Graph Capture (Prototype) — Intel® Extension for PyTorch* 2.7.0+cpu documentation (original) (raw)
Feature Description
This feature automatically applies a combination of TorchScript trace technique and TorchDynamo to try to generate a graph model, for providing a good user experience while keeping execution fast. Specifically, the process tries to generate a graph with TorchScript trace functionality first. In case of generation failure or incorrect results detected, it changes to TorchDynamo with TorchScript backend. Failure of the graph generation with TorchDynamo triggers a warning message. Meanwhile the generated graph model falls back to the original one. I.e. the inference workload runs in eager mode. Users can take advantage of this feature through a new knob --graph_mode of the ipex.optimize() function to automatically run into graph mode.
Usage Example
import torch import torchvision.models as models
model = models.resnet50(weights="ResNet50_Weights.DEFAULT") model.eval() data = torch.rand(1, 3, 224, 224)
#################### code changes #################### # noqa F401 import intel_extension_for_pytorch as ipex
model = ipex.optimize(model, graph_mode=True) ###################################################### # noqa F401
with torch.no_grad(): model(data)
print("Execution finished")