Methods

Summary

method	class parent	truncated documentation
__getstate__	BaseEstimator	Removes any non pickable attribute.
__getstate__	BaseLearningOnnx	Overwrites getstate to get rid of InferenceSession.
__getstate__	OrtDataLoader	Removes any non pickable attribute.
__getstate__	OrtGradientForwardBackwardOptimizer	Removes any non pickable attribute.
__getstate__	OrtGradientForwardBackward	Removes any non pickable attribute.
__init__	BaseEstimator
__init__	BaseLearningOnnx
__init__	OrtDataLoader
__init__	OrtGradientOptimizer
__init__	OrtGradientForwardBackwardOptimizer
__init__	OrtGradientForwardBackward
__init__	OrtGradientForwardBackwardFunction
__init__	AbsoluteLearningLoss
__init__	BaseLearningLoss
__init__	ElasticLearningLoss
__init__	NegLogLearningLoss
__init__	SquareLearningLoss
__init__	BaseLearningPenalty
__init__	ElasticLearningPenalty
__init__	NoLearningPenalty
__init__	BaseLearningRate
__init__	LearningRateSGD
__init__	LearningRateSGDNesterov
__init__	OnnxSegment
__init__	OnnxSplitting
__len__	OrtDataLoader	Returns the number of observations.
__repr__	BaseEstimator	Usual.
__repr__	BaseLearningOnnx	Usual
__repr__	OrtDataLoader	usual
__repr__	OrtGradientForwardBackward	usual
__repr__	OnnxSegment
__repr_extended__	BaseLearningOnnx
__repr_extended__	BaseLearningRate
__repr_extended__	LearningRateSGD
__repr_extended__	LearningRateSGDNesterov
__setstate__	BaseEstimator	Restores any non pickable attribute.
__setstate__	BaseLearningOnnx	Overwrites getstate to get rid of InferenceSession.
__setstate__	OrtDataLoader	Restores any non pickable attribute.
__setstate__	OrtGradientForwardBackwardOptimizer	Restores any non pickable attribute.
__setstate__	OrtGradientForwardBackward	Restores any non pickable attribute.
_bind_input_ortvalue	BaseLearningOnnx	Binds C_OrtValue to the structure used by InferenceSession to run inference.
_bind_input_ortvalue	OrtGradientOptimizer	Binds C_OrtValue to the structure used by InferenceSession to run inference.
_bind_output_ortvalue	BaseLearningOnnx	Binds C_OrtValue to the structure used by InferenceSession to run inference.
_call_iobinding	AbsoluteLearningLoss
_call_iobinding	BaseLearningLoss
_call_iobinding	ElasticLearningLoss
_call_iobinding	NegLogLearningLoss
_call_iobinding	SquareLearningLoss
_call_iobinding	BaseLearningPenalty
_call_iobinding	ElasticLearningPenalty
_call_iobinding	NoLearningPenalty
_call_iobinding	BaseLearningRate
_call_iobinding	LearningRateSGD
_call_iobinding	LearningRateSGDNesterov
_create_onnx_graphs	OrtGradientForwardBackward	Creates forward and backward ONNX graph. The new class has the following attributes:
_create_training_session	OrtGradientOptimizer	Creates an instance of TrainingSession.
_create_training_session	OrtGradientForwardBackwardOptimizer
_evaluation	OrtGradientOptimizer
_evaluation	OrtGradientForwardBackwardOptimizer
_get_att_state	OrtGradientForwardBackwardOptimizer
_get_cutting_points	OnnxSplitting
_get_trained_onnx	BaseEstimator	Returns the trained onnx graph, the initial graph modified by replacing the initializers with the trained …
_init	OnnxSplitting
_init_next	OrtGradientForwardBackward
_iteration	OrtGradientOptimizer
_iteration	OrtGradientForwardBackwardOptimizer
_make_onnx	OnnxSplitting	Builds one onnx subpart including segments from a to b (excluded).
_make_segment	OnnxSplitting
_next_iter	OrtDataLoader
_split_2	OnnxSplitting	Splits the segments into two groups of the same size.
backward	OrtGradientForwardBackwardFunction	Implements backward function. The function returns an OrtValueVector.
build_onnx_function	BaseLearningOnnx	This class computes a function represented as an ONNX graph. This method builds it. This function creates …
build_onnx_function	OrtGradientForwardBackwardOptimizer	Creates ONNX graph and InferenceSession related to any operations applying on OrtValue.
build_onnx_function	AbsoluteLearningLoss
build_onnx_function	ElasticLearningLoss
build_onnx_function	NegLogLearningLoss
build_onnx_function	SquareLearningLoss
build_onnx_function	ElasticLearningPenalty
build_onnx_function	NoLearningPenalty
build_onnx_function	LearningRateSGD
build_onnx_function	LearningRateSGDNesterov
build_onnx_score_function	AbsoluteLearningLoss	Assuming the loss function was created. This one takes the onnx graph and generate the onnx graph for the …
build_onnx_score_function	BaseLearningLoss	Assuming the loss function was created. This one takes the onnx graph and generate the onnx graph for the …
build_onnx_score_function	ElasticLearningLoss	Assuming the loss function was created. This one takes the onnx graph and generate the onnx graph for the …
build_onnx_score_function	NegLogLearningLoss	Assuming the loss function was created. This one takes the onnx graph and generate the onnx graph for the …
build_onnx_score_function	SquareLearningLoss	Assuming the loss function was created. This one takes the onnx graph and generate the onnx graph for the …
clear_binding_inputs	BaseLearningOnnx	Clears binding and empty cache.
