakerprocessingoperator"><span class="std std-ref">Create an Amazon SageMaker processing job</span></a></p> |
| </div> |
| </div></blockquote> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><em>dict</em></a>) -- The configuration necessary to start a processing job (templated). |
| For details of the configuration parameter see <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_processing_job" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_processing_job()</span></code></a></p></li> |
| <li><p><strong>aws_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- The AWS connection ID to use.</p></li> |
| <li><p><strong>wait_for_completion</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) -- If wait is set to True, the time interval, in seconds, |
| that the operation waits to check the status of the processing job.</p></li> |
| <li><p><strong>print_log</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) -- if the operator should print the cloudwatch log during processing</p></li> |
| <li><p><strong>check_interval</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) -- if wait is set to be true, this is the time interval |
| in seconds which the operator will check the status of the processing job</p></li> |
| <li><p><strong>max_ingestion_time</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) -- If wait is set to True, the operation fails if the processing job |
| doesn't finish within max_ingestion_time seconds. If you set this parameter to None, |
| the operation does not timeout.</p></li> |
| <li><p><strong>action_if_job_exists</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- Behaviour if the job name already exists. Possible options are "increment" |
| (default) and "fail".</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Return Dict</dt> |
| <dd class="field-even"><p>Returns The ARN of the processing job created in Amazon SageMaker.</p> |
| </dd> |
| </dl> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator.expand_role"> |
| <span class="sig-name descname"><span class="pre">expand_role</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerProcessingOperator.expand_role"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator.expand_role" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Placeholder for calling boto3's <cite>expand_role</cite>, which expands an IAM role name into an ARN.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator.execute"> |
| <span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerProcessingOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerEndpointConfigOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aws_conn_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">DEFAULT_CONN_ID</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerEndpointConfigOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p> |
| <p>Creates an endpoint configuration that Amazon SageMaker hosting |
| services uses to deploy models. In the configuration, you identify |
| one or more models, created using the CreateModel API, to deploy and |
| the resources that you want Amazon SageMaker to provision.</p> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p>For more information on how to use this operator, take a look at the guide: |
| <a class="reference internal" href="../../../../../../../operators/sagemaker.html#howto-operator-sagemakerendpointconfigoperator"><span class="std std-ref">Create an Amazon SageMaker endpoint config job</span></a></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><em>dict</em></a>) -- <p>The configuration necessary to create an endpoint config.</p> |
| <p>For details of the configuration parameter see <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_endpoint_config" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_endpoint_config()</span></code></a></p> |
| </p></li> |
| <li><p><strong>aws_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- The AWS connection ID to use.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Return Dict</dt> |
| <dd class="field-even"><p>Returns The ARN of the endpoint config created in Amazon SageMaker.</p> |
| </dd> |
| </dl> |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator.integer_fields"> |
| <span class="sig-name descname"><span class="pre">integer_fields</span></span><em class="property"><span class="w"> </span><span class="pre">=</span> <span class="pre">[['ProductionVariants',</span> <span class="pre">'InitialInstanceCount']]</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerEndpointConfigOperator.integer_fields"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator.integer_fields" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator.execute"> |
| <span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerEndpointConfigOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointConfigOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerEndpointOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aws_conn_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">DEFAULT_CONN_ID</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wait_for_completion</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">CHECK_INTERVAL_SECOND</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_ingestion_time</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">operation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'create'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerEndpointOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p> |
| <p>When you create a serverless endpoint, SageMaker provisions and manages |
| the compute resources for you. Then, you can make inference requests to |
| the endpoint and receive model predictions in response. SageMaker scales |
| the compute resources up and down as needed to handle your request traffic.</p> |
| <p>Requires an Endpoint Config.</p> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p>For more information on how to use this operator, take a look at the guide: |
