def test_quantize_torchscript(tmpdir): """Test converting to torchscipt """ dm = RegressDataModule() qmodel = RegressionModel() qcb = QuantizationAwareTraining(input_compatible=False) trainer = Trainer(callbacks=[qcb], default_root_dir=tmpdir, max_epochs=1) trainer.fit(qmodel, datamodule=dm) qmodel.to_torchscript()
def test_quantize_torchscript(tmpdir): """Test converting to torchscipt.""" dm = RegressDataModule() qmodel = RegressionModel() qcb = QuantizationAwareTraining(input_compatible=False) trainer = Trainer(callbacks=[qcb], default_root_dir=tmpdir, max_epochs=1) trainer.fit(qmodel, datamodule=dm) batch = iter(dm.test_dataloader()).next() qmodel(qmodel.quant(batch[0])) tsmodel = qmodel.to_torchscript() tsmodel(tsmodel.quant(batch[0]))