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authorKohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>2023-12-14 16:54:45 +0800
committerKohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>2023-12-14 16:54:45 +0800
commit0fb34b57b80b368f76a368c50569371c10382e12 (patch)
treecb32ad64211ac1670bae87946190c85abd40773e /modules/xpu_specific.py
parent39ebd5684b377157eca7034feec4596707cfa9c7 (diff)
parentaeaf1c510f1e7f246d892dad74122e0117a68a8c (diff)
Merge branch 'dev' into test-fp8
Diffstat (limited to 'modules/xpu_specific.py')
-rw-r--r--modules/xpu_specific.py9
1 files changed, 9 insertions, 0 deletions
diff --git a/modules/xpu_specific.py b/modules/xpu_specific.py
index d933c790..d8da94a0 100644
--- a/modules/xpu_specific.py
+++ b/modules/xpu_specific.py
@@ -48,3 +48,12 @@ if has_xpu:
CondFunc('torch.nn.modules.conv.Conv2d.forward',
lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)),
lambda orig_func, self, input: input.dtype != self.weight.data.dtype)
+ CondFunc('torch.bmm',
+ lambda orig_func, input, mat2, out=None: orig_func(input.to(mat2.dtype), mat2, out=out),
+ lambda orig_func, input, mat2, out=None: input.dtype != mat2.dtype)
+ CondFunc('torch.cat',
+ lambda orig_func, tensors, dim=0, out=None: orig_func([t.to(tensors[0].dtype) for t in tensors], dim=dim, out=out),
+ lambda orig_func, tensors, dim=0, out=None: not all(t.dtype == tensors[0].dtype for t in tensors))
+ CondFunc('torch.nn.functional.scaled_dot_product_attention',
+ lambda orig_func, query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False: orig_func(query, key.to(query.dtype), value.to(query.dtype), attn_mask, dropout_p, is_causal),
+ lambda orig_func, query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False: query.dtype != key.dtype or query.dtype != value.dtype)