Having a radical understanding of the foundations is crucial earlier than utilizing the MLOps three-stage pipeline. If you happen to haven’t already, I counsel the first article (introduction) to catch up.
Moreover, if the Knowledge Ingestion pipeline hasn’t been arrange but, take a look at Article #2.1 for the tutorial.
Within the occasion that you simply uncared for to construct the MLOps pipeline mannequin, please learn our Article #2.2 for the steps.
Lastly, when you haven’t tried inferencing together with your mannequin, I insist you get a gist of inferencing with Article #2.3.
We’re on the finish of our MLOps 3-Stage pipeline venture, we have now created separate elements for every stage. On this article, we’ll mix this all right into a single pipeline, which when executed, will perfrom all of the operations as requied.
Create a brand new python file named main_pipeline.py and begin it. We shall be following the beneath folder construction, for our venture:
.
|-- Animal_Data/
| `-- photographs/
| `-- animals10/
| `-- raw-img/
| `-- ~~ recordsdata as per animal lessons ~~
|-- pipeline_files/
| |-- data_ingestion.py
| |-- model_development.py
| `-- model_inference.py
|-- inference_samples/
| `-- sample_img.png
|-- main_pipeline.py
`-- best_checkpoint.pth.tar/
`-- best_model.pth
Don’t fear in case your folder construction doesn’t appear like this. You’ll be able to all the time make folder and transfer recordsdata in the precise listing. I prefer it this fashion, because it helps in organizing the recordsdata a lot better. Additionally, so as code samples, alter the file location accordingly.
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