(opt)
| 352 | |
| 353 | |
| 354 | def build_models(opt): |
| 355 | movement_enc = MovementConvEncoder(opt.dim_pose-4, opt.dim_movement_enc_hidden, opt.dim_movement_latent) |
| 356 | text_enc = TextEncoderBiGRUCo(word_size=opt.dim_word, |
| 357 | pos_size=opt.dim_pos_ohot, |
| 358 | hidden_size=opt.dim_text_hidden, |
| 359 | output_size=opt.dim_coemb_hidden, |
| 360 | device=opt.device) |
| 361 | |
| 362 | motion_enc = MotionEncoderBiGRUCo(input_size=opt.dim_movement_latent, |
| 363 | hidden_size=opt.dim_motion_hidden, |
| 364 | output_size=opt.dim_coemb_hidden, |
| 365 | device=opt.device) |
| 366 | |
| 367 | checkpoint = torch.load(pjoin('data/pretrained_models', opt.dataset_name, 'text_mot_match', 'model', 'finest.tar'), |
| 368 | map_location=opt.device) |
| 369 | movement_enc.load_state_dict(checkpoint['movement_encoder']) |
| 370 | text_enc.load_state_dict(checkpoint['text_encoder']) |
| 371 | motion_enc.load_state_dict(checkpoint['motion_encoder']) |
| 372 | print('Loading Evaluation Model Wrapper (Epoch %d) Completed!!' % (checkpoint['epoch'])) |
| 373 | return text_enc, motion_enc, movement_enc |
| 374 | |
| 375 | |
| 376 | class EvaluatorModelWrapper(object): |
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