correct
23_virtual_all_reduce_mean.py
started
2026-05-11T13:50:08Z
timingkernelbench.timing
kernel mean / median / std
0.01 / — / 1.47e-04 μs
ref mean / median / std
0.01 / — / 2.25e-04 μs
numerical precisioneval_kernel_against_ref
gpu memoryextended_metrics.measure_memory
kernel launches / fusiontorch.profiler
fusion ratio (ref / kernel)
2.00x
SOL (speed-of-light)nsight_hardware_counters
roofline / occupancynsight_hardware_counters
warp stalls (top 5)nsight
reference PyTorch source (the prompt the agent sees)
"""
Virtual ranks: input packs R per-rank tensors along dim 0. Output is the mean over ranks (B, D).
No distributed runtime required; the reference always reduces along dim 0.
"""
import torch
import torch.nn as nn
from kernelbench.distributed_collectives import default_device
R = 4
B = 16
D = 48
class Model(nn.Module):
"""x shape (R, B, D) -> mean over R -> (B, D)."""
def __init__(self):
super().__init__()
def forward(self, x: torch.Tensor) -> torch.Tensor:
return x.mean(dim=0)
def get_inputs():
dev = default_device()
p = popcorn_pri
return [torch.randn(p.jitter_int(R), p.jitter_int(B), p.jitter_int(D, align=8), device=dev)]
def get_init_inputs():
return []
turn 0301.2s turn · 10.0s LLM · 291.1s tools · tokens in=1,426 · out=331 · total=2,400
reasoning
The task is to replace the forward computation of a PyTorch model with a custom CUDA kernel. The model is simple: it takes a tensor x of shape (R, B, D) and returns the mean over dim=0, resulting in (...I need to replace the forward computation of a PyTorch model with a custom CUDA kernel.
call → compile_kernel
callcompile_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n'''\n\ncpp_source = '''\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← compile_kernel (fail)
failcompile_kernel
compile_kernel FAILED: RuntimeError.
RuntimeError: Error building extension 'mean_module': [1/3] /opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d019e1a13142/mean_module/main.cpp -o main.o
FAILED: [code=1] main.o
/opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d019e1a13142/mean_module/main.cpp -o main.o
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d019e1a13142/mean_module/main.cpp: In function 'at::Tensor mean_reduce(at::Tensor)':
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d019e1a13142/mean_module/main.cpp:11:5: error: 'mean_kernel' was not declared in this scope
11 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^~~~~~~~~~~
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d019e1a13142/mean_module/main.cpp:11:18: error: expected primary-expression before '<' token
11 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d019e1a13142/mean_module/main.cpp:11:36: error: expected primary-expression before '>' token
11 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
[2/3] /usr/local/cuda/bin/nvcc -MD -MF cuda.cuda.o.d -ccbin /opt/conda/bin/x86_64-conda-linux-gnu-cc -DTORCH_EXTENSION_NAME=mean_module -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_90,code=sm_90 --compiler-options '-fPIC' -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d019e1a13142/mean_module/cuda.cu -o cuda.cuda.o
nvcc warning : incompatible redefinition for option 'compiler-bindir', the last value of this option was used
ninja: build stopped: subcommand failed.
turn 1602.5s turn · 5.6s LLM · 596.9s tools · tokens in=3,422 · out=341 · total=3,888
reasoning
The error is that the CUDA kernel isn't declared in the cpp source. I need to include the kernel definition or use extern.
call → compile_kernel
callcompile_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n'''\n\ncpp_source = '''\ntorch::Tensor mean_reduce(torch::Tensor x);\n\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← compile_kernel (fail)
failcompile_kernel
compile_kernel FAILED: RuntimeError.
