[cherry-pick]cherry pick fix on ocr and distillation for models-1.4 (#2111)

* Fix get_attention_feeder_for_infer (#2067)

* Fix distillation in slim demo. (#2107)

PaddleCV/ocr_recognition/infer.py

@@ -31,7 +31,7 @@ def inference(args):
     """OCR inference"""
     if args.model == "crnn_ctc":
         infer = ctc_infer
-        get_feeder_data = get_ctc_feeder_data
+        get_feeder_data = get_ctc_feeder_for_infer
     else:
         infer = attention_infer
         get_feeder_data = get_attention_feeder_for_infer
@@ -78,7 +78,7 @@ def inference(args):
     batch_times = []
     iters = 0
     for data in infer_reader():
-        feed_dict = get_feeder_data(data, place, need_label=False)
+        feed_dict = get_feeder_data(data, place)
         if args.iterations > 0 and iters == args.iterations + args.skip_batch_num:
             break
         if iters < args.skip_batch_num:

PaddleCV/ocr_recognition/utility.py

@@ -83,7 +83,8 @@ def get_ctc_feeder_data(data, place, need_label=True):
     pixel_tensor = core.LoDTensor()
     pixel_data = None
     pixel_data = np.concatenate(
-        list(map(lambda x: x[0][np.newaxis, :], data)), axis=0).astype("float32")
+        list(map(lambda x: x[0][np.newaxis, :], data)),
+        axis=0).astype("float32")
     pixel_tensor.set(pixel_data, place)
     label_tensor = to_lodtensor(list(map(lambda x: x[1], data)), place)
     if need_label:
@@ -92,11 +93,16 @@ def get_ctc_feeder_data(data, place, need_label=True):
         return {"pixel": pixel_tensor}
 
 
+def get_ctc_feeder_for_infer(data, place):
+    return get_ctc_feeder_data(data, place, need_label=False)
+
+
 def get_attention_feeder_data(data, place, need_label=True):
     pixel_tensor = core.LoDTensor()
     pixel_data = None
     pixel_data = np.concatenate(
-        list(map(lambda x: x[0][np.newaxis, :], data)), axis=0).astype("float32")
+        list(map(lambda x: x[0][np.newaxis, :], data)),
+        axis=0).astype("float32")
     pixel_tensor.set(pixel_data, place)
     label_in_tensor = to_lodtensor(list(map(lambda x: x[1], data)), place)
     label_out_tensor = to_lodtensor(list(map(lambda x: x[2], data)), place)
@@ -127,7 +133,8 @@ def get_attention_feeder_for_infer(data, place):
     pixel_tensor = core.LoDTensor()
     pixel_data = None
     pixel_data = np.concatenate(
-        list(map(lambda x: x[0][np.newaxis, :], data)), axis=0).astype("float32")
+        list(map(lambda x: x[0][np.newaxis, :], data)),
+        axis=0).astype("float32")
     pixel_tensor.set(pixel_data, place)
     return {
         "pixel": pixel_tensor,

PaddleSlim/configs/mobilenetv1_resnet50_distillation.yaml

@@ -7,7 +7,7 @@ distillers:
         distillation_loss_weight: 1
     l2_distiller:
         class: 'L2Distiller'
-        teacher_feature_map: 'fc_1.tmp_0'
+        teacher_feature_map: 'res_fc.tmp_0'
         student_feature_map: 'fc_0.tmp_0'
         distillation_loss_weight: 1
 strategies:

PaddleSlim/configs/quantization_dist.yaml

@@ -9,7 +9,7 @@ distillers:
         distillation_loss_weight: 1
     l2_distiller:
         class: 'L2Distiller'
-        teacher_feature_map: 'fc_1.tmp_0'
+        teacher_feature_map: 'res_fc.tmp_0'
         student_feature_map: 'fc_0.tmp_0'
         distillation_loss_weight: 1
 strategies:

PaddleSlim/run.sh

@@ -34,18 +34,22 @@ export CUDA_VISIBLE_DEVICES=0,1,2,3
 
 
 # Fixing name conflicts in distillation
-mv ResNet50_pretrained/conv1_weights ResNet50_pretrained/res_conv1_weights
-mv ResNet50_pretrained/fc_0.w_0 ResNet50_pretrained/res_fc.w_0
-mv ResNet50_pretrained/fc_0.b_0 ResNet50_pretrained/res_fc.b_0
+cd ${pretrain_dir}/ResNet50_pretrained
+mv conv1_weights res_conv1_weights
+mv fc_0.w_0 res_fc.w_0
+mv fc_0.b_0 res_fc.b_0
+cd -
 python compress.py \
 --model "MobileNet" \
 --teacher_model "ResNet50" \
 --teacher_pretrained_model ./pretrain/ResNet50_pretrained \
 --compress_config ./configs/mobilenetv1_resnet50_distillation.yaml
 
-mv ResNet50_pretrained/res_conv1_weights ResNet50_pretrained/conv1_weights
-mv ResNet50_pretrained/res_fc.w_0 ResNet50_pretrained/fc_0.w_0
-mv ResNet50_pretrained/res_fc.b_0 ResNet50_pretrained/fc_0.b_0
+cd ${pretrain_dir}/ResNet50_pretrained
+mv res_conv1_weights conv1_weights
+mv res_fc.w_0 fc_0.w_0
+mv res_fc.b_0 fc_0.b_0
+cd -
 
 # for sensitivity filter pruning
 #-------------------------------
@@ -74,28 +78,32 @@ mv ResNet50_pretrained/res_fc.b_0 ResNet50_pretrained/fc_0.b_0
 
 # for distillation with quantization
 #-----------------------------------
-#export CUDA_VISIBLE_DEVICES=0
+#export CUDA_VISIBLE_DEVICES=4,5,6,7
 #
 ## Fixing name conflicts in distillation
-#mv ResNet50_pretrained/conv1_weights ResNet50_pretrained/res_conv1_weights
-#mv ResNet50_pretrained/fc_0.w_0 ResNet50_pretrained/res_fc.w_0
-#mv ResNet50_pretrained/fc_0.b_0 ResNet50_pretrained/res_fc.b_0
+#cd ${pretrain_dir}/ResNet50_pretrained
+#mv conv1_weights res_conv1_weights
+#mv fc_0.w_0 res_fc.w_0
+#mv fc_0.b_0 res_fc.b_0
+#cd -
 #
 #python compress.py \
 #--model "MobileNet" \
 #--teacher_model "ResNet50" \
-#--teacher_pretrained_model ./data/pretrain/ResNet50_pretrained \
+#--teacher_pretrained_model ./pretrain/ResNet50_pretrained \
 #--compress_config ./configs/quantization_dist.yaml
 #
-#mv ResNet50_pretrained/res_conv1_weights ResNet50_pretrained/conv1_weights
-#mv ResNet50_pretrained/res_fc.w_0 ResNet50_pretrained/fc_0.w_0
-#mv ResNet50_pretrained/res_fc.b_0 ResNet50_pretrained/fc_0.b_0
+#cd ${pretrain_dir}/ResNet50_pretrained
+#mv res_conv1_weights conv1_weights
+#mv res_fc.w_0 fc_0.w_0
+#mv res_fc.b_0 fc_0.b_0
+#cd -
 
 # for uniform filter pruning with quantization
 #---------------------------------------------
 #export CUDA_VISIBLE_DEVICES=0
 #python compress.py \
 #--model "MobileNet" \
-#--pretrained_model ./data/pretrain/MobileNetV1_pretrained \
+#--pretrained_model ./pretrain/MobileNetV1_pretrained \
 #--compress_config ./configs/quantization_pruning.yaml