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[ROCm] Fallback pytorch GELU with tanh approximation to GELU() (#29244)

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Signed-off-by: Divakar Verma <divakar.verma@amd.com>
Signed-off-by: Divakar Verma <137818590+divakar-amd@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
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Divakar Verma 2025-12-01 20:02:22 -06:00 committed by GitHub
parent c0dfc89485
commit 4b40924998
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1 changed files with 28 additions and 2 deletions
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30
vllm/model_executor/layers/activation.py
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@ -159,6 +159,13 @@ class GeluAndMulSparse(CustomOp):
self.approximate = approximate
if approximate not in ("none", "tanh"):
raise ValueError(f"Unknown approximate mode: {approximate}")
if current_platform.is_rocm() and approximate == "tanh":
# TODO:[ROCm] PyTorch native GELU with tanh is unstable with torch.compile
logger.warning_once(
"[ROCm] Pytorch's native GELU with tanh approximation is currently "
"unstable and produces garbage. Fallback to 'none' approximation."
)
self.approximate = "none"
# Sparsity.
if activation_sparsity == 0.0:
@ -209,6 +216,12 @@ class GeluAndMul(CustomOp):
self.op = torch.ops._C.gelu_and_mul
elif approximate == "tanh":
self.op = torch.ops._C.gelu_tanh_and_mul
if current_platform.is_rocm() and approximate == "tanh":
logger.warning_once(
"[ROCm] PyTorch's native GELU with tanh approximation is unstable "
"with torch.compile. For native implementation, fallback to 'none' "
"approximation. The custom kernel implementation is unaffected."
)
elif current_platform.is_xpu():
from vllm._ipex_ops import ipex_ops
@ -219,8 +232,12 @@ class GeluAndMul(CustomOp):
def forward_native(self, x: torch.Tensor) -> torch.Tensor:
"""PyTorch-native implementation equivalent to forward()."""
# TODO: [ROCm] PyTorch's native GELU with tanh is unstable with torch.compile
approximate = self.approximate
if current_platform.is_rocm() and approximate == "tanh":
approximate = "none"
d = x.shape[-1] // 2
return F.gelu(x[..., :d], approximate=self.approximate) * x[..., d:]
return F.gelu(x[..., :d], approximate=approximate) * x[..., d:]
def forward_cuda(self, x: torch.Tensor) -> torch.Tensor:
d = x.shape[-1] // 2
@ -522,7 +539,16 @@ _ACTIVATION_REGISTRY = LazyDict(
"gelu": lambda: nn.GELU(),
"gelu_fast": lambda: FastGELU(),
"gelu_new": lambda: NewGELU(),
"gelu_pytorch_tanh": lambda: nn.GELU(approximate="tanh"),
"gelu_pytorch_tanh": lambda: (
# TODO:[ROCm] PyTorch native GELU with tanh is unstable with torch.compile
logger.warning_once(
"[ROCm] PyTorch's native GELU with tanh approximation is unstable. "
"Falling back to GELU(approximate='none')."
),
nn.GELU(approximate="none"),
)[1]
if current_platform.is_rocm()
else nn.GELU(approximate="tanh"),
"relu": lambda: nn.ReLU(),
"relu2": lambda: ReLUSquaredActivation(),
"silu": lambda: nn.SiLU(),