fix: update bmm fp8 test (#487)

fp8 scale per tensor

ref sgl-project/sglang#1285

python/flashinfer/gemm.py

@@ -241,8 +241,9 @@ def bmm_fp8(
     >>> import flashinfer
     >>> def to_float8(x, dtype=torch.float8_e4m3fn):
     ...     finfo = torch.finfo(dtype)
-    ...     abs_max = x.abs().amax(dim=(1, 2), keepdim=True).clamp(min=1e-12)
-    ...     scale = finfo.max / abs_max
+    ...     min_val, max_val = x.aminmax()
+    ...     amax = torch.maximum(min_val.abs(), max_val.abs()).clamp(min=1e-12)
+    ...     scale = finfo.max / amax
     ...     x_scl_sat = (x * scale).clamp(min=finfo.min, max=finfo.max)
     ...     return x_scl_sat.to(dtype), scale.float().reciprocal()
     >>>

python/tests/test_bmm_fp8.py

@@ -1,13 +1,15 @@
 import pytest
 import torch
 import torch.nn.functional as F
+
 from flashinfer import bmm_fp8
 
 
 def to_float8(x, dtype=torch.float8_e4m3fn):
     finfo = torch.finfo(dtype)
-    abs_max = x.abs().amax(dim=(1, 2), keepdim=True).clamp(min=1e-12)
-    scale = finfo.max / abs_max
+    min_val, max_val = x.aminmax()
+    amax = torch.maximum(min_val.abs(), max_val.abs()).clamp(min=1e-12)
+    scale = finfo.max / amax
     x_scl_sat = (x * scale).clamp(min=finfo.min, max=finfo.max)
     return x_scl_sat.to(dtype), scale.float().reciprocal()
 
@@ -32,9 +34,8 @@ def test_bmm_fp8(input_dtype, mat2_dtype, res_dtype):
     bmm_fp8(input_fp8, mat2_fp8, input_inv_s, mat2_inv_s, res_dtype, res)
 
     reference = torch.bmm(input, mat2)
-
     cos_sim = F.cosine_similarity(reference.reshape(-1), res.reshape(-1), dim=0)
-    assert cos_sim > 0.98
+    assert cos_sim > 0.99
 
 
 if __name__ == "__main__":