Revert "[1/2] Optimizations and refactors about quant kernel (#9534)" (#10292)

python/sglang/srt/bench_utils.py

@@ -1,5 +1,4 @@
 import os
-import re
 import sys
 from contextlib import nullcontext
 
@@ -109,8 +108,7 @@ def bench_kineto(
     if not with_multiple_kernels:
         for name in kernel_names:
             assert (
-                sum([int(re.search(name, line) is not None) for line in prof_lines])
-                == 1
+                sum([name in line for line in prof_lines]) == 1
             ), f"Errors of the kernel {name} in the profiling table (table: {prof_lines})"
 
     # Save chrome traces
@@ -124,7 +122,7 @@ def bench_kineto(
         total_time = 0
         total_num = 0
         for line in prof_lines:
-            if re.search(name, line) is not None:
+            if name in line:
                 time_str = line.split()[-2]
                 num_str = line.split()[-1]
                 for unit, scale in units.items():

python/sglang/srt/layers/quantization/fp8_kernel.py

@@ -43,17 +43,11 @@ _is_cpu = is_cpu()
 _use_aiter = get_bool_env_var("SGLANG_USE_AITER") and _is_hip
 
 if _is_cuda:
-    from sgl_kernel import sgl_per_tensor_quant_fp8, sgl_per_token_quant_fp8
-
-    # Temporary
-    try:
-        from sgl_kernel import sgl_per_token_group_quant_8bit
-
-        enable_sgl_per_token_group_quant_8bit = True
-    except ImportError:
-        from sgl_kernel import sgl_per_token_group_quant_fp8
-
-        enable_sgl_per_token_group_quant_8bit = False
+    from sgl_kernel import (
+        sgl_per_tensor_quant_fp8,
+        sgl_per_token_group_quant_fp8,
+        sgl_per_token_quant_fp8,
+    )
 
 if _is_hip:
     if _use_aiter:
@@ -502,24 +496,9 @@ def sglang_per_token_group_quant_fp8(
     )
 
     if x.shape[0] > 0:
-        # Temporary
-        if enable_sgl_per_token_group_quant_8bit:
-            sgl_per_token_group_quant_8bit(
-                x,
-                x_q,
-                x_s,
-                group_size,
-                eps,
-                fp8_min,
-                fp8_max,
-                scale_ue8m0,
-                fuse_silu_and_mul,
-                masked_m,
-            )
-        else:
-            sgl_per_token_group_quant_fp8(
-                x, x_q, x_s, group_size, eps, fp8_min, fp8_max, scale_ue8m0
-            )
+        sgl_per_token_group_quant_fp8(
+            x, x_q, x_s, group_size, eps, fp8_min, fp8_max, scale_ue8m0
+        )
 
     return x_q, x_s
 

python/sglang/srt/layers/quantization/int8_kernel.py

@@ -12,13 +12,7 @@ from sglang.srt.utils import get_device_name, is_cuda
 
 _is_cuda = is_cuda()
 if _is_cuda:
-    # Temporary
-    try:
-        from sgl_kernel import sgl_per_token_group_quant_8bit
-    except ImportError:
-        from sgl_kernel import (
-            sgl_per_token_group_quant_int8 as sgl_per_token_group_quant_8bit,
-        )
+    from sgl_kernel import sgl_per_token_group_quant_int8
 
 logger = logging.getLogger(__name__)
 
@@ -210,7 +204,7 @@ def sglang_per_token_group_quant_int8(
         dtype=torch.float32,
     )
 
-    sgl_per_token_group_quant_8bit(x, x_q, x_s, group_size, eps, int8_min, int8_max)
+    sgl_per_token_group_quant_int8(x, x_q, x_s, group_size, eps, int8_min, int8_max)
 
     return x_q, x_s