The molla has 4 named, numeric columns

Column-based Signature Example

Each column-based stimolo and output is represented by per type corresponding esatto one of MLflow giorno types and an optional name. The following example displays an MLmodel file excerpt containing the model signature for a classification model trained on the Iris dataset. The output is an unnamed integer specifying the predicted class.

Tensor-based Signature Example

Each tensor-based incentivo and output is represented by a dtype corresponding preciso one of numpy datazione types, shape and an optional name. When specifying the shape, -1 is used for axes that ple displays an MLmodel file excerpt containing the model signature for verso classification model trained on the MNIST dataset. The spinta has one named tensor where molla sample is an image represented by a 28 ? 28 ? 1 array of float32 numbers. The output is an unnamed tensor that has 10 units specifying the likelihood corresponding preciso each of the 10 classes. Note that the first dimension of the input and the output is the batch size and is thus servizio esatto -1 onesto allow for variable batch sizes.

Signature Enforcement

Precisazione enforcement checks the provided stimolo against the model’s signature and raises an exception if the molla is not compatible. This enforcement is applied durante MLflow before calling the underlying model implementation. Note that this enforcement only applies when using MLflow model deployment tools or when loading models as python_function . Read more

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