| <a class="reference internal" href="../../../../../../../operators/sagemaker.html#howto-operator-sagemakerendpointoperator"><span class="std std-ref">Create an Amazon SageMaker endpoint job</span></a></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><em>dict</em></a>) -- <p>The configuration necessary to create an endpoint.</p> |
| <p>If you need to create a SageMaker endpoint based on an existed |
| SageMaker model and an existed SageMaker endpoint config:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">config</span> <span class="o">=</span> <span class="n">endpoint_configuration</span><span class="p">;</span> |
| </pre></div> |
| </div> |
| <p>If you need to create all of SageMaker model, SageMaker endpoint-config and SageMaker endpoint:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">config</span> <span class="o">=</span> <span class="p">{</span> |
| <span class="s1">'Model'</span><span class="p">:</span> <span class="n">model_configuration</span><span class="p">,</span> |
| <span class="s1">'EndpointConfig'</span><span class="p">:</span> <span class="n">endpoint_config_configuration</span><span class="p">,</span> |
| <span class="s1">'Endpoint'</span><span class="p">:</span> <span class="n">endpoint_configuration</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| <p>For details of the configuration parameter of model_configuration see |
| <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_model" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_model()</span></code></a></p> |
| <p>For details of the configuration parameter of endpoint_config_configuration see |
| <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_endpoint_config" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_endpoint_config()</span></code></a></p> |
| <p>For details of the configuration parameter of endpoint_configuration see |
| <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_endpoint" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_endpoint()</span></code></a></p> |
| </p></li> |
| <li><p><strong>wait_for_completion</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) -- Whether the operator should wait until the endpoint creation finishes.</p></li> |
| <li><p><strong>check_interval</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) -- If wait is set to True, this is the time interval, in seconds, that this operation |
| waits before polling the status of the endpoint creation.</p></li> |
| <li><p><strong>max_ingestion_time</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) -- If wait is set to True, this operation fails if the endpoint creation doesn't |
| finish within max_ingestion_time seconds. If you set this parameter to None it never times out.</p></li> |
| <li><p><strong>operation</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- Whether to create an endpoint or update an endpoint. Must be either 'create or 'update'.</p></li> |
| <li><p><strong>aws_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- The AWS connection ID to use.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Return Dict</dt> |
| <dd class="field-even"><p>Returns The ARN of the endpoint created in Amazon SageMaker.</p> |
| </dd> |
| </dl> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator.create_integer_fields"> |
| <span class="sig-name descname"><span class="pre">create_integer_fields</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerEndpointOperator.create_integer_fields"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator.create_integer_fields" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Set fields which should be casted to integers.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator.expand_role"> |
| <span class="sig-name descname"><span class="pre">expand_role</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerEndpointOperator.expand_role"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator.expand_role" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Placeholder for calling boto3's <cite>expand_role</cite>, which expands an IAM role name into an ARN.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator.execute"> |
| <span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerEndpointOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerEndpointOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerTransformOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aws_conn_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">DEFAULT_CONN_ID</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wait_for_completion</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">CHECK_INTERVAL_SECOND</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_ingestion_time</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTransformOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p> |
| <p>Starts a transform job. A transform job uses a trained model to get inferences |
| on a dataset and saves these results to an Amazon S3 location that you specify.</p> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p>For more information on how to use this operator, take a look at the guide: |
| <a class="reference internal" href="../../../../../../../operators/sagemaker.html#howto-operator-sagemakertransformoperator"><span class="std std-ref">Create an Amazon SageMaker transform job</span></a></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><em>dict</em></a>) -- <p>The configuration necessary to start a transform job (templated).</p> |
| <p>If you need to create a SageMaker transform job based on an existed SageMaker model:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">config</span> <span class="o">=</span> <span class="n">transform_config</span> |
| </pre></div> |
| </div> |
| <p>If you need to create both SageMaker model and SageMaker Transform job:</p> |
| <div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">config</span> <span class="o">=</span> <span class="p">{</span> |
