[Quant] Molmo SupportsQuant

[kylesayrs]

Purpose

• Add SupportsQuant interface to Molo models which
  • Initializes the quant_config attribute and updates the quant_config with the relevant packed_modules_mapping
  • Marks a model as being capable of supporting quantized inference
  • In the future, will check if a model has been correctly defined, for example if prefixes and quant_configs have been passed correctly
• This mixin will replace the configure_quant_config function after it has been added to a sufficient number of models
• These changes reflect the issue that configure_quant_config assumes that all packed_modules_mappings will be declared prior to initialization. In reality, some models are submodels of each other, so their mappings can only be determined at init time.
  • Using a mixin which updates after class is initialized but the mapping before the parameters init guarantees that the config is up to date w.r.t. mappings before the parameters init

Prerequisites

• [Quant] Add SupportsQuant to phi3 and clip #13104

Changes

• Add SupportsQuant interface to MolmoVisionBackbone, MolmoModel, and MolmoForCausalLM

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[DarkLight1337]

Can we remove this from L1440 now that it's defined in the inner model?

[kylesayrs]

I believe that that line is still required by SupportsLoRA

vllm/vllm/lora/models.py

Lines 342 to 343 in ce77eb9

	self.packed_modules_mapping = copy.deepcopy(
	self.model.packed_modules_mapping)

[kylesayrs]

Theoretically, the packed_modules_mapping attribute should be defined at the lowest level possible, ie on every Module with packed modules.

I think in practice we should add the SupportsQuant and packed_modules_mapping to all classes which define a load_weights method, as it seems like these are the classes which are composable with other models

[DarkLight1337]

I see, thanks for the explanation!

I think in practice we should add the SupportsQuant and packed_modules_mapping to all classes which define a load_weights method, as it seems like these are the classes which are composable with other models

Sounds good to me!