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sdxl bug-fix: scaled_dot_product_attention api dtype #573

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merged 2 commits into from
Jul 27, 2024
Merged

sdxl bug-fix: scaled_dot_product_attention api dtype #573

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1df43ed
sdxl decoder attn type bug-fix
Fzilan Jul 1, 2024
1cd4b13
fix
Fzilan Jul 22, 2024
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9 changes: 5 additions & 4 deletions examples/stable_diffusion_xl/gm/modules/transformers/transformers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,8 @@

def scaled_dot_product_attention(query, key, value, attn_mask=None, dtype=None):
# force fp16 precision calculation
_dtype = query.dtype
origin_dtype = query.dtype
dtype = origin_dtype if dtype is None else dtype
if dtype is not None:
query, key, value = query.astype(dtype), key.astype(dtype), value.astype(dtype)

Expand All @@ -19,14 +20,14 @@ def scaled_dot_product_attention(query, key, value, attn_mask=None, dtype=None):
attn_weight = ops.softmax(
ops.cast(ops.matmul(query, key.swapaxes(-2, -1)) / (query.shape[-1] ** 0.5) + attn_mask, ms.float32),
axis=-1,
).astype(_dtype)
).astype(dtype)
else:
attn_weight = ops.softmax(
ops.cast(ops.matmul(query, key.swapaxes(-2, -1)) / (query.shape[-1] ** 0.5), ms.float32), axis=-1
).astype(_dtype)
).astype(dtype)

out = ops.matmul(attn_weight, value)
out = out.astype(_dtype)
out = out.astype(origin_dtype)

return out

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