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1022443168
Test Plan: revert-hammer
Differential Revision:
D30279364 (b004307252)
Original commit changeset: c1ed77dfe43a
fbshipit-source-id: eab50857675c51e0088391af06ec0ecb14e2347e
40 lines
1.5 KiB
Python
40 lines
1.5 KiB
Python
"""
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This is a script for end-to-end mobile custom build test purpose. It prepares
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MobileNetV2 TorchScript model, and dumps root ops used by the model for custom
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build script to create a tailored build which only contains these used ops.
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"""
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import torch
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import torchvision
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import yaml
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# Download and trace the model.
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model = torchvision.models.mobilenet_v2(pretrained=True)
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model.eval()
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example = torch.rand(1, 3, 224, 224)
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traced_script_module = torch.jit.trace(model, example)
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# Save traced TorchScript model.
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traced_script_module.save("MobileNetV2.pt")
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# Dump root ops used by the model (for custom build optimization).
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ops = torch.jit.export_opnames(traced_script_module)
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# Besides the ops used by the model, custom c++ client code might use some extra
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# ops, too. For example, the dummy predictor.cpp driver in this test suite calls
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# `aten::ones` to create all-one-tensor for testing purpose, which is not used
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# by the MobileNetV2 model itself.
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#
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# This is less a problem for Android, where we expect users to use the limited
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# set of Java APIs. To actually solve this problem, we probably need ask users
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# to run code analyzer against their client code to dump these extra root ops.
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# So it will require more work to switch to custom build with dynamic dispatch -
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# in static dispatch case these extra ops will be kept by linker automatically.
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#
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# For CI purpose this one-off hack is probably fine? :)
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EXTRA_CI_ROOT_OPS = ['aten::ones']
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ops.extend(EXTRA_CI_ROOT_OPS)
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with open('MobileNetV2.yaml', 'w') as output:
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yaml.dump(ops, output)
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