识别模型导出
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@ -323,6 +323,20 @@ def eval(model, valid_dataloader, post_process_class, eval_class):
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return metirc
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def save_inference_mode(model, config, logger):
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model.eval()
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save_path = '{}/infer/{}'.format(config['Global']['save_model_dir'],
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config['Architecture']['model_type'])
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if config['Architecture']['model_type'] == 'rec':
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input_shape = [None, 3, 32, None]
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jit_model = paddle.jit.to_static(
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model, input_spec=[paddle.static.InputSpec(input_shape)])
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paddle.jit.save(jit_model, save_path)
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logger.info('inference model save to {}'.format(save_path))
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model.train()
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def preprocess():
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FLAGS = ArgsParser().parse_args()
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config = load_config(FLAGS.config)
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@ -334,7 +348,7 @@ def preprocess():
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alg = config['Architecture']['algorithm']
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assert alg in [
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'EAST', 'DB', 'SAST', 'Rosetta', 'CRNN', 'STARNet', 'RARE', 'SRN'
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'EAST', 'DB', 'SAST', 'Rosetta', 'CRNN', 'STARNet', 'RARE', 'SRN', 'CLS'
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]
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device = 'gpu:{}'.format(dist.ParallelEnv().dev_id) if use_gpu else 'cpu'
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@ -89,6 +89,7 @@ def main(config, device, logger, vdl_writer):
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program.train(config, train_dataloader, valid_dataloader, device, model,
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loss_class, optimizer, lr_scheduler, post_process_class,
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eval_class, pre_best_model_dict, logger, vdl_writer)
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program.save_inference_mode(model, config, logger)
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def test_reader(config, device, logger):
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@ -102,8 +103,8 @@ def test_reader(config, device, logger):
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if count % 1 == 0:
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batch_time = time.time() - starttime
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starttime = time.time()
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logger.info("reader: {}, {}, {}".format(count,
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len(data), batch_time))
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logger.info("reader: {}, {}, {}".format(
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count, len(data[0]), batch_time))
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except Exception as e:
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logger.info(e)
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logger.info("finish reader: {}, Success!".format(count))
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@ -112,4 +113,4 @@ def test_reader(config, device, logger):
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if __name__ == '__main__':
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config, device, logger, vdl_writer = program.preprocess()
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main(config, device, logger, vdl_writer)
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# test_reader(config, device, logger)
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# test_reader(config, device, logger)
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