Fix hackable case

[li-plus]

In this case, the output is always zeros regardless of the input. Because after the max op, dim 1 only has one element and x - x.mean is always 0.

KernelBench/KernelBench/level2/80_Gemm_Max_Subtract_GELU.py

Lines 13 to 25 in 768d52c

	def forward(self, x):
	"""
	Args:
	x: Input tensor of shape (batch_size, in_features)
	Returns:
	Output tensor of shape (batch_size, out_features)
	"""
	x = self.gemm(x)
	x = torch.max(x, dim=self.max_dim, keepdim=True).values
	x = x - x.mean(dim=1, keepdim=True)
	x = torch.nn.functional.gelu(x)
	return x