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- import os
- os.environ['CUDA_VISIBLE_DEVICES'] = '0'
- import paddlex as pdx
- model = pdx.load_model('output/mobilenetv2/best_model')
- eval_dataset = pdx.datasets.ImageNet(
- data_dir='vegetables_cls',
- file_list='vegetables_cls/val_list.txt',
- label_list='vegetables_cls/labels.txt',
- transforms=model.eval_transforms)
- pdx.slim.prune.analysis(
- model,
- dataset=eval_dataset,
- batch_size=16,
- save_file='mobilenetv2.sensi.data')
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