Uses of Class
tensorflow.serving.Model.ModelSpec
Packages that use Model.ModelSpec
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Uses of Model.ModelSpec in tensorflow.serving
Methods in tensorflow.serving that return Model.ModelSpecModifier and TypeMethodDescriptionModel.ModelSpec.Builder.build()Model.ModelSpec.Builder.buildPartial()static Model.ModelSpecModel.ModelSpec.getDefaultInstance()Model.ModelSpec.Builder.getDefaultInstanceForType()Model.ModelSpec.getDefaultInstanceForType()Classification.ClassificationRequest.Builder.getModelSpec()Model Specification.Classification.ClassificationRequest.getModelSpec()Model Specification.Classification.ClassificationRequestOrBuilder.getModelSpec()Model Specification.Classification.ClassificationResponse.Builder.getModelSpec()Effective Model Specification used for classification.Classification.ClassificationResponse.getModelSpec()Effective Model Specification used for classification.Classification.ClassificationResponseOrBuilder.getModelSpec()Effective Model Specification used for classification.GetModelMetadata.GetModelMetadataRequest.Builder.getModelSpec()Model Specification indicating which model we are querying for metadata.GetModelMetadata.GetModelMetadataRequest.getModelSpec()Model Specification indicating which model we are querying for metadata.GetModelMetadata.GetModelMetadataRequestOrBuilder.getModelSpec()Model Specification indicating which model we are querying for metadata.GetModelMetadata.GetModelMetadataResponse.Builder.getModelSpec()Model Specification indicating which model this metadata belongs to.GetModelMetadata.GetModelMetadataResponse.getModelSpec()Model Specification indicating which model this metadata belongs to.GetModelMetadata.GetModelMetadataResponseOrBuilder.getModelSpec()Model Specification indicating which model this metadata belongs to.GetModelStatus.GetModelStatusRequest.Builder.getModelSpec()Model Specification.GetModelStatus.GetModelStatusRequest.getModelSpec()Model Specification.GetModelStatus.GetModelStatusRequestOrBuilder.getModelSpec()Model Specification.Inference.InferenceResult.Builder.getModelSpec().tensorflow.serving.ModelSpec model_spec = 1;Inference.InferenceResult.getModelSpec().tensorflow.serving.ModelSpec model_spec = 1;Inference.InferenceResultOrBuilder.getModelSpec().tensorflow.serving.ModelSpec model_spec = 1;Inference.InferenceTask.Builder.getModelSpec()Model Specification.Inference.InferenceTask.getModelSpec()Model Specification.Inference.InferenceTaskOrBuilder.getModelSpec()Model Specification.Logging.LogMetadata.Builder.getModelSpec().tensorflow.serving.ModelSpec model_spec = 1;Logging.LogMetadata.getModelSpec().tensorflow.serving.ModelSpec model_spec = 1;Logging.LogMetadataOrBuilder.getModelSpec().tensorflow.serving.ModelSpec model_spec = 1;Predict.PredictRequest.Builder.getModelSpec()Model Specification.Predict.PredictRequest.getModelSpec()Model Specification.Predict.PredictRequestOrBuilder.getModelSpec()Model Specification.Predict.PredictResponse.Builder.getModelSpec()Effective Model Specification used to process PredictRequest.Predict.PredictResponse.getModelSpec()Effective Model Specification used to process PredictRequest.Predict.PredictResponseOrBuilder.getModelSpec()Effective Model Specification used to process PredictRequest.RegressionOuterClass.RegressionRequest.Builder.getModelSpec()Model Specification.RegressionOuterClass.RegressionRequest.getModelSpec()Model Specification.RegressionOuterClass.RegressionRequestOrBuilder.getModelSpec()Model Specification.RegressionOuterClass.RegressionResponse.Builder.getModelSpec()Effective Model Specification used for regression.RegressionOuterClass.RegressionResponse.getModelSpec()Effective Model Specification used for regression.RegressionOuterClass.RegressionResponseOrBuilder.getModelSpec()Effective Model Specification used for regression.SessionServiceOuterClass.SessionRunRequest.Builder.getModelSpec()Model Specification.SessionServiceOuterClass.SessionRunRequest.getModelSpec()Model Specification.SessionServiceOuterClass.SessionRunRequestOrBuilder.getModelSpec()Model Specification.SessionServiceOuterClass.SessionRunResponse.Builder.getModelSpec()Effective Model Specification used for session run.SessionServiceOuterClass.SessionRunResponse.getModelSpec()Effective Model Specification used for session run.SessionServiceOuterClass.SessionRunResponseOrBuilder.getModelSpec()Effective Model Specification used for session run.static Model.ModelSpecModel.ModelSpec.parseDelimitedFrom(InputStream input) static Model.ModelSpecModel.ModelSpec.parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static Model.ModelSpecModel.ModelSpec.parseFrom(byte[] data) static