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WeNet
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{
    "model_type": "ONNX",
    "npu_mode": "NPU3",
    "quant": {
      "input_configs": [
        {
            "tensor_name": "speech",
            "calibration_dataset": "./calibration_dataset/speech.tar.gz",
            "calibration_size": -1,
            "calibration_format": "Numpy"
        },
        {
          "tensor_name": "speech_lengths",
          "calibration_dataset": "./calibration_dataset/speech_lengths.tar.gz",
          "calibration_size": -1,
          "calibration_format": "Numpy"
      }
      ],
      "layer_configs": [
        {
            "start_tensor_names": ["DEFAULT"], 
            "end_tensor_names": ["DEFAULT"], 
            "data_type": "U16"
        } 
      ],
      "calibration_method": "MinMax",
      "conv_bias_data_type": "FP32",
      "disable_auto_refine_scale": true,
      "enable_smooth_quant": true,
      "precision_analysis": true,
      "precision_analysis_method": "EndToEnd",
      "transformer_opt_level": 1
    },
    "input_processors": [
      {
        "tensor_name": "speech",
        "src_dtype": "FP32"
      },
      {
        "tensor_name": "speech_lengths",
        "src_dtype": "S32"
      }
    ],
    "compiler": {
      "check": 0
    }
  }