benchmark() — pytorch Function Reference
Architecture documentation for the benchmark() function in kernels.py from the pytorch codebase.
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Dependency Diagram
graph TD a45d8f6b_d010_10b3_6034_08ec9eff9865["benchmark()"] 53bb1e84_568b_f953_f0ea_4ece045dd64e["get_shapes()"] a45d8f6b_d010_10b3_6034_08ec9eff9865 -->|calls| 53bb1e84_568b_f953_f0ea_4ece045dd64e 38cd02c9_bda5_f921_f4c9_f7772e1a880b["benchmark_single_shape()"] a45d8f6b_d010_10b3_6034_08ec9eff9865 -->|calls| 38cd02c9_bda5_f921_f4c9_f7772e1a880b style a45d8f6b_d010_10b3_6034_08ec9eff9865 fill:#6366f1,stroke:#818cf8,color:#fff
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Source Code
benchmarks/dynamo/genai_layers/kernels.py lines 274–279
def benchmark(self):
for M, N in self.get_shapes():
print(f"Tensor dimensions: [{M}, {N}]")
torch_dtype = cutlass_torch.dtype(cutlass.BFloat16)
x = 0.1 * torch.randn(M, N, device="cuda", dtype=torch_dtype)
self.benchmark_single_shape((x,), setting=f"shape: [{M}, {N}]")
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Frequently Asked Questions
What does benchmark() do?
benchmark() is a function in the pytorch codebase.
What does benchmark() call?
benchmark() calls 2 function(s): benchmark_single_shape, get_shapes.
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