Uses of Interface
ai.onnx.proto.OnnxMl.StringStringEntryProtoOrBuilder
Packages that use OnnxMl.StringStringEntryProtoOrBuilder
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Uses of OnnxMl.StringStringEntryProtoOrBuilder in ai.onnx.proto
Classes in ai.onnx.proto that implement OnnxMl.StringStringEntryProtoOrBuilderModifier and TypeClassDescriptionstatic final classStringStringEntryProto follows the pattern for cross-proto-version maps.static final classStringStringEntryProto follows the pattern for cross-proto-version maps.Methods in ai.onnx.proto that return OnnxMl.StringStringEntryProtoOrBuilderModifier and TypeMethodDescriptionOnnxMl.TensorProto.Builder.getExternalDataOrBuilder(int index) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProto.getExternalDataOrBuilder(int index) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TensorProtoOrBuilder.getExternalDataOrBuilder(int index) Data can be stored inside the protobuf file using type-specific fields or raw_data.OnnxMl.TrainingInfoProto.Builder.getInitializationBindingOrBuilder(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.getInitializationBindingOrBuilder(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.TrainingInfoProtoOrBuilder.getInitializationBindingOrBuilder(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.ModelProto.Builder.getMetadataPropsOrBuilder(int index) Named metadata values; keys should be distinct.OnnxMl.ModelProto.getMetadataPropsOrBuilder(int index) Named metadata values; keys should be distinct.OnnxMl.ModelProtoOrBuilder.getMetadataPropsOrBuilder(int index) Named metadata values; keys should be distinct.OnnxMl.TensorAnnotation.Builder.getQuantParameterTensorNamesOrBuilder(int index) <key, value> pairs to annotate tensor specified by <tensor_name> above.OnnxMl.TensorAnnotation.getQuantParameterTensorNamesOrBuilder(int index) <key, value> pairs to annotate tensor specified by <tensor_name> above.OnnxMl.TensorAnnotationOrBuilder.getQuantParameterTensorNamesOrBuilder(int index) <key, value> pairs to annotate tensor specified by <tensor_name> above.OnnxMl.TrainingInfoProto.Builder.getUpdateBindingOrBuilder(int index) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProto.getUpdateBindingOrBuilder(int index) Gradient-based training is usually an iterative procedure.OnnxMl.TrainingInfoProtoOrBuilder.getUpdateBindingOrBuilder(int index) Gradient-based training is usually an iterative procedure.Methods in ai.onnx.proto that return types with arguments of type OnnxMl.StringStringEntryProtoOrBuilderModifier and TypeMethodDescriptionList<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TensorProto.Builder.getExternalDataOrBuilderList()Data can be stored inside the protobuf file using type-specific fields or raw_data.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TensorProto.getExternalDataOrBuilderList()Data can be stored inside the protobuf file using type-specific fields or raw_data.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TensorProtoOrBuilder.getExternalDataOrBuilderList()Data can be stored inside the protobuf file using type-specific fields or raw_data.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TrainingInfoProto.Builder.getInitializationBindingOrBuilderList()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.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TrainingInfoProto.getInitializationBindingOrBuilderList()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.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TrainingInfoProtoOrBuilder.getInitializationBindingOrBuilderList()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.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.ModelProto.Builder.getMetadataPropsOrBuilderList()Named metadata values; keys should be distinct.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.ModelProto.getMetadataPropsOrBuilderList()Named metadata values; keys should be distinct.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.ModelProtoOrBuilder.getMetadataPropsOrBuilderList()Named metadata values; keys should be distinct.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TensorAnnotation.Builder.getQuantParameterTensorNamesOrBuilderList()<key, value> pairs to annotate tensor specified by <tensor_name> above.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TensorAnnotation.getQuantParameterTensorNamesOrBuilderList()<key, value> pairs to annotate tensor specified by <tensor_name> above.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TensorAnnotationOrBuilder.getQuantParameterTensorNamesOrBuilderList()<key, value> pairs to annotate tensor specified by <tensor_name> above.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TrainingInfoProto.Builder.getUpdateBindingOrBuilderList()Gradient-based training is usually an iterative procedure.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TrainingInfoProto.getUpdateBindingOrBuilderList()Gradient-based training is usually an iterative procedure.List<? extends OnnxMl.StringStringEntryProtoOrBuilder> OnnxMl.TrainingInfoProtoOrBuilder.getUpdateBindingOrBuilderList()Gradient-based training is usually an iterative procedure.