Merge pull request #14229 from Nuullll/ipex-embedding
[IPEX] Fix embedding and ControlNet
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commit
f3cc5f8382
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@ -48,3 +48,12 @@ if has_xpu:
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CondFunc('torch.nn.modules.conv.Conv2d.forward',
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lambda orig_func, self, input: orig_func(self, input.to(self.weight.data.dtype)),
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lambda orig_func, self, input: input.dtype != self.weight.data.dtype)
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CondFunc('torch.bmm',
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lambda orig_func, input, mat2, out=None: orig_func(input.to(mat2.dtype), mat2, out=out),
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lambda orig_func, input, mat2, out=None: input.dtype != mat2.dtype)
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CondFunc('torch.cat',
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lambda orig_func, tensors, dim=0, out=None: orig_func([t.to(tensors[0].dtype) for t in tensors], dim=dim, out=out),
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lambda orig_func, tensors, dim=0, out=None: not all(t.dtype == tensors[0].dtype for t in tensors))
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CondFunc('torch.nn.functional.scaled_dot_product_attention',
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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),
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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)
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