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fix: Mixtral compatibility with transformers >=5.0 fused MoE API #451

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fix: Mixtral compatibility with transformers >=5.0 fused MoE API #451

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72 changes: 63 additions & 9 deletions llmc/models/mixtral.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,10 @@
from .base_model import BaseModel


def _has_legacy_moe(block):
return hasattr(block, 'block_sparse_moe')


@MODEL_REGISTRY
class Mixtral(BaseModel):
def __init__(self, config, device_map=None, use_cache=False):
Expand Down Expand Up @@ -36,11 +40,27 @@ def get_layernorms_in_block(self, block):
}

def get_extra_modules(self, block):
if _has_legacy_moe(block):
return {
'block_sparse_moe': block.block_sparse_moe
}
return {
'block_sparse_moe': block.block_sparse_moe
'mlp': block.mlp
}

def get_moe_gate(self, block):
if _has_legacy_moe(block):
return block.block_sparse_moe.gate
return block.mlp.gate

def get_subsets_in_block(self, block):
if _has_legacy_moe(block):
return self._get_subsets_legacy(block)
return self._get_subsets_fused(block)

def _get_subsets_legacy(self, block):
"""transformers <5.0: block.block_sparse_moe with ModuleList experts."""
moe = block.block_sparse_moe
return [
{
'layers': {
Expand All @@ -62,25 +82,59 @@ def get_subsets_in_block(self, block):
},
{
'layers': {
**{f'block_sparse_moe.experts.{i}.w1': block.block_sparse_moe.experts[i].w1 for i in range(len(block.block_sparse_moe.experts))}, # noqa
**{f'block_sparse_moe.experts.{i}.w3': block.block_sparse_moe.experts[i].w3 for i in range(len(block.block_sparse_moe.experts))}, # noqa
'block_sparse_moe.gate': block.block_sparse_moe.gate,
**{f'block_sparse_moe.experts.{i}.w1': moe.experts[i].w1 for i in range(len(moe.experts))}, # noqa
**{f'block_sparse_moe.experts.{i}.w3': moe.experts[i].w3 for i in range(len(moe.experts))}, # noqa
'block_sparse_moe.gate': moe.gate,
},
'prev_op': [block.post_attention_layernorm],
'input': ['block_sparse_moe'],
'inspect': block.block_sparse_moe,
'inspect': moe,
'has_kwargs': False,
'is_mlp': True,
},
*[
{
'layers': {f'block_sparse_moe.experts.{i}.w2': block.block_sparse_moe.experts[i].w2}, # noqa
'prev_op': [block.block_sparse_moe.experts[i].w3],
'layers': {f'block_sparse_moe.experts.{i}.w2': moe.experts[i].w2},
'prev_op': [moe.experts[i].w3],
'input': [f'block_sparse_moe.experts.{i}.w2'],
'inspect': block.block_sparse_moe.experts[i].w2,
'inspect': moe.experts[i].w2,
'has_kwargs': False,
'is_mlp': True,
}
for i in range(len(block.block_sparse_moe.experts))
for i in range(len(moe.experts))
],
]

def _get_subsets_fused(self, block):
"""transformers >=5.0: block.mlp with fused MixtralExperts."""
moe = block.mlp
return [
{
'layers': {
'self_attn.q_proj': block.self_attn.q_proj,
'self_attn.k_proj': block.self_attn.k_proj,
'self_attn.v_proj': block.self_attn.v_proj,
},
'prev_op': [block.input_layernorm],
'input': ['self_attn.q_proj'],
'inspect': block.self_attn,
'has_kwargs': True,
},
{
'layers': {'self_attn.o_proj': block.self_attn.o_proj},
'prev_op': [block.self_attn.v_proj],
'input': ['self_attn.o_proj'],
'inspect': block.self_attn.o_proj,
'has_kwargs': False,
},
{
'layers': {
'mlp.gate': moe.gate,
},
'prev_op': [block.post_attention_layernorm],
'input': ['mlp'],
'inspect': moe,
'has_kwargs': False,
'is_mlp': True,
},
]