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ml_model.py
11
ml_model.py
@ -6,6 +6,8 @@ import os.path
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import mlflow
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import mlflow
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import sys
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import sys
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from mlflow.tracking import MlflowClient
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from tensorflow import keras
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from tensorflow import keras
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from tensorflow.keras import layers
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from tensorflow.keras import layers
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from tensorflow.keras.layers.experimental import preprocessing
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from tensorflow.keras.layers.experimental import preprocessing
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@ -48,7 +50,12 @@ model.fit(train_X, train_Y, verbose=verbose, epochs=epochs)
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signature = mlflow.models.signature.infer_signature(train_X.numpy(), model.predict(train_X.numpy()))
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signature = mlflow.models.signature.infer_signature(train_X.numpy(), model.predict(train_X.numpy()))
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input_data = test_X
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input_data = test_X
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# Dane do rejestracji modelu w MlFlow
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mlflow.set_tracking_uri("http://172.17.0.1:5000")
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client = MlflowClient()
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model_name = "s434704"
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with mlflow.start_run():
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with mlflow.start_run():
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mlflow.keras.log_model(model, "movies_on_streaming_platforms_model", registered_model_name="s434704", input_example=input_data.numpy(), signature=signature)
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mlflow.keras.save_model(model, "movies_on_streaming_platforms_model", input_example=input_data.numpy(), signature=signature)
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mlflow.keras.save_model(model, "movies_on_streaming_platforms_model", input_example=input_data.numpy(), signature=signature)
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