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[Transform] Spinquant R3 #1778

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[Transform] Spinquant R3 #1778

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46 changes: 31 additions & 15 deletions src/llmcompressor/modifiers/transform/spinquant/base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -119,16 +119,17 @@ def on_initialize(self, state: State, **kwargs) -> bool:

self.mappings = infer_mapping_from_model(state.model)
self.norm_mappings = infer_norm_mapping_from_model(state.model)
head_dim = self._infer_head_dim(state.model)

config_groups = {}
if SpinquantRotation.R1 in self.rotations:
config_groups["R1"] = self._create_r1_scheme()

if SpinquantRotation.R2 in self.rotations:
config_groups["R2"] = self._create_r2_scheme(state.model)
config_groups["R2"] = self._create_r2_scheme(head_dim)

if SpinquantRotation.R3 in self.rotations:
config_groups["R3"] = self._create_r3_scheme()
config_groups["R3"] = self._create_r3_scheme(head_dim)

if SpinquantRotation.R4 in self.rotations:
config_groups["R4"] = self._create_r4_scheme()
Expand Down Expand Up @@ -209,16 +210,7 @@ def _create_r1_scheme(self) -> TransformScheme:
],
)

def _create_r2_scheme(self, model: PreTrainedModel) -> TransformScheme:
config = model.config

if hasattr(config, "head_dim"):
head_dim = config.head_dim
elif hasattr(config, "hidden_size") and hasattr(config, "num_attention_heads"):
head_dim = config.hidden_size // config.num_attention_heads
else:
raise NotImplementedError()

def _create_r2_scheme(self, head_dim: int) -> TransformScheme:
return TransformScheme(
type=self.transform_type,
randomize=self.randomize,
Expand All @@ -235,9 +227,23 @@ def _create_r2_scheme(self, model: PreTrainedModel) -> TransformScheme:
],
)

def _create_r3_scheme(self) -> TransformScheme:
raise NotImplementedError(
"SpinQuant R3 rotations will be added in a future release"
def _create_r3_scheme(self, head_dim: int) -> TransformScheme:
return TransformScheme(
type=self.transform_type,
randomize=self.randomize,
requires_grad=self.learnable,
precision=self.precision,
head_dim=head_dim,
apply=[
TransformArgs(
targets=[self.mappings.attn],
location="q_attn",
),
TransformArgs(
targets=[self.mappings.attn],
location="k_cache",
),
],
)

def _create_r4_scheme(self) -> TransformScheme:
Expand All @@ -258,3 +264,13 @@ def _create_r4_scheme(self) -> TransformScheme:
),
],
)

def _infer_head_dim(self, model: PreTrainedModel) -> int:
config = model.config

if hasattr(config, "head_dim"):
return config.head_dim
elif hasattr(config, "hidden_size") and hasattr(config, "num_attention_heads"):
return config.hidden_size // config.num_attention_heads
else:
raise NotImplementedError()
2 changes: 2 additions & 0 deletions src/llmcompressor/modifiers/transform/spinquant/mappings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@ class SpinQuantMapping(BaseModel):

embedding: str

attn: str
attn_q: str
attn_k: str
attn_v: str
Expand All @@ -50,6 +51,7 @@ def cast_to_list(cls, value):

_default_mappings = SpinQuantMapping(
embedding="re:.*embed_tokens$",
attn="re:.*self_attn$",
attn_q="re:.*q_proj$",
attn_k="re:.*k_proj$",
attn_v="re:.*v_proj$",
Expand Down