| <span class="s1">'Model'</span><span class="p">:</span> <span class="n">model_config</span><span class="p">,</span> |
| <span class="s1">'Transform'</span><span class="p">:</span> <span class="n">transform_config</span> |
| <span class="p">}</span> |
| </pre></div> |
| </div> |
| <p>For details of the configuration parameter of transform_config see |
| <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_transform_job" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_transform_job()</span></code></a></p> |
| <p>For details of the configuration parameter of model_config, See: |
| <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_model" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_model()</span></code></a></p> |
| </p></li> |
| <li><p><strong>aws_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- The AWS connection ID to use.</p></li> |
| <li><p><strong>wait_for_completion</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) -- Set to True to wait until the transform job finishes.</p></li> |
| <li><p><strong>check_interval</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) -- If wait is set to True, the time interval, in seconds, |
| that this operation waits to check the status of the transform job.</p></li> |
| <li><p><strong>max_ingestion_time</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) -- If wait is set to True, the operation fails |
| if the transform job doesn't finish within max_ingestion_time seconds. If you |
| set this parameter to None, the operation does not timeout.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Return Dict</dt> |
| <dd class="field-even"><p>Returns The ARN of the model created in Amazon SageMaker.</p> |
| </dd> |
| </dl> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator.create_integer_fields"> |
| <span class="sig-name descname"><span class="pre">create_integer_fields</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTransformOperator.create_integer_fields"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator.create_integer_fields" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Set fields which should be casted to integers.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator.expand_role"> |
| <span class="sig-name descname"><span class="pre">expand_role</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTransformOperator.expand_role"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator.expand_role" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Placeholder for calling boto3's <cite>expand_role</cite>, which expands an IAM role name into an ARN.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator.execute"> |
| <span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTransformOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerTuningOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aws_conn_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">DEFAULT_CONN_ID</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wait_for_completion</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">CHECK_INTERVAL_SECOND</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_ingestion_time</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTuningOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p> |
| <p>Starts a hyperparameter tuning job. A hyperparameter tuning job finds the |
| best version of a model by running many training jobs on your dataset using |
| the algorithm you choose and values for hyperparameters within ranges that |
| you specify. It then chooses the hyperparameter values that result in a model |
| that performs the best, as measured by an objective metric that you choose.</p> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p>For more information on how to use this operator, take a look at the guide: |
| <a class="reference internal" href="../../../../../../../operators/sagemaker.html#howto-operator-sagemakertuningoperator"><span class="std std-ref">Start a hyperparameter tuning job</span></a></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><em>dict</em></a>) -- <p>The configuration necessary to start a tuning job (templated).</p> |
| <p>For details of the configuration parameter see |
| <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_hyper_parameter_tuning_job" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_hyper_parameter_tuning_job()</span></code></a></p> |
| </p></li> |
| <li><p><strong>aws_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- The AWS connection ID to use.</p></li> |
| <li><p><strong>wait_for_completion</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) -- Set to True to wait until the tuning job finishes.</p></li> |
| <li><p><strong>check_interval</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) -- If wait is set to True, the time interval, in seconds, |
| that this operation waits to check the status of the tuning job.</p></li> |
| <li><p><strong>max_ingestion_time</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) -- If wait is set to True, the operation fails |
| if the tuning job doesn't finish within max_ingestion_time seconds. If you |
| set this parameter to None, the operation does not timeout.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Return Dict</dt> |
| <dd class="field-even"><p>Returns The ARN of the tuning job created in Amazon SageMaker.</p> |
| </dd> |
| </dl> |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator.integer_fields"> |
| <span class="sig-name descname"><span class="pre">integer_fields</span></span><em class="property"><span class="w"> </span><span class="pre">=</span> <span class="pre">[['HyperParameterTuningJobConfig',</span> <span class="pre">'ResourceLimits',</span> <span class="pre">'MaxNumberOfTrainingJobs'],...</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTuningOperator.integer_fields"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator.integer_fields" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator.expand_role"> |
