Fix run time error in ROCm platform (#5147)
Co-authored-by: wunhuang <wunhuang@amd.com> Co-authored-by: root <root@dell300x-pla-t10-17.pla.dcgpu>
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@@ -4,6 +4,10 @@ import torch
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import triton
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import triton.language as tl
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from sglang.srt.utils import is_hip
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_is_hip = is_hip()
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fused_softcap_autotune = triton.autotune(
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configs=[
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triton.Config(kwargs={"BLOCK_SIZE": 128}, num_warps=4),
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@@ -185,6 +189,9 @@ def fused_dual_residual_rmsnorm(x, residual, weight1, weight2, eps, autotune=Fal
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assert x.shape == residual.shape and x.dtype == residual.dtype
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output, mid = torch.empty_like(x), torch.empty_like(x)
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bs, hidden_dim = x.shape
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min_num_warps = 16 if _is_hip else 32
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if autotune:
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fused_dual_residual_rmsnorm_kernel_autotune[(bs,)](
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output, mid, x, residual, weight1, weight2, eps=eps, hidden_dim=hidden_dim
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@@ -193,7 +200,10 @@ def fused_dual_residual_rmsnorm(x, residual, weight1, weight2, eps, autotune=Fal
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config = {
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"BLOCK_SIZE": triton.next_power_of_2(hidden_dim),
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"num_warps": max(
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min(triton.next_power_of_2(triton.cdiv(hidden_dim, 256)), 32), 4
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min(
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triton.next_power_of_2(triton.cdiv(hidden_dim, 256)), min_num_warps
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),
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4,
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),
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}
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@@ -250,10 +260,13 @@ def fused_rmsnorm(x, weight, eps, autotune=False, inplace=False):
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else:
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output = torch.empty_like(x)
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bs, hidden_dim = x.shape
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min_num_warps = 16 if _is_hip else 32
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config = {
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"BLOCK_SIZE": triton.next_power_of_2(hidden_dim),
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"num_warps": max(
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min(triton.next_power_of_2(triton.cdiv(hidden_dim, 256)), 32), 4
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min(triton.next_power_of_2(triton.cdiv(hidden_dim, 256)), min_num_warps), 4
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),
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}
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@@ -5,6 +5,9 @@ import triton
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import triton.language as tl
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from sglang.srt.layers.moe.topk import fused_topk
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from sglang.srt.utils import is_hip
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_is_hip = is_hip()
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@triton.jit
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@@ -116,10 +119,13 @@ def fused_moe_router_impl(
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topk_ids = torch.empty((bs, topk), dtype=torch.int32, device=x.device)
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grid = lambda meta: (bs,)
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min_num_warps = 16 if _is_hip else 32
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config = {
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"BLOCK_SIZE": triton.next_power_of_2(hidden_dim),
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"num_warps": max(
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min(triton.next_power_of_2(triton.cdiv(hidden_dim, 256)), 32), 4
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min(triton.next_power_of_2(triton.cdiv(hidden_dim, 256)), min_num_warps), 4
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),
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}
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@@ -171,6 +171,7 @@ def input_to_float8(
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amax = torch.maximum(min_val.abs(), max_val.abs()).clamp(min=1e-12)
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fp8_max = finfo.max
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if _is_hip:
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dtype = torch.float8_e4m3fnuz
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fp8_max = 224.0
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scale = fp8_max / amax
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x_scl_sat = (x * scale).clamp(min=-fp8_max, max=fp8_max)
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