fix imagenet ac demo (#1136)

* fix imagenet ac demo

* update

demo/auto_compression/detection/README.md

@@ -95,7 +95,7 @@ tar -xf ppyoloe_crn_l_300e_coco.tar
 
 使用run.py脚本得到模型的mAP：
 ```
-export CUDA_VISIBLE_DEVEICES=0
+export CUDA_VISIBLE_DEVICES=0
 python run.py --config_path=./configs/ppyoloe_l_qat_dis.yaml --eval=True
 ```
 
@@ -105,7 +105,7 @@ python run.py --config_path=./configs/ppyoloe_l_qat_dis.yaml --eval=True
 
 蒸馏量化自动压缩示例通过run.py脚本启动，会使用接口```paddleslim.auto_compression.AutoCompression```对模型进行自动压缩。配置config文件中模型路径、蒸馏、量化、和训练等部分的参数，配置完成后便可对模型进行量化和蒸馏。具体运行命令为：
 ```
-export CUDA_VISIBLE_DEVEICES=0
+export CUDA_VISIBLE_DEVICES=0
 python run.py --config_path=./configs/ppyoloe_l_qat_dis.yaml --save_dir='./output/'
 ```
 

demo/auto_compression/image_classification/README.md

@@ -69,7 +69,7 @@ tar -xf MobileNetV1_infer.tar
 
 ```shell
 # 单卡启动
-export CUDA_VISIBLE_DEVEICES=0
+export CUDA_VISIBLE_DEVICES=0
 python run.py \
     --model_dir='MobileNetV1_infer' \
     --model_filename='inference.pdmodel' \

demo/auto_compression/image_classification/run.py

@@ -92,7 +92,7 @@ if __name__ == '__main__':
     args = parser.parse_args()
     print_arguments(args)
     paddle.enable_static()
-    compress_config, train_config = load_config(args.config_path)
+    compress_config, train_config, _ = load_config(args.config_path)
     data_dir = args.data_dir
 
     train_reader = paddle.batch(

demo/auto_compression/image_classification/run.sh

 # 单卡启动
-export CUDA_VISIBLE_DEVEICES=0
+export CUDA_VISIBLE_DEVICES=0
 python run.py \
     --model_dir='MobileNetV1_infer' \
     --model_filename='inference.pdmodel' \

demo/auto_compression/nlp/README.md

@@ -88,7 +88,7 @@ tar -zxvf afqmc.tar
 数据集为CLUE，不同任务名称代表CLUE上不同的任务，可选择的任务名称有：afqmc, tnews, iflytek, ocnli, cmnli, cluewsc2020, csl。具体运行命令为
 ：
 ```shell
-export CUDA_VISIBLE_DEVEICES=0
+export CUDA_VISIBLE_DEVICES=0
 python run.py \
     --model_type='ppminilm' \
     --model_dir='./afqmc/' \

paddleslim/auto_compression/compressor.py

@@ -36,7 +36,7 @@ _logger = get_logger(__name__, level=logging.INFO)
 
 try:
     if platform.system().lower() == 'linux':
-        from ..quant.quant_post_hpo import quant_post_hpo
+        from ..quant import quant_post_hpo
 except Exception as e:
     _logger.warning(e)