| <span class="sig-name descname"><span class="pre">expand_role</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTuningOperator.expand_role"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator.expand_role" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Placeholder for calling boto3's <cite>expand_role</cite>, which expands an IAM role name into an ARN.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator.execute"> |
| <span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTuningOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTuningOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerModelOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aws_conn_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">DEFAULT_CONN_ID</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerModelOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p> |
| <p>Creates a model in Amazon SageMaker. In the request, you name the model and |
| describe a primary container. For the primary container, you specify the Docker |
| image that contains inference code, artifacts (from prior training), and a custom |
| environment map that the inference code uses when you deploy the model for predictions.</p> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p>For more information on how to use this operator, take a look at the guide: |
| <a class="reference internal" href="../../../../../../../operators/sagemaker.html#howto-operator-sagemakermodeloperator"><span class="std std-ref">Create an Amazon SageMaker model</span></a></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>config</strong> -- <p>The configuration necessary to create a model.</p> |
| <p>For details of the configuration parameter see <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_model" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_model()</span></code></a></p> |
| </p></li> |
| <li><p><strong>aws_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- The AWS connection ID to use.</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Return Dict</dt> |
| <dd class="field-even"><p>Returns The ARN of the model created in Amazon SageMaker.</p> |
| </dd> |
| </dl> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator.expand_role"> |
| <span class="sig-name descname"><span class="pre">expand_role</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerModelOperator.expand_role"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator.expand_role" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Placeholder for calling boto3's <cite>expand_role</cite>, which expands an IAM role name into an ARN.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator.execute"> |
| <span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerModelOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerModelOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerTrainingOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aws_conn_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">DEFAULT_CONN_ID</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wait_for_completion</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">print_log</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_interval</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">CHECK_INTERVAL_SECOND</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_ingestion_time</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_if_job_exists</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">action_if_job_exists</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'increment'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTrainingOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p> |
| <p>Starts a model training job. After training completes, Amazon SageMaker saves |
| the resulting model artifacts to an Amazon S3 location that you specify.</p> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p>For more information on how to use this operator, take a look at the guide: |
| <a class="reference internal" href="../../../../../../../operators/sagemaker.html#howto-operator-sagemakertrainingoperator"><span class="std std-ref">Create an Amazon SageMaker training job</span></a></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><em>dict</em></a>) -- <p>The configuration necessary to start a training job (templated).</p> |
| <p>For details of the configuration parameter see <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.create_training_job()</span></code></a></p> |
| </p></li> |
| <li><p><strong>aws_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- The AWS connection ID to use.</p></li> |
| <li><p><strong>wait_for_completion</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) -- If wait is set to True, the time interval, in seconds, |
| that the operation waits to check the status of the training job.</p></li> |
| <li><p><strong>print_log</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) -- if the operator should print the cloudwatch log during training</p></li> |
| <li><p><strong>check_interval</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a>) -- if wait is set to be true, this is the time interval |
| in seconds which the operator will check the status of the training job</p></li> |
| <li><p><strong>max_ingestion_time</strong> (<em>Optional</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><em>int</em></a><em>]</em>) -- If wait is set to True, the operation fails if the training job |
| doesn't finish within max_ingestion_time seconds. If you set this parameter to None, |
| the operation does not timeout.</p></li> |
| <li><p><strong>check_if_job_exists</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><em>bool</em></a>) -- If set to true, then the operator will check whether a training job |
| already exists for the name in the config.</p></li> |
| <li><p><strong>action_if_job_exists</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- Behaviour if the job name already exists. Possible options are "increment" |
