| | |
| | | export_dir=export_dir, |
| | | **kwargs, |
| | | ) |
| | | elif type == "torchscripts": |
| | | elif type == "torchscript": |
| | | device = "cuda" if torch.cuda.is_available() else "cpu" |
| | | print("Exporting torchscripts on device {}".format(device)) |
| | | _torchscripts(m, path=export_dir, device=device) |
| | |
| | | dummy_input = tuple([i.cuda() for i in dummy_input]) |
| | | |
| | | model_script = torch.jit.trace(model, dummy_input) |
| | | model_script.save(os.path.join(path, f"{model.export_name}.torchscripts")) |
| | | model_script.save(os.path.join(path, f"{model.export_name}.torchscript")) |
| | | |
| | | |
| | | def _bladedisc_opt(model, model_inputs, enable_fp16=True): |
| | |
| | | model.encoder = _bladedisc_opt(model.encoder, input_data[:2]) |
| | | model.decoder = _bladedisc_opt(model.decoder, tuple(decoder_inputs)) |
| | | model_script = torch.jit.trace(model, input_data) |
| | | model_script.save(os.path.join(path, f"{model.export_name}_blade.torchscripts")) |
| | | model_script.save(os.path.join(path, f"{model.export_name}_blade.torchscript")) |