[Compressed Tensors] Allow configs with non-explicit ignores

[kylesayrs]

Purpose

• Allow for greater config flexibility by not requiring all layers to be listed in the ignore list
  • Any layers which do not match schemes are assumed to be ignored

Previously:

"quantization_config": {
  "config_groups": {
    "group_0": {
      "targets": [
        "re:.*attn.*_proj$",
      ],
    }
  },
  "ignore": [
    "layers.2.attn.indexer.weights_proj",
    "layers.4.attn.indexer.weights_proj",
    "layers.6.attn.indexer.weights_proj",
    "layers.8.attn.indexer.weights_proj",
    "layers.10.attn.indexer.weights_proj",
  ],
},

Now:

"quantization_config": {
  "config_groups": {
    "group_0": {
      "targets": [
        "re:.*attn.*_proj$",
      ],
    }
  },
  "ignore": [],
},

Changes

• Allow find_matched_target to return None, and treat a non-match against schemes as an ignored layer

Testing

• Added test_find_matched_target_returns_none_on_no_match
• Added test_get_scheme_dict_returns_none_on_no_match

[claude]

Claude Code Review

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[gemini-code-assist]

Code Review

This pull request refactors find_matched_target to return None instead of raising a ValueError when a target is not found, updating the calling logic in compressed_tensors.py to handle these cases explicitly. Feedback was provided regarding a potential AttributeError in get_scheme_dict if the retrieved scheme dictionary is None, along with a suggestion to avoid in-place modifications of the configuration dictionary.

[mgoin]

LGTM Kyle, thanks for cleaning up the ValueError. Can you add a unit test to solidify this expected behavior?

[dsikka]

LGTM but we should probably add a basic smoke test for this.