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https://github.com/huggingface/text-generation-inference.git
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could use PositionRotaryEmbedding impl so rocm and ipex could all work
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
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@ -570,28 +570,6 @@ class RotaryPositionEmbeddingMultimodalSections(PositionRotaryEmbedding):
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.to(inv_freq.device)
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)
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def forward(
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self,
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query: torch.Tensor,
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key: torch.Tensor,
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cos: torch.Tensor,
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sin: torch.Tensor,
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):
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if SYSTEM == "ipex":
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ipex.llm.functional.rotary_embedding(
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query, key, sin, cos, query.size(-1), True
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)
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else:
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# rotate half the sequence length
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rot = cos.shape[-1] // 2
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q2 = torch.cat([-query[..., rot:], query[..., :rot]], dim=-1)
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k2 = torch.cat([-key[..., rot:], key[..., :rot]], dim=-1)
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# apply the rotation
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rotary_emb.apply_rotary(query, q2, cos, sin, query, q2, True)
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rotary_emb.apply_rotary(key, k2, cos, sin, key, k2, True)
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def _update_cos_sin_cache(
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self, dtype: torch.dtype, device: torch.device, seqlen: int
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):
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@ -620,7 +598,4 @@ class RotaryPositionEmbeddingMultimodalSections(PositionRotaryEmbedding):
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cos = self._cos_cached[position_ids].gather(1, self._sections[:slen])
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sin = self._sin_cached[position_ids].gather(1, self._sections[:slen])
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cos = torch.cat([cos, cos], dim=-1)
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sin = torch.cat([sin, sin], dim=-1)
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return cos, sin
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