Merge pull request #161 from LielinJiang/fix_bug_0211

fix nas python3 bug and update distill pretrained model

slim/distillation/README.md

@@ -69,7 +69,10 @@ distill_loss = l2_loss('teacher_bilinear_interp_2.tmp_0', 'bilinear_interp_0.tmp
 在该脚本中定义了teacher_model和student_model，用teacher_model的输出指导student_model的训练
 
 ### 执行示例
-如下命令启动训练，每间隔```cfg.TRAIN.SNAPSHOT_EPOCH```会进行一次评估。
+
+下载teacher的预训练模型和student的预训练模型, 替换如下命令中的```your_tearcher_pretrained_model_path```和```your_student_pretrained_model```
+
+执行如下命令启动训练，每间隔```cfg.TRAIN.SNAPSHOT_EPOCH```会进行一次评估。
 ```shell
 CUDA_VISIBLE_DEVICES=0,1 
 python -m paddle.distributed.launch ./slim/distillation/train_distill.py \
@@ -77,7 +80,9 @@ python -m paddle.distributed.launch ./slim/distillation/train_distill.py \
 --teacher_cfg ./slim/distillation/cityscape_teacher.yaml \
 --use_gpu \
 --use_mpio \
---do_eval
+--do_eval \
+SLIM.KNOWLEDGE_DISTILL_TEACHER_MODEL_DIR your_tearcher_pretrained_model_path \
+TRAIN.PRETRAINED_MODEL_DIR your_student_pretrained_model
 ```
 
 ## 评估预测

slim/distillation/cityscape.yaml

@@ -49,7 +49,7 @@ TEST:
     TEST_MODEL: "snapshots/cityscape_v5/final/"
 TRAIN:
     MODEL_SAVE_DIR: "snapshots/cityscape_mbv2_kd_e100_1/"
-    PRETRAINED_MODEL_DIR: u"/workspace/pretrained_models/mobilenet_cityscapes"
+    PRETRAINED_MODEL_DIR: u"pretrained_model/mobilenet_cityscapes"
     SNAPSHOT_EPOCH: 5
     SYNC_BATCH_NORM: True
 SOLVER:

slim/distillation/cityscape_teacher.yaml

@@ -61,5 +61,5 @@ SOLVER:
 SLIM:
     KNOWLEDGE_DISTILL_IS_TEACHER: True
     KNOWLEDGE_DISTILL: True
-    KNOWLEDGE_DISTILL_TEACHER_MODEL_DIR: "/workspace/pretrained_models/xception65_bn_cityscapes"
+    KNOWLEDGE_DISTILL_TEACHER_MODEL_DIR: "pretrained_model/xception65_bn_cityscapes"
 

slim/nas/README.md

@@ -46,7 +46,7 @@ SLIM:
 ## 训练与评估
 执行以下命令，边训练边评估
 ```shell
-python -u ./slim/nas/train_nas.py --log_steps 10 --cfg configs/deeplabv3p_mobilenetv2_cityscapes.yaml --use_gpu --use_mpio \
+CUDA_VISIBLE_DEVICES=0 python -u ./slim/nas/train_nas.py --log_steps 10 --cfg configs/deeplabv3p_mobilenetv2_cityscapes.yaml --use_gpu --use_mpio \
 SLIM.NAS_PORT 23333 \
 SLIM.NAS_ADDRESS "" \
 SLIM.NAS_SEARCH_STEPS 2 \

slim/nas/mobilenetv2_search_space.py

@@ -180,7 +180,7 @@ class MobileNetV2SpaceSeg(SearchSpaceBase):
                     c=int(c * self.scale),
                     n=n,
                     s=s,
-                    k=k,
+                    k=int(k),
                     name='mobilenetv2_conv' + str(i))
                 in_c = int(c * self.scale)