提交 c07d1ffe 编写于 作者: W wuzewu

Update demo

上级 8917fb23
import paddle.fluid as fluid import paddle
import paddlehub as hub import paddlehub as hub
from paddle.fluid.dygraph.parallel import ParallelEnv from paddle.distributed import ParallelEnv
from paddlehub.finetune.trainer import Trainer from paddlehub.finetune.trainer import Trainer
from paddlehub.datasets.flowers import Flowers from paddlehub.datasets.flowers import Flowers
from paddlehub.process.transforms import Compose, Resize, Normalize from paddlehub.process.transforms import Compose, Resize, Normalize
from paddlehub.module.cv_module import ImageClassifierModule from paddlehub.module.cv_module import ImageClassifierModule
if __name__ == '__main__': if __name__ == '__main__':
with fluid.dygraph.guard(fluid.CUDAPlace(ParallelEnv().dev_id)): paddle.disable_static(paddle.CUDAPlace(ParallelEnv().dev_id))
transforms = Compose([Resize((224, 224)), Normalize()]) transforms = Compose([Resize((224, 224)), Normalize()])
flowers = Flowers(transforms) flowers = Flowers(transforms)
flowers_validate = Flowers(transforms, mode='val') flowers_validate = Flowers(transforms, mode='val')
model = hub.Module(directory='mobilenet_v2_animals', class_dim=flowers.num_classes) model = hub.Module(name='mobilenet_v2_imagenet', class_dim=flowers.num_classes)
# model = hub.Module(name='mobilenet_v2_animals', class_dim=flowers.num_classes)
optimizer = fluid.optimizer.AdamOptimizer(learning_rate=0.001, parameter_list=model.parameters()) optimizer = paddle.optimizer.Adam(learning_rate=0.001, parameters=model.parameters())
trainer = Trainer(model, optimizer, checkpoint_dir='test_ckpt_img_cls') trainer = Trainer(model, optimizer, checkpoint_dir='test_ckpt_img_cls')
trainer.train(flowers, epochs=100, batch_size=32, eval_dataset=flowers_validate, save_interval=1) trainer.train(flowers, epochs=100, batch_size=32, eval_dataset=flowers_validate, save_interval=1)
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