name: "similarity_model"
backend: "python"
max_batch_size: 128

parameters: {
  key: "EXECUTION_ENV_PATH",
  value: {
    # string_value: "/inspire/hdd/project/embodied-multimodality/public/cchang/env/audio.tar.gz"
    # string_value: "/inspire/hdd/project/embodied-multimodality/public/cchang/env/audio_clean.tar.gz"
    # string_value: "/inspire/hdd/project/embodied-multimodality/public/cchang/env_tar/audio_env.tar.gz"
    string_value: "/inspire/hdd/project/embodied-multimodality/public/cchang/env/mooncast/bin/python"
  }
}

input [
  {
    name: "AUDIO1"
    data_type: TYPE_STRING
    dims: [ 1 ]  # 音频路径
  },
  {
    name: "AUDIO2"
    data_type: TYPE_STRING
    dims: [ 1 ]  # 音频路径
  }
]

output [
  {
    name: "SIMILARITY"
    data_type: TYPE_FP32
    dims: [ 1 ]  # 相似度分数
  }
]

dynamic_batching {
  preferred_batch_size: [ 16, 32 ]
}

instance_group [
  {
    count: 1
    kind: KIND_GPU
  }
]