L2 P64 · original

error 64_Gemm_LogSumExp_LeakyReLU_LeakyReLU_GELU_GELU.py

model

gpt-5.5-priority

turns / max

2 / 10

tool calls

tokens (total)

wall clock

—

truncated

backend

cuda fp32

variant

original

runtime

—

ref runtime

0.00 μs

speedup

—

started

2026-05-02T19:56:10Z

reference PyTorch source (the prompt the agent sees)

import torch
import torch.nn as nn

class Model(nn.Module):
    """
    Model that performs a matrix multiplication (Gemm), followed by LogSumExp, LeakyReLU, 
    LeakyReLU, GELU, and GELU activations.
    """
    def __init__(self, in_features, out_features, bias=True):
        super(Model, self).__init__()
        self.linear = nn.Linear(in_features, out_features, bias=bias)

    def forward(self, x):
        # Gemm
        x = self.linear(x)
        # LogSumExp
        x = torch.logsumexp(x, dim=1, keepdim=True)
        # LeakyReLU
        x = torch.nn.functional.leaky_relu(x, negative_slope=0.01)
        # LeakyReLU
        x = torch.nn.functional.leaky_relu(x, negative_slope=0.01)
        # GELU
        x = torch.nn.functional.gelu(x)
        # GELU
        x = torch.nn.functional.gelu(x)
        return x

batch_size = 1024
in_features = 8192
out_features = 8192

def get_inputs():
    return [torch.rand(batch_size, in_features)]

def get_init_inputs():
    return [in_features, out_features]

turn 010.4s turn · 10.4s LLM · 0.0s tools

call → get_gpu_specs

callget_gpu_specs {}

result ← get_gpu_specs (fail)

failget_gpu_specs get_gpu_specs FAILED: unexpected error during tool execution. _WorkItemTimeout: work item exceeded soft timeout budget Traceback (most recent call last): File "/scratch/tejas/PopcornBench/src/kernelbench/agent/agent.py", line 627, in _execute_tool return tool.execute(self.ctx, **args) File "/scratch/tejas/PopcornBench/src/kernelbench/agent/tools.py", line 656, in execute return ctx.eval_client.get_gpu_specs(ctx) File "/scratch/tejas/PopcornBench/src/kernelbench/agent/eval_client.py", line 62, in get_gpu_specs return self._call("specs", args) File "/scratch/tejas/PopcornBench/src/kernelbench/agent/eval_client.py", line 117, in _call payload = self._response_q.get(timeout=remaining) File "<string>", line 2, in get File "/home/prabhune/.local/share/uv/python/cpython-3.10-linux-x86_64-gnu/lib/python3.10/multiprocessing/managers.py", line 818, in _callmethod kind, result = conn.recv() File "/home/prabhune/.local/share/uv/python/cpython-3.10-linux-x86_64-gnu/lib/python3.10/multiprocessing/connection.py", line 250, in recv buf = self._recv_bytes() File "/home/prabhune/.local/share/uv/python/cpython-3.10-linux-x86_64-gnu/lib/python3.10/multiprocessing/connection.py", line 414, in _recv_bytes buf = self._recv(4) File "/home/prabhune/.local/share/uv/python/cpython-3.10-linux-x86_64-gnu/lib/python3.10/multiprocessing/connection.py", line 379, in _recv chunk = read(handle, remaining) File "/scratch/tejas/PopcornBench/scripts/run_sweep.py", line 161, in _alarm_handler raise _WorkItemTimeout("work item exceeded soft timeout budget") __mp_main__._WorkItemTimeout: work item exceeded soft timeout budget

turn 110.4s turn · 10.4s LLM · 0.0s tools

feedbackLLM call failed: Empty: