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mediapipe/mediapipe/calculators/tflite/tflite_inference_calculator.proto
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MediaPipe Teamandjqtang 137867d088 Project import generated by Copybara.
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2019-12-02 17:54:10 -08:00

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// Copyright 2019 The MediaPipe Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
syntax = "proto2";
package mediapipe;
import "mediapipe/framework/calculator.proto";
// Full Example:
//
// node {
// calculator: "TfLiteInferenceCalculator"
// input_stream: "TENSOR_IN:image_tensors"
// output_stream: "TENSOR_OUT:result_tensors"
// options {
// [mediapipe.TfLiteInferenceCalculatorOptions.ext] {
// model_path: "model.tflite"
// use_gpu: true
// }
// }
// }
//
message TfLiteInferenceCalculatorOptions {
extend mediapipe.CalculatorOptions {
optional TfLiteInferenceCalculatorOptions ext = 233867213;
}
// Path to the TF Lite model (ex: /path/to/modelname.tflite).
// On mobile, this is generally just modelname.tflite.
optional string model_path = 1;
// Whether the TF Lite GPU or CPU backend should be used. Effective only when
// input tensors are on CPU. For input tensors on GPU, GPU backend is always
// used.
optional bool use_gpu = 2 [default = false];
// Android only. When true, an NNAPI delegate will be used for inference.
// If NNAPI is not available, then the default CPU delegate will be used
// automatically.
optional bool use_nnapi = 3 [default = false];
}