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@WeiweiZhang1 WeiweiZhang1 commented Jan 23, 2026

Description

Please briefly describe your main changes, the motivation.

Type of Change

  • Bug fix
  • New feature
  • Documentation update
  • Performance improvement
  • Code refactoring
  • Other (please specify):

Related Issues

Fixes or relates to #1187

Checklist Before Submitting

  • My code has been tested locally.
  • Documentation has been updated as needed.
  • New or updated tests are included where applicable.

Signed-off-by: WeiweiZhang1 <weiwei1.zhang@intel.com>
Copilot AI review requested due to automatic review settings January 23, 2026 07:59
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Pull request overview

This PR removes duplicate arguments from quantization extra configuration by only saving attributes that differ from the default Scheme values, reducing redundancy in the saved configuration files.

Changes:

  • Modified export functions to filter extra_config entries, keeping only attributes that differ from scheme defaults
  • Updated test cases to verify that duplicate/default values are not present in extra_config
  • Added assertions to ensure extra_config contains only non-default attributes

Reviewed changes

Copilot reviewed 5 out of 5 changed files in this pull request and generated no comments.

Show a summary per file
File Description
auto_round/export/export_to_autoround/export_to_nvfp_mxfp.py Updated logic to save only non-equal keys in extra_config for both layer configs and regex configs
auto_round/export/export_to_autoround/export_to_fp8.py Changed iteration from scheme_keys to neq_keys to avoid saving default values
auto_round/export/export_to_autoround/export.py Added filtering logic for regex_config to save only attributes differing from scheme defaults
test/test_cuda/quantization/test_mix_bits.py Added assertions to verify extra_config excludes default values and removed redundant config entries from test data
test/test_cpu/quantization/test_mix_bits.py Added assertions to verify extra_config excludes default values and removed redundant config entries from test data

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2 participants