38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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"""Custom activation functions for diffusion models."""
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import torch
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import torch.nn.functional as F
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from vllm_omni.diffusion.layers.custom_op import CustomOp
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from vllm_omni.platforms import current_omni_platform
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class SiluAndMul(CustomOp):
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"""SwiGLU activation dispatched by the current vLLM-Omni platform."""
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def __init__(self) -> None:
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super().__init__()
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if current_omni_platform.is_cuda() or current_omni_platform.is_rocm() or current_omni_platform.is_musa():
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self.op = torch.ops._C.silu_and_mul
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@staticmethod
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def forward_native(x: torch.Tensor) -> torch.Tensor:
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d = x.shape[-1] // 2
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return F.silu(x[..., :d]) * x[..., d:]
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def forward_cuda(self, x: torch.Tensor) -> torch.Tensor:
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if x.device.type == "cpu":
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return self.forward_native(x)
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d = x.shape[-1] // 2
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output_shape = x.shape[:-1] + (d,)
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out = torch.empty(output_shape, dtype=x.dtype, device=x.device)
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self.op(out, x)
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return out
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def forward_npu(self, x: torch.Tensor) -> torch.Tensor:
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return self.forward_native(x)
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def forward_xpu(self, x: torch.Tensor) -> torch.Tensor:
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return self.forward_native(x)
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