model:                                               # mandatory. used to specify model specific information.
  name: gpt2 
  framework: onnxrt_integerops                       # mandatory. possible values are tensorflow, mxnet, pytorch, pytorch_ipex, onnxrt_integerops and onnxrt_qlinearops.

quantization:
  approach: post_training_dynamic_quant              # optional. default value is post_training_static_quant.
  op_wise: {
     'Gather_*': {
     'activation':  {'dtype': ['fp32']},
     'weight': {'dtype': ['fp32']}
     }
   }

evaluation:
  accuracy:
    metric:
      MSE: 
        compare_label: False

tuning:
  accuracy_criterion:
    relative:  0.999                                 # optional. default value is relative, other value is absolute. this example allows relative accuracy loss: 1%.
  exit_policy:
    timeout: 0                                       # optional. tuning timeout (seconds). default value is 0 which means early stop. combine with max_trials field to decide when to exit.
  random_seed: 9527                                  # optional. random seed for deterministic tuning.
