conf_ipex.yaml

#
# Copyright (c) 2021 Intel Corporation
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# Licensed under the Apache License, Version 2.0 (the "License");
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#   http://www.apache.org/licenses/LICENSE-2.0
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version: 1.0

model:                                               # mandatory. used to specify model specific information.
  name: dlrm
  framework: pytorch_ipex                            # 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.
  calibration:
    sampling_size: 102400                               # optional. default value is 100. used to set how many samples should be used in calibration.
  model_wise:                                        # optional. tuning constraints on model-wise for advance user to reduce tuning space.
    weight:
      granularity: per_channel
      scheme: sym
      dtype: int8
      algorithm: minmax
    activation:
      granularity: per_tensor
      scheme: sym
      dtype: int8
      algorithm: minmax
tuning:
  accuracy_criterion:
    relative:  0.01                                  # 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.