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use new fp32 softmax kernel #11776

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Aug 13, 2024
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use new fp32 softmax kernel #11776

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5 changes: 3 additions & 2 deletions python/llm/src/ipex_llm/transformers/models/minicpmv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,8 +42,9 @@ def siglip_attention_forward(
if attention_mask is not None:
attn_weights = attn_weights + attention_mask

# upcast attention to fp32
attn_weights = torch.nn.functional.softmax(attn_weights, dim=-1)
import xe_addons
xe_addons.attn_softmax_inplaced(attn_weights)

attn_weights = torch.nn.functional.dropout(attn_weights, p=self.dropout, training=self.training)
attn_output = torch.matmul(attn_weights, value_states)

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6 changes: 3 additions & 3 deletions python/llm/src/ipex_llm/transformers/models/phi3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -184,9 +184,9 @@ def attention_forward(
if attention_mask is not None:
attn_weights = attn_weights + attention_mask

# upcast attention to fp32
attn_weights = torch.nn.functional.softmax(attn_weights, dim=-1,
dtype=torch.float32).to(value_states.dtype)
import xe_addons
xe_addons.attn_softmax_inplaced(attn_weights)

attn_weights = torch.nn.functional.dropout(attn_weights, p=self.attention_dropout,
training=self.training)
attn_output = torch.matmul(attn_weights, value_states)
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