demo_models.yml

# The name of library
library_name: mobile_squeeze
# host, armeabi-v7a or arm64-v8a
target_abis: [arm64-v8a]
# soc's name or all
target_socs: [all]
# The build mode for model(s).
# 'code' for transferring model(s) into cpp code, 'file' for keeping model(s) in protobuf file(s) (.pb).
model_graph_format: code
# 'code' for transferring model data(s) into cpp code, 'file' for keeping model data(s) in file(s) (.data).
model_data_format: code
# One yaml config file can contain multi models' deployment info.
models:
  mobilenet_v1:
      platform: tensorflow
      model_file_path: https://cnbj1.fds.api.xiaomi.com/mace/miai-models/mobilenet-v1/mobilenet-v1-1.0.pb
      model_sha256_checksum: 71b10f540ece33c49a7b51f5d4095fc9bd78ce46ebf0300487b2ee23d71294e6
      subgraphs:
        - input_tensors:
            - input
          input_shapes:
            - 1,224,224,3
          output_tensors:
            - MobilenetV1/Predictions/Reshape_1
          output_shapes:
            - 1,1001
          validation_inputs_data:
            - https://cnbj1.fds.api.xiaomi.com/mace/inputs/dog.npy
      runtime: cpu+gpu
      limit_opencl_kernel_time: 0
      obfuscate: 0
      winograd: 0
  squeezenet_v11:
      platform: caffe
      model_file_path: http://cnbj1-inner-fds.api.xiaomi.net/mace/mace-models/squeezenet/SqueezeNet_v1.1/model.prototxt
      weight_file_path: http://cnbj1-inner-fds.api.xiaomi.net/mace/mace-models/squeezenet/SqueezeNet_v1.1/weight.caffemodel
      model_sha256_checksum: 625c952063da1569e22d2f499dc454952244d42cd8feca61f05502566e70ae1c
      weight_sha256_checksum: 72b912ace512e8621f8ff168a7d72af55910d3c7c9445af8dfbff4c2ee960142
      subgraphs:
        - input_tensors:
            - data
          input_shapes:
            - 1,227,227,3
          output_tensors:
            - prob
          output_shapes:
            - 1,1,1,1000
          accuracy_validation_script:
            - path/to/your/script
      runtime: cpu+gpu
      limit_opencl_kernel_time: 0
      obfuscate: 0
      winograd: 0