RuntimeError: Error building extension 'mean_module': [1/3] /opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_69f870d3d591/mean_module/main.cpp -o main.o
FAILED: [code=1] main.o
/opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_69f870d3d591/mean_module/main.cpp -o main.o
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_69f870d3d591/mean_module/main.cpp: In function 'at::Tensor mean_reduce(at::Tensor)':
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_69f870d3d591/mean_module/main.cpp:13:5: error: 'mean_kernel' was not declared in this scope
13 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^~~~~~~~~~~
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_69f870d3d591/mean_module/main.cpp:13:18: error: expected primary-expression before '<' token
13 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_69f870d3d591/mean_module/main.cpp:13:36: error: expected primary-expression before '>' token
13 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
[2/3] /usr/local/cuda/bin/nvcc -MD -MF cuda.cuda.o.d -ccbin /opt/conda/bin/x86_64-conda-linux-gnu-cc -DTORCH_EXTENSION_NAME=mean_module -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_90,code=sm_90 --compiler-options '-fPIC' -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_69f870d3d591/mean_module/cuda.cu -o cuda.cuda.o
nvcc warning : incompatible redefinition for option 'compiler-bindir', the last value of this option was used
ninja: build stopped: subcommand failed.
turn 2392.8s turn · 6.1s LLM · 386.7s tools · tokens in=4,917 · out=358 · total=5,319
reasoning
Still failing. I need to declare the kernel in the cpp_source as extern "C" or something.
call → compile_kernel
callcompile_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n'''\n\ncpp_source = '''\nextern \"C\" {\nvoid mean_kernel(const float* input, float* output, int R, int B, int D);\n}\n\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← compile_kernel (fail)
failcompile_kernel
compile_kernel FAILED: RuntimeError.
RuntimeError: Error building extension 'mean_module_v1': [1/3] /opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v1 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_6f4f0c0e39d8/mean_module/main.cpp -o main.o
FAILED: [code=1] main.o
/opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v1 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_6f4f0c0e39d8/mean_module/main.cpp -o main.o
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_6f4f0c0e39d8/mean_module/main.cpp: In function 'at::Tensor mean_reduce(at::Tensor)':
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_6f4f0c0e39d8/mean_module/main.cpp:15:18: error: expected primary-expression before '<' token
15 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_6f4f0c0e39d8/mean_module/main.cpp:15:36: error: expected primary-expression before '>' token
15 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
[2/3] /usr/local/cuda/bin/nvcc -MD -MF cuda.cuda.o.d -ccbin /opt/conda/bin/x86_64-conda-linux-gnu-cc -DTORCH_EXTENSION_NAME=mean_module_v1 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_90,code=sm_90 --compiler-options '-fPIC' -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_6f4f0c0e39d8/mean_module/cuda.cu -o cuda.cuda.o
nvcc warning : incompatible redefinition for option 'compiler-bindir', the last value of this option was used
ninja: build stopped: subcommand failed.
turn 31003.9s turn · 4.1s LLM · 999.8s tools · tokens in=6,281 · out=317 · total=6,751
reasoning
The declaration is wrong; extern "C" for __global__ needs proper prototype.
call → compile_kernel
callcompile_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\nsource = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← compile_kernel (fail)
failcompile_kernel
compile_kernel FAILED: RuntimeError.
RuntimeError: Error building extension 'mean_module_v2': [1/2] /opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v2 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_35f0b69e40d3/mean_module/main.cpp -o main.o
FAILED: [code=1] main.o
/opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v2 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_35f0b69e40d3/mean_module/main.cpp -o main.o
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_35f0b69e40d3/mean_module/main.cpp:3:1: error: '__global__' does not name a type
3 | __global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {
| ^~~~~~~~~~
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_35f0b69e40d3/mean_module/main.cpp: In function 'at::Tensor mean_reduce(at::Tensor)':
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_35f0b69e40d3/mean_module/main.cpp:23:5: error: 'mean_kernel' was not declared in this scope
23 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^~~~~~~~~~~
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_35f0b69e40d3/mean_module/main.cpp:23:18: error: expected primary-expression before '<' token
23 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_35f0b69e40d3/mean_module/main.cpp:23:36: error: expected primary-expression before '>' token
23 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
ninja: build stopped: subcommand failed.
turn 4 · 1 tool call(s) · 717.9s turn · 4.5s LLM · tokens in=7,587 · out=363 · total=8,016 · 8,064 chars (click to expand)
turn 4717.9s turn · 4.5s LLM · 713.4s tools · tokens in=7,587 · out=363 · total=8,016
reasoning
Now cpp is compiled as C++ not CUDA. So need to use cuda_sources for the kernel.
