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43 changes: 31 additions & 12 deletions src/llmcompressor/modifiers/awq/base.py
Original file line number Diff line number Diff line change
Expand Up @@ -310,14 +310,24 @@ def _set_resolved_mappings(self, model: Module) -> None:
if not balance_layer:
continue

# exclude v_proj/o_proj mappings whose shapes are incompatible
# exclude v_proj->o_proj mappings whose shapes are incompatible
# https://github.com/mit-han-lab/llm-awq/pull/67#issuecomment-1681632777
if (
".v_proj" in layer_name
and ".o_proj" in balance_name
and isinstance(smooth_layer, torch.nn.Linear)
isinstance(smooth_layer, torch.nn.Linear)
and isinstance(balance_layer, torch.nn.Linear)
and smooth_layer.weight.shape != balance_layer.weight.shape
and ".o_proj" in balance_name
and (
(
".v_proj" in layer_name
and smooth_layer.out_features
!= balance_layer.in_features
)
or (
".qkv_proj" in layer_name
and smooth_layer.out_features
!= 3 * balance_layer.in_features
)
)
):
num_skipped_oproj_mappings += 1
continue
Expand Down Expand Up @@ -466,33 +476,42 @@ def _apply_smoothing(self, model: Module) -> None:
inp, w_mean, x_mean, module2inspect, balance_layers, fp16_output
)

scales = best_scales

@torch.no_grad()
def smooth(module):
with align_module_device(module):
scales = best_scales.to(module.weight.device)
if module in balance_layers:
module.weight.mul_(scales.view(1, -1).to(module.weight.device))
update_offload_parameter(
module,
"weight",
module.weight.mul_(scales.view(1, -1)),
)
elif module == smooth_layer:
if module.weight.ndim == 1:
update_offload_parameter(
module,
"weight",
module.weight.div(scales.to(module.weight.device)),
module.weight.div_(scales),
)
else:
# NOTE: edge case when smooth layer number of out_features
# is not equal to balance layer number of in_features
# e.g. when fused qkv_proj is used to smooth o_proj
# in this case, default to scaling the last output features
# because the desired smooth layer is v_proj
# https://github.com/casper-hansen/AutoAWQ/blob/main/awq/quantize/scale.py#L123
update_offload_parameter(
module,
"weight",
module.weight.div(
scales.view(-1, 1).to(module.weight.device)
module.weight[-scales.size(0) :].div_(
scales.view(-1, 1)
),
)
if hasattr(module, "bias") and module.bias is not None:
update_offload_parameter(
module,
"bias",
module.bias.div(scales.to(module.bias.device)),
module.bias.div_(scales),
)

parent = get_fsdp_parent(mapping.smooth_name, model)
Expand Down