Remove obsolete sgl-kernel legacy paths (#21528)

sgl-kernel/tests/test_merge_state_v2.py

@@ -5,7 +5,7 @@ import pytest
 import torch
 import triton
 import triton.language as tl
-from sgl_kernel import merge_state, merge_state_v2
+from sgl_kernel import merge_state_v2
 
 
 @triton.jit
@@ -146,11 +146,9 @@ def generate_markdown_table():
     global all_case_info
     table_header = (
         "| tokens | heads | headsize | dtype "
-        "| device | torch | triton | v1 | v2 | speedup(vs triton) | speedup(vs v1)|"
-    )
-    table_separator = (
-        "| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |"
+        "| device | torch | triton | v2 | speedup(vs triton) |"
     )
+    table_separator = "| --- | --- | --- | --- | --- | --- | --- | --- | --- |"
 
     def shortly_dtype(dtype: torch.dtype) -> str:
         return str(dtype).removeprefix("torch.")
@@ -169,21 +167,17 @@ def generate_markdown_table():
             device,
             time_torch,
             time_triton,
-            time_v1,
             time_v2,
         ) = info
         dtype = shortly_dtype(dtype)
         device = shortly_device(device)
         improved_triton = time_triton / time_v2
-        improved_v1 = time_v1 / time_v2
         print(
             f"| {num_tokens} | {num_heads} | {head_size} "
             f"| {dtype} | {device} | {time_torch:.4f}ms "
             f"| {time_triton:.4f}ms "
-            f"| {time_v1:.4f}ms "
             f"| {time_v2:.4f}ms "
-            f"| {improved_triton:.4f}x "
-            f"| {improved_v1:.4f}x |"
+            f"| {improved_triton:.4f}x |"
         )
 
 
@@ -259,11 +253,6 @@ def test_merge_attn_states(
             prefix_lse_ = prefix_lse
             suffix_lse_ = suffix_lse
 
-        if fn_type == "cuda_v1":
-            # merge_state v1 kernel not support float32
-            if output_dtype not in (torch.half, torch.bfloat16):
-                return 0, output_fn, output_lse_fn
-
         total_time = 0
         start = torch.cuda.Event(enable_timing=True)
         end = torch.cuda.Event(enable_timing=True)
@@ -316,29 +305,21 @@ def test_merge_attn_states(
         fn_type="triton",
     )
 
-    # 2. Run the merge_state V1 kernel
-    output_v1 = output.clone()
-    output_lse_v1 = output_lse.clone()
-    time_v1, output_v1, output_lse_v1 = perf_kernel_fn(
-        output_v1, output_lse_v1, merge_state, fn_type="cuda_v1"
-    )
-
-    # 3. Run the merge_state V2 kernel
+    # 2. Run the merge_state V2 kernel
     output_v2 = output.clone()
     output_lse_v2 = output_lse.clone()
     time_v2, output_v2, output_lse_v2 = perf_kernel_fn(
         output_v2, output_lse_v2, merge_state_v2, fn_type="cuda_v2"
     )
 
-    # 4. Performance compare
+    # 3. Performance compare
     improved = time_triton / time_v2
     print(f"  Torch time: {time_torch:.6f}ms")
     print(f" Triton time: {time_triton:.6f}ms")
-    print(f"CUDA v1 time: {time_v1:.6f}ms")
     print(f"CUDA v2 time: {time_v2:.6f}ms, Performance: {improved:.5f}x")
     print("-" * 100)
 
-    # 5. Correctness compare
+    # 4. Correctness compare
     # Liger Kernel: Efficient Triton Kernels for LLM Training
     # https://arxiv.org/pdf/2410.10989, 3.3 Correctness
     # use rtol = 1e-2 for bfloat16.
@@ -387,7 +368,6 @@ def test_merge_attn_states(
             device,
             time_torch,
             time_triton,
-            time_v1,
             time_v2,
         )
     )