[ROCm] Add AMD GPU support on Deepseek v3.2 and SparseMLA (#26670)

Signed-off-by: ganyi <ygan@amd.com>

vllm/utils/deep_gemm.py

@@ -325,6 +325,7 @@ DEFAULT_BLOCK_SIZE = [128, 128]
 def per_block_cast_to_fp8(
     x: torch.Tensor, block_size: list[int] = DEFAULT_BLOCK_SIZE, use_ue8m0: bool = False
 ) -> tuple[torch.Tensor, torch.Tensor]:
+    fp8_dtype = current_platform.fp8_dtype()
     assert x.dim() == 2
     m, n = x.shape
     block_m, block_n = block_size
@@ -334,9 +335,9 @@ def per_block_cast_to_fp8(
     x_padded[:m, :n] = x
     x_view = x_padded.view(-1, block_m, x_padded.size(1) // block_n, block_n)
     x_amax = x_view.abs().float().amax(dim=(1, 3), keepdim=True).clamp(1e-4)
-    sf = x_amax / 448.0
+    sf = x_amax / 224.0 if current_platform.is_fp8_fnuz() else x_amax / 448.0
     sf = _ceil_to_ue8m0(sf) if use_ue8m0 else sf
-    x_scaled = (x_view * (1.0 / sf)).to(torch.float8_e4m3fn)
+    x_scaled = (x_view * (1.0 / sf)).to(fp8_dtype)
     return x_scaled.view_as(x_padded)[:m, :n].contiguous(), sf.view(
         x_view.size(0), x_view.size(2)
     )