Feat (mx): gptq compatibility and quant tests #1013
Conversation
Giuseppe5
changed the title
| @@ -14,6 +14,11 @@ def group_dim(self): | |||
| def group_size(self): | |||
| return self.quant_injector.group_size | |||
|
|
|||
| def apply_input_view(self, x): | |||
There was a problem hiding this comment.
Worth making a GroupwiseQuantProxyMixin which provides these functions? Looks like that a lot is shared between GroupwiseWeightQuantProxyFromInjector & GroupwiseActQuantProxyFromInjector...
There was a problem hiding this comment.
After further review, I seem to recall there was some issue with Proxy Mixins (perhaps with dependency injection) results in the ExportMixin needing to be in a certain location. I'll leave this for now - we can revisit at another time.
src/brevitas/graph/gpxq.py
Outdated
| @@ -232,7 +238,8 @@ def process_input(self, inp): | |||
| if isinstance(inp, IntQuantTensor): | |||
| if is_quant_enabled and self.quant_metadata is None: | |||
| self.quant_metadata = _CachedIO(inp, metadata_only=True) | |||
| inp = inp.value | |||
| if isinstance(inp, QuantTensor): | |||
There was a problem hiding this comment.
When could this not be True? I see you've added this check, but it's not obvious to me. Can inp get modified in-place by _CachedIO?
There was a problem hiding this comment.
I think the answer to my question is "no", so I've removed that check in 1f0933f.
|
Rebased after #1012 was merged. Note, had to resolve some merge conflicts, but I think I made all the right choices about which bits to keep or not... |
|
The failing tests seem to be a github actions issue rather than a real issue. I can run the failing test suite ( Merging, and will open another issue if this becomes a regular thing. |
Depends on #1011 and #1012
Added tests for MX and FloatQuant, with some restrictions;