[Refactor] Use is_in_ci() utility in JIT kernel benchmarks (#17118)
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@@ -1,10 +1,10 @@
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import os
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from typing import Optional, Tuple
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import torch
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import triton
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import triton.testing
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from sglang.jit_kernel.benchmark.utils import is_in_ci
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from sglang.jit_kernel.per_tensor_quant_fp8 import per_tensor_quant_fp8
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try:
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@@ -22,10 +22,7 @@ try:
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except ImportError:
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_is_hip = False
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IS_CI = (
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os.getenv("CI", "false").lower() == "true"
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or os.getenv("GITHUB_ACTIONS", "false").lower() == "true"
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)
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IS_CI = is_in_ci()
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fp8_type_ = torch.float8_e4m3fnuz if _is_hip else torch.float8_e4m3fn
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@@ -1,5 +1,4 @@
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import itertools
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import os
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from typing import Tuple
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import torch
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@@ -7,13 +6,11 @@ import triton
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import triton.testing
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from sgl_kernel import rmsnorm
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from sglang.jit_kernel.benchmark.utils import is_in_ci
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from sglang.jit_kernel.norm import fused_inplace_qknorm
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from sglang.srt.utils import get_current_device_stream_fast
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IS_CI = (
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os.getenv("CI", "false").lower() == "true"
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or os.getenv("GITHUB_ACTIONS", "false").lower() == "true"
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)
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IS_CI = is_in_ci()
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alt_stream = torch.cuda.Stream()
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@@ -1,5 +1,4 @@
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import itertools
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import os
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import torch
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import triton
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@@ -7,12 +6,10 @@ import triton.testing
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from flashinfer import rmsnorm as fi_rmsnorm
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from sgl_kernel import rmsnorm
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from sglang.jit_kernel.benchmark.utils import is_in_ci
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from sglang.jit_kernel.norm import rmsnorm as jit_rmsnorm
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IS_CI = (
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os.getenv("CI", "false").lower() == "true"
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or os.getenv("GITHUB_ACTIONS", "false").lower() == "true"
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)
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IS_CI = is_in_ci()
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def sglang_aot_rmsnorm(
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