call → compile_kernel
callcompile_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = r'''\n__global__ void mean_kernel(const float* __restrict__ input, float* __restrict__ output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r = 0; r < R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / (float)R;\n }\n}\n'''\n\ncpp_source = r'''\ntorch::Tensor mean_reduce(torch::Tensor x);\n\nextern void launch_mean_kernel(const float* input, float* output, int R, int B, int D, cudaStream_t stream);\n\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n cudaStream_t stream = at::cuda::getCurrentCUDAStream();\n launch_mean_kernel(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D, stream);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← compile_kernel (fail)
failcompile_kernel
compile_kernel FAILED: RuntimeError.
RuntimeError: Error building extension 'mean_module_v3': [1/3] /opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v3 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_2924c9634060/mean_module/main.cpp -o main.o
FAILED: [code=1] main.o
/opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v3 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_2924c9634060/mean_module/main.cpp -o main.o
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_2924c9634060/mean_module/main.cpp:5:88: error: 'cudaStream_t' has not been declared
5 | extern void launch_mean_kernel(const float* input, float* output, int R, int B, int D, cudaStream_t stream);
| ^~~~~~~~~~~~
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_2924c9634060/mean_module/main.cpp: In function 'at::Tensor mean_reduce(at::Tensor)':
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_2924c9634060/mean_module/main.cpp:12:5: error: 'cudaStream_t' was not declared in this scope
12 | cudaStream_t stream = at::cuda::getCurrentCUDAStream();
| ^~~~~~~~~~~~
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_2924c9634060/mean_module/main.cpp:13:80: error: 'stream' was not declared in this scope; did you mean 'std::io_errc::stream'?
13 | launch_mean_kernel(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D, stream);
| ^~~~~~
| std::io_errc::stream
In file included from /opt/conda/lib/gcc/x86_64-conda-linux-gnu/14.2.0/include/c++/ios:44,
from /opt/conda/lib/gcc/x86_64-conda-linux-gnu/14.2.0/include/c++/ostream:40,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/c10/core/DeviceType.h:10,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/c10/core/Device.h:4,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/ATen/core/TensorBody.h:12,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/ATen/core/Tensor.h:4,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/ATen/Tensor.h:4,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/autograd/function_hook.h:4,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:3,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/autograd/variable.h:7,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/autograd/autograd.h:4,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:4,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include/torch/all.h:8,
from /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/extension.h:6,
from /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_2924c9634060/mean_module/main.cpp:1:
/opt/conda/lib/gcc/x86_64-conda-linux-gnu/14.2.0/include/c++/bits/ios_base.h:225:24: note: 'std::io_errc::stream' declared here
225 | enum class io_errc { stream = 1 };
| ^~~~~~
[2/3] /usr/local/cuda/bin/nvcc -MD -MF cuda.cuda.o.d -ccbin /opt/conda/bin/x86_64-conda-linux-gnu-cc -DTORCH_EXTENSION_NAME=mean_module_v3 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_90,code=sm_90 --compiler-options '-fPIC' -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_2924c9634060/mean_module/cuda.cu -o cuda.cuda.o
nvcc warning : incompatible redefinition for option 'compiler-bindir', the last value of this option was used
ninja: build stopped: subcommand failed.
turn 5608.1s turn · 5.8s LLM · 602.3s tools · tokens in=9,639 · out=347 · total=10,087
reasoning
Too complicated. Simplify by not using stream.
call → compile_kernel
callcompile_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n'''\n\ncpp_source = '''\n#include <torch/extension.h>\n\ntorch::Tensor mean_reduce(torch::Tensor x);\n\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← compile_kernel (fail)
failcompile_kernel
compile_kernel FAILED: RuntimeError.
