Readonly evalGet input names of the loaded eval model. Is an empty array if no eval model is loaded.
Readonly evalGet output names of the loaded eval model. Is an empty array if no eval model is loaded.
Readonly trainingGet input names of the loaded training model.
Readonly trainingGet output names of the loaded training model.
Copies the model parameters to a contiguous buffer. Usually used in the context of Federated Learning. Currently, only supporting models with parameters of type Float32.
A promise that resolves to a Float32 OnnxValue of the requested parameters.
When set to true, only trainable parameters are copied. Trainable parameters are parameters for which requires_grad is set to true. Default value is true.
Retrieves the size of all parameters for the training state. Calculates the total number of primitive (datatype of the parameters) elements of all the parameters in the training state.
When set to true, the size is calculated for trainable params only. Default value is true.
Copies parameter values from the given array to the training state. Currently, only supporting models with parameters of type Float32.
True if trainable parameters only to be modified, false otherwise. Default value is true.
Run a single eval step with the given inputs and options using the eval model.
A promise that resolves to a map, which uses output names as keys and OnnxValue as corresponding values.
Representation of the model input.
Optional options: RunOptionsOptional. A set of options that controls the behavior of model eval step.
Run a single eval step with the given inputs and options using the eval model.
A promise that resolves to a map, which uses output names as keys and OnnxValue as corresponding values.
Representation of the model input.
Representation of the model output. detail.
Optional options: RunOptionsOptional. A set of options that controls the behavior of model eval step.
Runs a single optimizer step, which performs weight updates for the trainable parameters using the optimizer model.
Optional options: RunOptionsOptional. A set of options that controls the behavior of model optimizing.
Run TrainStep asynchronously with the given feeds and options.
A promise that resolves to a map, which uses output names as keys and OnnxValue as corresponding values.
Representation of the model input. See type description of InferenceSession.InputType for
detail.
Optional options: RunOptionsOptional. A set of options that controls the behavior of model training.
Run a single train step with the given inputs and options.
A promise that resolves to a map, which uses output names as keys and OnnxValue as corresponding values.
Representation of the model input.
Representation of the model output. detail.
Optional options: RunOptionsOptional. A set of options that controls the behavior of model training.
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Represent a runtime instance of an ONNX training session, which contains a model that can be trained, and, optionally, an eval and optimizer model.