Uses of Class
ai.onnx.proto.OnnxMl.TrainingInfoProto.Builder
Packages that use OnnxMl.TrainingInfoProto.Builder
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Uses of OnnxMl.TrainingInfoProto.Builder in ai.onnx.proto
Subclasses with type arguments of type OnnxMl.TrainingInfoProto.Builder in ai.onnx.protoModifier and TypeClassDescriptionstatic final classTraining information TrainingInfoProto stores information for training a model.Methods in ai.onnx.proto that return OnnxMl.TrainingInfoProto.BuilderModifier and TypeMethodDescriptionOnnxMl.TrainingInfoProto.Builder.addAllInitializationBinding(Iterable<? extends OnnxMl.StringStringEntryProto> values) This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.addAllUpdateBinding(Iterable<? extends OnnxMl.StringStringEntryProto> values) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.Builder.addInitializationBinding(int index, OnnxMl.StringStringEntryProto value) This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.addInitializationBinding(int index, OnnxMl.StringStringEntryProto.Builder builderForValue) This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.addInitializationBinding(OnnxMl.StringStringEntryProto value) This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.addInitializationBinding(OnnxMl.StringStringEntryProto.Builder builderForValue) This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) OnnxMl.ModelProto.Builder.addTrainingInfoBuilder()Training-specific information.OnnxMl.ModelProto.Builder.addTrainingInfoBuilder(int index) Training-specific information.OnnxMl.TrainingInfoProto.Builder.addUpdateBinding(int index, OnnxMl.StringStringEntryProto value) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.Builder.addUpdateBinding(int index, OnnxMl.StringStringEntryProto.Builder builderForValue) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.Builder.addUpdateBinding(OnnxMl.StringStringEntryProto value) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.Builder.addUpdateBinding(OnnxMl.StringStringEntryProto.Builder builderForValue) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.Builder.clear()OnnxMl.TrainingInfoProto.Builder.clearAlgorithm()This field represents a training algorithm step.OnnxMl.TrainingInfoProto.Builder.clearField(com.google.protobuf.Descriptors.FieldDescriptor field) OnnxMl.TrainingInfoProto.Builder.clearInitialization()This field describes a graph to compute the initial tensors upon starting the training process.OnnxMl.TrainingInfoProto.Builder.clearInitializationBinding()This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) OnnxMl.TrainingInfoProto.Builder.clearUpdateBinding()Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.Builder.clone()OnnxMl.ModelProto.Builder.getTrainingInfoBuilder(int index) Training-specific information.OnnxMl.TrainingInfoProto.Builder.mergeAlgorithm(OnnxMl.GraphProto value) This field represents a training algorithm step.OnnxMl.TrainingInfoProto.Builder.mergeFrom(OnnxMl.TrainingInfoProto other) OnnxMl.TrainingInfoProto.Builder.mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) OnnxMl.TrainingInfoProto.Builder.mergeFrom(com.google.protobuf.Message other) OnnxMl.TrainingInfoProto.Builder.mergeInitialization(OnnxMl.GraphProto value) This field describes a graph to compute the initial tensors upon starting the training process.OnnxMl.TrainingInfoProto.Builder.mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) OnnxMl.TrainingInfoProto.newBuilder()OnnxMl.TrainingInfoProto.newBuilder(OnnxMl.TrainingInfoProto prototype) OnnxMl.TrainingInfoProto.newBuilderForType()protected OnnxMl.TrainingInfoProto.BuilderOnnxMl.TrainingInfoProto.newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) OnnxMl.TrainingInfoProto.Builder.removeInitializationBinding(int index) This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.removeUpdateBinding(int index) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.Builder.setAlgorithm(OnnxMl.GraphProto value) This field represents a training algorithm step.OnnxMl.TrainingInfoProto.Builder.setAlgorithm(OnnxMl.GraphProto.Builder builderForValue) This field represents a training algorithm step.OnnxMl.TrainingInfoProto.Builder.setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value) OnnxMl.TrainingInfoProto.Builder.setInitialization(OnnxMl.GraphProto value) This field describes a graph to compute the initial tensors upon starting the training process.OnnxMl.TrainingInfoProto.Builder.setInitialization(OnnxMl.GraphProto.Builder builderForValue) This field describes a graph to compute the initial tensors upon starting the training process.OnnxMl.TrainingInfoProto.Builder.setInitializationBinding(int index, OnnxMl.StringStringEntryProto value) This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.setInitializationBinding(int index, OnnxMl.StringStringEntryProto.Builder builderForValue) This field specifies the bindings from the outputs of "initialization" to some initializers in "ModelProto.graph.initializer" and the "algorithm.initializer" in the same TrainingInfoProto.OnnxMl.TrainingInfoProto.Builder.setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value) OnnxMl.TrainingInfoProto.Builder.setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields) OnnxMl.TrainingInfoProto.Builder.setUpdateBinding(int index, OnnxMl.StringStringEntryProto value) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.Builder.setUpdateBinding(int index, OnnxMl.StringStringEntryProto.Builder builderForValue) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.toBuilder()Methods in ai.onnx.proto that return types with arguments of type OnnxMl.TrainingInfoProto.BuilderModifier and TypeMethodDescriptionOnnxMl.ModelProto.Builder.getTrainingInfoBuilderList()Training-specific information.Methods in ai.onnx.proto with parameters of type OnnxMl.TrainingInfoProto.BuilderModifier and TypeMethodDescriptionOnnxMl.ModelProto.Builder.addTrainingInfo(int index, OnnxMl.TrainingInfoProto.Builder builderForValue) Training-specific information.OnnxMl.ModelProto.Builder.addTrainingInfo(OnnxMl.TrainingInfoProto.Builder builderForValue) Training-specific information.OnnxMl.ModelProto.Builder.setTrainingInfo(int index, OnnxMl.TrainingInfoProto.Builder builderForValue) Training-specific information.