| (default) and "fail". |
| This is only relevant if check_if</p></li> |
| </ul> |
| </dd> |
| <dt class="field-even">Return Dict</dt> |
| <dd class="field-even"><p>Returns The ARN of the training job created in Amazon SageMaker.</p> |
| </dd> |
| </dl> |
| <dl class="py attribute"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator.integer_fields"> |
| <span class="sig-name descname"><span class="pre">integer_fields</span></span><em class="property"><span class="w"> </span><span class="pre">=</span> <span class="pre">[['ResourceConfig',</span> <span class="pre">'InstanceCount'],</span> <span class="pre">['ResourceConfig',</span> <span class="pre">'VolumeSizeInGB'],...</span></em><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTrainingOperator.integer_fields"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator.integer_fields" title="Permalink to this definition">¶</a></dt> |
| <dd></dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator.expand_role"> |
| <span class="sig-name descname"><span class="pre">expand_role</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTrainingOperator.expand_role"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator.expand_role" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Placeholder for calling boto3's <cite>expand_role</cite>, which expands an IAM role name into an ARN.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator.execute"> |
| <span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerTrainingOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTrainingOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
| </dd></dl> |
| |
| <dl class="py class"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerDeleteModelOperator"> |
| <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker.</span></span><span class="sig-name descname"><span class="pre">SageMakerDeleteModelOperator</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">aws_conn_id</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">DEFAULT_CONN_ID</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerDeleteModelOperator"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerDeleteModelOperator" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Bases: <a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator" title="airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SageMakerBaseOperator</span></code></a></p> |
| <p>Deletes a SageMaker model.</p> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <p>For more information on how to use this operator, take a look at the guide: |
| <a class="reference internal" href="../../../../../../../operators/sagemaker.html#howto-operator-sagemakerdeletemodeloperator"><span class="std std-ref">Delete an Amazon SageMaker model</span></a></p> |
| </div> |
| <dl class="field-list simple"> |
| <dt class="field-odd">Parameters</dt> |
| <dd class="field-odd"><ul class="simple"> |
| <li><p><strong>config</strong> -- The configuration necessary to delete the model. |
| For details of the configuration parameter see <a class="reference external" href="https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.delete_model" title="(in Boto3 Docs v1.24.7)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">SageMaker.Client.delete_model()</span></code></a></p></li> |
| <li><p><strong>aws_conn_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><em>str</em></a>) -- The AWS connection ID to use.</p></li> |
| </ul> |
| </dd> |
| </dl> |
| <dl class="py method"> |
| <dt class="sig sig-object py" id="airflow.providers.amazon.aws.operators.sagemaker.SageMakerDeleteModelOperator.execute"> |
| <span class="sig-name descname"><span class="pre">execute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">context</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../../_modules/airflow/providers/amazon/aws/operators/sagemaker.html#SageMakerDeleteModelOperator.execute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerDeleteModelOperator.execute" title="Permalink to this definition">¶</a></dt> |
| <dd><p>This is the main method to derive when creating an operator. |
| Context is the same dictionary used as when rendering jinja templates.</p> |
| <p>Refer to get_template_context for more context.</p> |
| <dl class="field-list simple"> |
| </dl> |
| </dd></dl> |
| |
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| <ul> |
| <li><a class="reference internal" href="#"><code class="xref py py-mod docutils literal notranslate"><span class="pre">airflow.providers.amazon.aws.operators.sagemaker</span></code></a><ul> |
| <li><a class="reference internal" href="#module-contents">Module Contents</a><ul> |
| <li><a class="reference internal" href="#classes">Classes</a></li> |
| <li><a class="reference internal" href="#attributes">Attributes</a><ul> |
| <li><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.DEFAULT_CONN_ID">DEFAULT_CONN_ID</a></li> |
| <li><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.CHECK_INTERVAL_SECOND">CHECK_INTERVAL_SECOND</a></li> |
| <li><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator">SageMakerBaseOperator</a><ul> |
| <li><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.template_fields">template_fields</a></li> |
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| <li><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerBaseOperator.hook">hook</a></li> |
| </ul> |
| </li> |
| <li><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerProcessingOperator">SageMakerProcessingOperator</a><ul> |
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| </ul> |
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| <li><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator">SageMakerTransformOperator</a><ul> |
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| <li><a class="reference internal" href="#airflow.providers.amazon.aws.operators.sagemaker.SageMakerTransformOperator.execute">execute</a></li> |
| </ul> |
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