RuntimeError: Error building extension 'mean_module_v4': [1/3] /opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v4 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d70a2f7387f6/mean_module/main.cpp -o main.o
FAILED: [code=1] main.o
/opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v4 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d70a2f7387f6/mean_module/main.cpp -o main.o
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d70a2f7387f6/mean_module/main.cpp: In function 'at::Tensor mean_reduce(at::Tensor)':
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d70a2f7387f6/mean_module/main.cpp:15:5: error: 'mean_kernel' was not declared in this scope
15 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^~~~~~~~~~~
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d70a2f7387f6/mean_module/main.cpp:15:18: error: expected primary-expression before '<' token
15 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d70a2f7387f6/mean_module/main.cpp:15:36: error: expected primary-expression before '>' token
15 | mean_kernel<<<blocks, threads>>>(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^
[2/3] /usr/local/cuda/bin/nvcc -MD -MF cuda.cuda.o.d -ccbin /opt/conda/bin/x86_64-conda-linux-gnu-cc -DTORCH_EXTENSION_NAME=mean_module_v4 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_90,code=sm_90 --compiler-options '-fPIC' -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d70a2f7387f6/mean_module/cuda.cu -o cuda.cuda.o
nvcc warning : incompatible redefinition for option 'compiler-bindir', the last value of this option was used
ninja: build stopped: subcommand failed.
turn 6836.3s turn · 5.5s LLM · 830.8s tools · tokens in=11,131 · out=367 · total=11,628
reasoning
The issue is the kernel symbol is not visible to the C++ compiler because the cuda is separate translation unit.
call → compile_kernel
callcompile_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n\nvoid launch_mean(const float* input, float* output, int R, int B, int D) {\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(input, output, R, B, D);\n}\n'''\n\ncpp_source = '''\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n launch_mean(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← compile_kernel (fail)
failcompile_kernel
compile_kernel FAILED: RuntimeError.
RuntimeError: Error building extension 'mean_module_v5': [1/3] /opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v5 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d8099f00d6b4/mean_module/main.cpp -o main.o
FAILED: [code=1] main.o
/opt/conda/bin/x86_64-conda-linux-gnu-c++ -MMD -MF main.o.d -DTORCH_EXTENSION_NAME=mean_module_v5 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -fPIC -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d8099f00d6b4/mean_module/main.cpp -o main.o
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d8099f00d6b4/mean_module/main.cpp: In function 'at::Tensor mean_reduce(at::Tensor)':
/scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d8099f00d6b4/mean_module/main.cpp:8:5: error: 'launch_mean' was not declared in this scope
8 | launch_mean(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
| ^~~~~~~~~~~
[2/3] /usr/local/cuda/bin/nvcc -MD -MF cuda.cuda.o.d -ccbin /opt/conda/bin/x86_64-conda-linux-gnu-cc -DTORCH_EXTENSION_NAME=mean_module_v5 -DTORCH_API_INCLUDE_EXTENSION_H -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include -isystem /scratch/abaner/KernelBench/.venv/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /usr/local/cuda/include -isystem /opt/conda/include/python3.10 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_90,code=sm_90 --compiler-options '-fPIC' -std=c++17 -c /scratch/abaner/KernelBench/runs/pop_l123_default_gpt/popcorn/grok-4.3/level_1_problem_23_cache/k_d8099f00d6b4/mean_module/cuda.cu -o cuda.cuda.o
nvcc warning : incompatible redefinition for option 'compiler-bindir', the last value of this option was used
ninja: build stopped: subcommand failed.
turn 7526.0s turn · 6.1s LLM · 519.9s tools · tokens in=12,478 · out=388 · total=12,875
reasoning
Still missing declaration. Add declaration in cpp.
call → compile_kernel
callcompile_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n\nvoid launch_mean(const float* input, float* output, int R, int B, int D) {\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(input, output, R, B, D);\n}\n'''\n\ncpp_source = '''\nvoid launch_mean(const float* input, float* output, int R, int B, int D);\n\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n launch_mean(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← compile_kernel (ok)
okcompile_kernel
compile_kernel PASSED: kernel compiled without errors.
turn 81049.6s turn · 2.3s LLM · 1047.3s tools · tokens in=12,892 · out=389 · total=13,290
reasoning
Great, it compiled. Now check correctness.
call → run_correctness
callrun_correctness
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n\nvoid launch_mean(const float* input, float* output, int R, int B, int D) {\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(input, output, R, B, D);\n}\n'''\n\ncpp_source = '''\nvoid launch_mean(const float* input, float* output, int R, int B, int D);\n\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n launch_mean(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← run_correctness (ok)
okrun_correctness
run_correctness PASSED: (5 / 5) trials all matched the reference.