fit	OrtGradientOptimizer	Trains the model.
fit	OrtGradientForwardBackwardOptimizer	Trains the model.
forward	OrtGradientForwardBackwardFunction	Implements forward function.
get_full_state	OrtGradientForwardBackwardOptimizer	Returns the trained weights and the inputs.
get_initializer	OrtGradientForwardBackward	Returns an initializer as numpy arrays.
get_params	BaseEstimator	Returns the list of parameters. Parameter deep is unused.
get_state	OrtGradientOptimizer	Returns the trained weights.
get_state	OrtGradientForwardBackwardOptimizer	Returns the trained weights.
get_trained_onnx	BaseEstimator	Returns the trained onnx graph, the initial graph modified by replacing the initializers with the trained …
get_trained_onnx	OrtGradientOptimizer	Returns the trained onnx graph, the initial graph modified by replacing the initializers with the trained …
get_trained_onnx	OrtGradientForwardBackwardOptimizer	Returns the trained onnx graph, the initial graph modified by replacing the initializers with the trained …
init_learning_rate	BaseLearningRate	Initializes the learning rate at the beginning of the training.
init_learning_rate	LearningRateSGD	Updates the learning rate at the end of an iteration.
init_learning_rate	LearningRateSGDNesterov	Updates the learning rate at the end of an iteration.
iter_bind	OrtDataLoader	Iterates over the datasets by drawing batch_size consecutive observations. Modifies a bind structure.
iter_numpy	OrtDataLoader	Iterates over the datasets by drawing batch_size consecutive observations. This iterator is slow as it …
iter_ortvalue	OrtDataLoader	Iterates over the datasets by drawing batch_size consecutive observations. This iterator is slow as it …
loop	BaseLearningRate	Loops over learning rate values, n to be precise.
loop	LearningRateSGD	Loops over learning rate values, n to be precise.
loop	LearningRateSGDNesterov	Loops over learning rate values, n to be precise.
loss_gradient	AbsoluteLearningLoss	Returns the loss and the gradient as OrtValue.
loss_gradient	BaseLearningLoss	Returns the loss and the gradient as OrtValue.
loss_gradient	ElasticLearningLoss	Returns the loss and the gradient as OrtValue.
loss_gradient	NegLogLearningLoss	Returns the loss and the gradient as OrtValue.
loss_gradient	SquareLearningLoss	Returns the loss and the gradient as OrtValue.
loss_scores	AbsoluteLearningLoss	Returns the weighted loss (or score) for every observation as OrtValue.
loss_scores	BaseLearningLoss	Returns the weighted loss (or score) for every observation as OrtValue.
loss_scores	ElasticLearningLoss	Returns the weighted loss (or score) for every observation as OrtValue.
loss_scores	NegLogLearningLoss	Returns the weighted loss (or score) for every observation as OrtValue.
loss_scores	SquareLearningLoss	Returns the weighted loss (or score) for every observation as OrtValue.
losses	OrtGradientForwardBackwardOptimizer	Returns the losses associated to every observation.
make_onnx	OnnxSplitting	Builds onnx subparts based on the segmentation defined by extremities.
new_instance	OrtGradientForwardBackward	Creates an instance of class self.cls_type_. It implements methods forward and backward.
penalty_loss	BaseLearningPenalty	Returns the received loss. Updates the loss inplace.
penalty_loss	ElasticLearningPenalty	Computes the penalty associated to every weights and adds them up to the loss.
penalty_loss	NoLearningPenalty	Returns the received loss. Updates the loss inplace.
save_for_backward	OrtGradientForwardBackwardFunction	Saves inputs furing forward steps. The list inputs is copied (simple copy, no deep copy).
save_onnx_graph	BaseOnnxClass	Saves all ONNX files stored in this class.
score	OrtGradientForwardBackwardOptimizer	Return the whole score associated.
set_params	BaseEstimator	Returns the list of parameters. Parameter deep is unused.
set_state	OrtGradientOptimizer	Changes the trained weights.
set_state	OrtGradientForwardBackwardOptimizer	Changes the trained weights.
split_segment	OnnxSplitting	Splits the segments into n_parts segments
update_learning_rate	BaseLearningRate	Updates the learning rate at the end of an iteration.
update_learning_rate	LearningRateSGD	Updates the learning rate at the end of an iteration.
update_learning_rate	LearningRateSGDNesterov	Updates the learning rate at the end of an iteration.
update_weights	BaseLearningPenalty	Returns the received loss. Updates the weight inplace.
update_weights	ElasticLearningPenalty
update_weights	NoLearningPenalty	Returns the received loss. Updates the weight inplace.
update_weights	BaseLearningRate	Updates weights based on the algorithm this class is setting up.
update_weights	LearningRateSGD
update_weights	LearningRateSGDNesterov