Try to fix mac issue.
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@ -2,6 +2,7 @@ import torch
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from einops import rearrange
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from torch import Tensor
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from comfy.ldm.modules.attention import optimized_attention
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import comfy.model_management
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def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor) -> Tensor:
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q, k = apply_rope(q, k, pe)
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@ -13,12 +14,17 @@ def attention(q: Tensor, k: Tensor, v: Tensor, pe: Tensor) -> Tensor:
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def rope(pos: Tensor, dim: int, theta: int) -> Tensor:
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assert dim % 2 == 0
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scale = torch.linspace(0, (dim - 2) / dim, steps=dim//2, dtype=torch.float64, device=pos.device)
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if comfy.model_management.is_device_mps(pos.device):
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device = torch.device("cpu")
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else:
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device = pos.device
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scale = torch.linspace(0, (dim - 2) / dim, steps=dim//2, dtype=torch.float64, device=device)
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omega = 1.0 / (theta**scale)
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out = torch.einsum("...n,d->...nd", pos.float(), omega)
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out = torch.einsum("...n,d->...nd", pos.to(dtype=torch.float32, device=device), omega)
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out = torch.stack([torch.cos(out), -torch.sin(out), torch.sin(out), torch.cos(out)], dim=-1)
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out = rearrange(out, "b n d (i j) -> b n d i j", i=2, j=2)
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return out.float()
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return out.to(dtype=torch.float32, device=pos.device)
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def apply_rope(xq: Tensor, xk: Tensor, freqs_cis: Tensor):
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