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ONNXModel

docs/Quick Examples/transformers/deep_learning/_ONNXModel.md

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import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; import DocTable from "@theme/DocumentationTable";

ONNXModel

<Tabs defaultValue="py" values={[ {label: Python, value: py}, {label: Scala, value: scala}, ]}> <TabItem value="py">

py
from synapse.ml.onnx import ONNXModel

model_path = "PUT_YOUR_MODEL_PATH"
onnx_ml = (ONNXModel()
            .setModelLocation(model_path)
            .setFeedDict({"float_input": "features"})
            .setFetchDict({"prediction": "output_label", "rawProbability": "output_probability"}))
</TabItem> <TabItem value="scala">
scala
import com.microsoft.azure.synapse.ml.onnx._

val model_path = "PUT_YOUR_MODEL_PATH"
val onnx_ml = (new ONNXModel()
                  .setModelLocation(model_path)
                  .setFeedDict(Map("float_input" -> "features"))
                  .setFetchDict(Map("prediction" -> "output_label", "rawProbability" -> "output_probability")))
</TabItem> </Tabs>

<DocTable className="ONNXModel" py="synapse.ml.onnx.html#module-synapse.ml.onnx.ONNXModel" scala="com/microsoft/azure/synapse/ml/onnx/ONNXModel.html" csharp="classSynapse_1_1ML_1_1Onnx_1_1ONNXModel.html" sourceLink="https://github.com/microsoft/SynapseML/blob/master/deep-learning/src/main/scala/com/microsoft/azure/synapse/ml/onnx/ONNXModel.scala" />