Model.ModelSpecModel.ModelSpec.parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static Model.ModelSpecModel.ModelSpec.parseFrom(com.google.protobuf.ByteString data) static Model.ModelSpecModel.ModelSpec.parseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static Model.ModelSpecModel.ModelSpec.parseFrom(com.google.protobuf.CodedInputStream input) static Model.ModelSpecModel.ModelSpec.parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static Model.ModelSpecModel.ModelSpec.parseFrom(InputStream input) static Model.ModelSpecModel.ModelSpec.parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) static Model.ModelSpecModel.ModelSpec.parseFrom(ByteBuffer data) static Model.ModelSpecModel.ModelSpec.parseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry) Methods in tensorflow.serving that return types with arguments of type Model.ModelSpecModifier and TypeMethodDescriptioncom.google.protobuf.Parser<Model.ModelSpec> Model.ModelSpec.getParserForType()static com.google.protobuf.Parser<Model.ModelSpec> Model.ModelSpec.parser()Methods in tensorflow.serving with parameters of type Model.ModelSpecModifier and TypeMethodDescriptionModel.ModelSpec.Builder.mergeFrom(Model.ModelSpec other) Classification.ClassificationRequest.Builder.mergeModelSpec(Model.ModelSpec value) Model Specification.Classification.ClassificationResponse.Builder.mergeModelSpec(Model.ModelSpec value) Effective Model Specification used for classification.GetModelMetadata.GetModelMetadataRequest.Builder.mergeModelSpec(Model.ModelSpec value) Model Specification indicating which model we are querying for metadata.GetModelMetadata.GetModelMetadataResponse.Builder.mergeModelSpec(Model.ModelSpec value) Model Specification indicating which model this metadata belongs to.GetModelStatus.GetModelStatusRequest.Builder.mergeModelSpec(Model.ModelSpec value) Model Specification.Inference.InferenceResult.Builder.mergeModelSpec(Model.ModelSpec value) .tensorflow.serving.ModelSpec model_spec = 1;Inference.InferenceTask.Builder.mergeModelSpec(Model.ModelSpec value) Model Specification.Logging.LogMetadata.Builder.mergeModelSpec(Model.ModelSpec value) .tensorflow.serving.ModelSpec model_spec = 1;Predict.PredictRequest.Builder.mergeModelSpec(Model.ModelSpec value) Model Specification.Predict.PredictResponse.Builder.mergeModelSpec(Model.ModelSpec value) Effective Model Specification used to process PredictRequest.RegressionOuterClass.RegressionRequest.Builder.mergeModelSpec(Model.ModelSpec value) Model Specification.RegressionOuterClass.RegressionResponse.Builder.mergeModelSpec(Model.ModelSpec value) Effective Model Specification used for regression.SessionServiceOuterClass.SessionRunRequest.Builder.mergeModelSpec(Model.ModelSpec value) Model Specification.SessionServiceOuterClass.SessionRunResponse.Builder.mergeModelSpec(Model.ModelSpec value) Effective Model Specification used for session run.static Model.ModelSpec.BuilderModel.ModelSpec.newBuilder(Model.ModelSpec prototype) Classification.ClassificationRequest.Builder.setModelSpec(Model.ModelSpec value) Model Specification.Classification.ClassificationResponse.Builder.setModelSpec(Model.ModelSpec value) Effective Model Specification used for classification.GetModelMetadata.GetModelMetadataRequest.Builder.setModelSpec(Model.ModelSpec value) Model Specification indicating which model we are querying for metadata.GetModelMetadata.GetModelMetadataResponse.Builder.setModelSpec(Model.ModelSpec value) Model Specification indicating which model this metadata belongs to.GetModelStatus.GetModelStatusRequest.Builder.setModelSpec(Model.ModelSpec value) Model Specification.Inference.InferenceResult.Builder.setModelSpec(Model.ModelSpec value) .tensorflow.serving.ModelSpec model_spec = 1;Inference.InferenceTask.Builder.setModelSpec(Model.ModelSpec value) Model Specification.Logging.LogMetadata.Builder.setModelSpec(Model.ModelSpec value) .tensorflow.serving.ModelSpec model_spec = 1;Predict.PredictRequest.Builder.setModelSpec(Model.ModelSpec value) Model Specification.Predict.PredictResponse.Builder.setModelSpec(Model.ModelSpec value) Effective Model Specification used to process PredictRequest.RegressionOuterClass.RegressionRequest.Builder.setModelSpec(Model.ModelSpec value) Model Specification.RegressionOuterClass.RegressionResponse.Builder.setModelSpec(Model.ModelSpec value) Effective Model Specification used for regression.SessionServiceOuterClass.SessionRunRequest.Builder.setModelSpec(Model.ModelSpec value) Model Specification.SessionServiceOuterClass.SessionRunResponse.Builder.setModelSpec(Model.ModelSpec value) Effective Model Specification used for session run.