# The name of library
library_name: mobilenet
target_abis: [arm64-v8a]
model_graph_format: file
model_data_format: file
models:
  mobilenet_v1: # model tag, which will be used in model loading and must be specific.
    platform: onnx
    # path to your onnx model file. Support local path, http:// and https://
    model_file_path: https://cnbj1.fds.api.xiaomi.com/mace/miai-models/mobilenet-v1/mobilenet-v1-1.0.pb
    # sha256_checksum of your model's onnx file.
    # use this command to get the sha256_checksum: sha256sum path/to/your/pb/file
    model_sha256_checksum: 71b10f540ece33c49a7b51f5d4095fc9bd78ce46ebf0300487b2ee23d71294e6
    # define your model's interface
    # if there multiple inputs or outputs, write like blow:
    # subgraphs:
    # - input_tensors:
    #     - input0
    #     - input1
    #   input_shapes:
    #     - 1,224,224,3
    #     - 1,224,224,3
    #    output_tensors:
    #      - output0
    #      - output1
    #    output_shapes:
    #      - 1,1001
    #      - 1,1001
    subgraphs:
      - input_tensors:
          - input
        input_shapes:
          - 1,224,224,3
        output_tensors:
          - MobilenetV1/Predictions/Reshape_1
        output_shapes:
          - 1,1001
        # onnx backend framwork for validation. Suppport pytorch/caffe/tensorflow. Default is tensorflow.
        backend: tensorflow
    # cpu, gpu or cpu+gpu
    runtime: cpu+gpu
    winograd: 0