CPU Optimizer

Optimize models for CPU inference

Overview

optimize_for_cpu prepares a model for efficient CPU inference by combining:

  1. Channels-last memory format — optimizes layout for CNN operations on CPU
  2. Compilation — torch.compile (default) or torch.jit.trace for operator fusion
Backend Speed Compatibility Best For
"compile" Faster Most models Default choice
"trace" Good Requires static shapes Legacy / mobile 
from fasterai.misc.cpu_optimizer import optimize_for_cpu

model = resnet18(pretrained=True)
sample = torch.randn(1, 3, 224, 224)

# Default: torch.compile
optimized = optimize_for_cpu(model, sample)

# Or JIT trace for mobile/static shapes
traced = optimize_for_cpu(model, sample, backend="trace")

Note: accelerate_model_for_cpu is deprecated. Use optimize_for_cpu instead.

See Also