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- AVTECH's Air Flow 2 Sensor (NO) provides real-time recognition of air flow stoppage. This Air Flow 2 Sensor (NO) is normally open and includes a mounting clip and clamp. Typical use is to monitor continuous air flow in an HVAC duct, under a raised floor, or near a fan on a rack cabinet or important ser.
Apache Airflow¶
Airflow 2 4 14 Mm
Apache Airflowis a platform that enables you to programmatically author, schedule, and monitor workflows. Using Airflow,you can build a workflow for SageMaker training, hyperparameter tuning, batch transform and endpoint deployment.You can use any SageMaker deep learning framework or Amazon algorithms to perform above operations in Airflow.
Airflow 2 4 14 Inch
There are two ways to build a SageMaker workflow. Using Airflow SageMaker operators or using Airflow PythonOperator.
1. SageMaker Operators: In Airflow 1.10.1, the SageMaker team contributed special operators for SageMaker operations.Each operator takes a configuration dictionary that defines the corresponding operation. We provide APIs to generatethe configuration dictionary in the SageMaker Python SDK. Currently, the following SageMaker operators are supported:
SageMakerTrainingOperator
SageMakerTuningOperator
SageMakerModelOperator
SageMakerTransformOperator
SageMakerEndpointConfigOperator
Permute 2 2 1 7.SageMakerEndpointOperator
2. PythonOperator: Airflow built-in operator that executes Python callables. You can use the PythonOperator to executeoperations in the SageMaker Python SDK to create a SageMaker workflow.
Using Airflow on AWS¶
Turbine is an open-source AWS CloudFormation template that enables you to create an Airflow resource stack on AWS.You can get it here: https://github.com/villasv/aws-airflow-stack
Using Airflow SageMaker Operators¶
![Airflow Airflow](https://acisxtech.com/wp-content/uploads/2019/09/Airflow-Crack-Main-Image-300x144.jpg)
Starting with Airflow 1.10.1, you can use SageMaker operators in Airflow. All SageMaker operators take a configurationdictionary that can be generated by the SageMaker Python SDK. For example:
Now you can pass these configurations to the corresponding SageMaker operators and create the workflow:
Using Airflow Python Operator¶
Airflow PythonOperatoris a built-in operator that can execute any Python callable. If you want to build the SageMaker workflow in a moreflexible way, write your python callables for SageMaker operations by using the SageMaker Python SDK.
Airflow 2 4 14 Pipe
Then build your workflow by using the PythonOperator with the Python callables defined above:
Airflow 2 4 14 Gauge
A workflow that runs a SageMaker training job and a batch transform job is finished. You can customize your Pythoncallables with the SageMaker Python SDK according to your needs, and build more flexible and powerful workflows.