Numerical precision: max_abs_err=0.00e+00 mean_abs_err=0.00e+00 max_rel_err=0.00e+00
turn 9164.1s turn · 5.2s LLM · 158.9s tools · tokens in=13,384 · out=388 · total=13,796 · FINAL
reasoning
It's correct, and for such tiny problem, this kernel should be faster or at least acceptable. I think submit it.
call → submit_kernel
callsubmit_kernel
{
"kernel_code": "import torch\nimport torch.nn as nn\nfrom torch.utils.cpp_extension import load_inline\n\ncuda_source = '''\n__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {\n int idx = blockIdx.x * blockDim.x + threadIdx.x;\n int total = B * D;\n if (idx < total) {\n float sum = 0.0f;\n for(int r=0; r<R; r++) {\n sum += input[r * total + idx];\n }\n output[idx] = sum / R;\n }\n}\n\nvoid launch_mean(const float* input, float* output, int R, int B, int D) {\n int total = B * D;\n int threads = 256;\n int blocks = (total + threads - 1) / threads;\n mean_kernel<<<blocks, threads>>>(input, output, R, B, D);\n}\n'''\n\ncpp_source = '''\nvoid launch_mean(const float* input, float* output, int R, int B, int D);\n\ntorch::Tensor mean_reduce(torch::Tensor x) {\n int R = x.size(0);\n int B = x.size(1);\n int D = x.size(2);\n auto output = torch::empty({B, D}, x.options());\n launch_mean(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);\n return output;\n}\n'''\n\nmodule = load_inline(\n name='mean_module',\n cpp_sources=[cpp_source],\n cuda_sources=[cuda_source],\n functions=['mean_reduce'],\n verbose=False\n)\n\nclass ModelNew(nn.Module):\n def __init__(self):\n super().__init__()\n def forward(self, x: torch.Tensor) -> torch.Tensor:\n return module.mean_reduce(x)\n"
}
result ← submit_kernel (ok)
oksubmit_kernel
submit_kernel PASSED: (5 / 5) correctness trials all passed.
Kernel runtime: 0.01 μs
Runtime stats: mean=0.01μs median=?μs std=0.00μs
Numerical precision: max_abs_err=0.00e+00 mean_abs_err=0.00e+00 max_rel_err=0.00e+00
Memory: 33.01 MB peak (ref: 33.01 MB, ratio: 1.0x)
Kernel launches: 1 (ref: 2, fusion ratio: 2.0)
SOL score: 0.0022
final submitted kernel (52 lines, 1,370 chars) — full source, untruncated
import torch
import torch.nn as nn
from torch.utils.cpp_extension import load_inline
cuda_source = '''
__global__ void mean_kernel(const float* input, float* output, int R, int B, int D) {
int idx = blockIdx.x * blockDim.x + threadIdx.x;
int total = B * D;
if (idx < total) {
float sum = 0.0f;
for(int r=0; r<R; r++) {
sum += input[r * total + idx];
}
output[idx] = sum / R;
}
}
void launch_mean(const float* input, float* output, int R, int B, int D) {
int total = B * D;
int threads = 256;
int blocks = (total + threads - 1) / threads;
mean_kernel<<<blocks, threads>>>(input, output, R, B, D);
}
'''
cpp_source = '''
void launch_mean(const float* input, float* output, int R, int B, int D);
torch::Tensor mean_reduce(torch::Tensor x) {
int R = x.size(0);
int B = x.size(1);
int D = x.size(2);
auto output = torch::empty({B, D}, x.options());
launch_mean(x.data_ptr<float>(), output.data_ptr<float>(), R, B, D);
return output;
}
'''
module = load_inline(
name='mean_module',
cpp_sources=[cpp_source],
cuda_sources=[cuda_source],
functions=['mean_reduce'],
verbose=False
)
class ModelNew(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x: torch.Tensor) -> torch.Tensor:
return module.mean_reduce(x)