#
# Copyright (c) 2021 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

version: 1.0

model:                                               # mandatory. used to specify model specific information.
  name: mp_handpose
  framework: onnxrt_qlinearops                       # mandatory. supported values are tensorflow, pytorch, pytorch_ipex, onnxrt_integer, onnxrt_qlinear or mxnet; allow new framework backend extension.

quantization:                                        # optional. tuning constraints on model-wise for advance user to reduce tuning space.
  approach: post_training_static_quant               # optional. default value is post_training_static_quant.                          
  calibration:
    dataloader:
      batch_size: 1
      dataset:
        dummy:
          shape: [1, 256, 256, 3]
          low: -1.0
          high: 1.0
          dtype: float32
          label: True

  model_wise:                                        # optional. tuning constraints on model-wise for advance user to reduce tuning space.
    weight:
      granularity: per_tensor
      scheme: asym
      dtype: int8
      algorithm: minmax
    activation:
      granularity: per_tensor
      scheme: asym
      dtype: int8
      algorithm: minmax

tuning:
  accuracy_criterion:
    relative:  0.02                                  # 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.