Package: auto-mlflow
Auto MLFlowYour automated MLOps library for MLFlow.InstallationInstall MLFlow.pip3 install mlflowInstall Auto MLFlow.pip3 install auto_mlflowWorking Demonstration:Start a MLFlow Server.mlflow server --host 127.0.0.1 --port 5555Use Auto MLFlow to log model and experiment related information.importauto_mlflowuser_name="Ravin Kumar"project_name="Object Detection"experiment_name="Using Yolo approach"runName="using yolov3"total_epochs=30mlflow_server_uri="http://127.0.0.1:5555"# IP address of the MLFlow Server.# initialisationauto_mlflow.init_run(user_name,project_name,experiment_name,runName,mlflow_server_uri)# project, experiment, and run is created# below this line, whatever is printed in the terminal will also get logged in the MLFlow inside the file log.txtauto_mlflow.write_param(param_dict={"learning_rate":"0.001","total_epochs":str(total_epochs)})# save training related information# storing train, val, and test loss valuesmodel_architecture=get_model_architecture()forepochinrange(total_epochs):train_loss=...valid_loss=...test_loss=...metric_dict={"train_loss":train_loss,"valid_loss":valid_loss,"test_loss":test_loss}auto_mlflow.write_metric(metric_dict,step=epoch)# storing an image in MLFlow Servernumpy_array_gbr=visualised_image(.....)auto_mlflow.write_image(numpy_array_gbr,image_name="image.jpg")# storing text in a file inside MLFlow Serverauto_mlflow.write_text(filename="additional_file.txt",filedata="object detection model")# storing already existing local file inside MLFlow Server# example- incase one wants to save only weights, and not rely on model registry. This will get saved inside weights/ in MLFlow Severauto_mlflow.write_files("yolo_weights.pth",filepath="weights")# storing an entire directory present in local system, to the MLFlow Serverauto_mlflow.write_directory("./other_data",mlflow_dir_path="artifacts")# this will copy all the content of ./other_data to MLFlow inside artifacts/# Logging a modelauto_mlflow.log_model(model_architecture,model_run_path="models")# the logged model can be used for model registryauto_mlflow.end_run()# all the information is successfully saved.# completeLICENSECopyright (c) 2024 Ravin Kumar
Website: https://mr-ravin.github.io

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