package tensorflow.serving

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open source marker; do not remove PredictionService provides access to machine-learned models loaded by model_servers.

• rpc Classify (ClassificationRequest, ClassificationResponse)

  prediction_service.proto:17

  Classify.

  message ClassificationRequest

  classification.proto:32

  • optional ModelSpec model_spec = 1

    Model Specification.

  • optional Input input = 2

    Input data.

  message ClassificationResponse

  classification.proto:40

  • optional ClassificationResult result = 1

    Result of the classification.

• rpc GetModelMetadata (GetModelMetadataRequest, GetModelMetadataResponse)

  prediction_service.proto:29

  GetModelMetadata - provides access to metadata for loaded models.

  message GetModelMetadataRequest

  get_model_metadata.proto:15

  • optional ModelSpec model_spec = 1

    Model Specification indicating which model we are querying for metadata.

  • repeated string metadata_field = 2

    Metadata fields to get. Currently supported: "signature_def".

  message GetModelMetadataResponse

  get_model_metadata.proto:22

  • optional ModelSpec model_spec = 1

    Model Specification indicating which model this metadata belongs to.

  • map<string, google.protobuf.Any> metadata = 2

    Map of metadata field name to metadata field. The options for metadata field name are listed in GetModelMetadataRequest. Currently supported: "signature_def".

• rpc MultiInference (MultiInferenceRequest, MultiInferenceResponse)

  prediction_service.proto:26

  MultiInference API for multi-headed models.

  message MultiInferenceRequest

  inference.proto:43

  Inference request containing one or more requests.

  • repeated InferenceTask tasks = 1

    Inference tasks.

  • optional Input input = 2

    Input data.

  message MultiInferenceResponse

  inference.proto:52

  Inference request containing one or more responses.

  • repeated InferenceResult results = 1

    List of results; one for each InferenceTask in the request, returned in the same order as the request.

• rpc Predict (PredictRequest, PredictResponse)

  prediction_service.proto:23

  Predict -- provides access to loaded TensorFlow model.

  message PredictRequest

  predict.proto:12

  PredictRequest specifies which TensorFlow model to run, as well as how inputs are mapped to tensors and how outputs are filtered before returning to user.

  • optional ModelSpec model_spec = 1

    Model Specification.

  • map<string, TensorProto> inputs = 2

    Input tensors. Names of input tensor are alias names. The mapping from aliases to real input tensor names is stored in the SavedModel export as a prediction SignatureDef under the 'inputs' field.

  • repeated string output_filter = 3

    Output filter. Names specified are alias names. The mapping from aliases to real output tensor names is stored in the SavedModel export as a prediction SignatureDef under the 'outputs' field. Only tensors specified here will be run/fetched and returned, with the exception that when none is specified, all tensors specified in the named signature will be run/fetched and returned.

  message PredictResponse

  predict.proto:33

  Response for PredictRequest on successful run.

  • map<string, TensorProto> outputs = 1

    Output tensors.

• rpc Regress (RegressionRequest, RegressionResponse)

  prediction_service.proto:20

  Regress.

  message RegressionRequest

  regression.proto:23

  • optional ModelSpec model_spec = 1

    Model Specification.

  • optional Input input = 2

    Input data.

  message RegressionResponse

  regression.proto:31

  • optional RegressionResult result = 1

A single class.

Used in: Classifications

• string label = 1

  Label or name of the class.

• float score = 2

  Score for this class (e.g., the probability the item belongs to this class).

Contains one result per input example, in the same order as the input in ClassificationRequest.

Used in: ClassificationResponse, InferenceResult

• repeated Classifications classifications = 1

List of classes for a single item (tensorflow.Example).

Used in: ClassificationResult

• repeated Class classes = 1

Specifies one or more fully independent input Examples. See examples at: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/example/example.proto

Used in: Input

• repeated Example examples = 1

Specifies one or more independent input Examples, with a common context Example. The common use case for context is to cleanly and optimally specify some features that are common across multiple examples. See example below with a search query as the context and multiple restaurants to perform some inference on. context: { feature: { key : "query" value: { bytes_list: { value: [ "pizza" ] } } } } examples: { feature: { key : "cuisine" value: { bytes_list: { value: [ "Pizzeria" ] } } } } examples: { feature: { key : "cuisine" value: { bytes_list: { value: [ "Taqueria" ] } } } } Implementations of ExampleListWithContext merge the context Example into each of the Examples. Note that feature keys must not be duplicated between the Examples and context Example, or the behavior is undefined. See also: tensorflow/core/example/example.proto https://developers.google.com/protocol-buffers/docs/proto3#maps

Used in: Input

• repeated Example examples = 1

• optional Example context = 2

Inference result, matches the type of request or is an error.

Used in: MultiInferenceResponse

• optional ModelSpec model_spec = 1

• oneof result

  • ClassificationResult classification_result = 2

  • RegressionResult regression_result = 3

Inference request such as classification, regression, etc...

Used in: MultiInferenceRequest

• optional ModelSpec model_spec = 1

• string method_name = 2

  Signature's method_name. Should be one of the method names defined in third_party/tensorflow/python/saved_model/signature_constants.py. e.g. "tensorflow/serving/classify".

Used in: ClassificationRequest, MultiInferenceRequest, RegressionRequest

• oneof kind

  • ExampleList example_list = 1

  • ExampleListWithContext example_list_with_context = 2

Metadata for an inference request such as the model name and version.

Used in: ClassificationRequest, GetModelMetadataRequest, GetModelMetadataResponse, InferenceResult, InferenceTask, PredictRequest, RegressionRequest

• string name = 1

  Required servable name.

• optional google.protobuf.Int64Value version = 2

  Optional version. If unspecified, will use the latest (numerical) version. Typically not needed unless coordinating across multiple models that were co-trained and/or have inter-dependencies on the versions used at inference time.

• string signature_name = 3

  A named signature to evaluate. If unspecified, the default signature will be used.

Regression result for a single item (tensorflow.Example).

Used in: RegressionResult

• float value = 1

Contains one result per input example, in the same order as the input in RegressionRequest.

Used in: InferenceResult, RegressionResponse

• repeated Regression regressions = 1

Message returned for "signature_def" field.

• map<string, SignatureDef> signature_def = 1