diff --git a/PaddleCV/PaddleDetection/tools/eval.py b/PaddleCV/PaddleDetection/tools/eval.py
index 4c941863decf7ce23383d5de03b179aae523769a..6e15044884ad94503283683beae3c93e7fa1cec7 100644
--- a/PaddleCV/PaddleDetection/tools/eval.py
+++ b/PaddleCV/PaddleDetection/tools/eval.py
@@ -18,19 +18,6 @@ from __future__ import print_function
 
 import os
 
-
-def set_paddle_flags(**kwargs):
-    for key, value in kwargs.items():
-        if os.environ.get(key, None) is None:
-            os.environ[key] = str(value)
-
-
-# NOTE(paddle-dev): All of these flags should be set before
-# `import paddle`. Otherwise, it would not take any effect.
-set_paddle_flags(
-    FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
-)
-
 import paddle.fluid as fluid
 
 from ppdet.utils.eval_utils import parse_fetches, eval_run, eval_results, json_eval_results
diff --git a/PaddleCV/PaddleDetection/tools/infer.py b/PaddleCV/PaddleDetection/tools/infer.py
index 64049e3fc2b513d6e1e8946edc4bb33518ea8f40..8097a9cae6191d32daadd17bfea779a20fe91ee8 100644
--- a/PaddleCV/PaddleDetection/tools/infer.py
+++ b/PaddleCV/PaddleDetection/tools/infer.py
@@ -22,19 +22,6 @@ import glob
 import numpy as np
 from PIL import Image
 
-
-def set_paddle_flags(**kwargs):
-    for key, value in kwargs.items():
-        if os.environ.get(key, None) is None:
-            os.environ[key] = str(value)
-
-
-# NOTE(paddle-dev): All of these flags should be set before
-# `import paddle`. Otherwise, it would not take any effect.
-set_paddle_flags(
-    FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
-)
-
 from paddle import fluid
 
 from ppdet.utils.cli import print_total_cfg
diff --git a/PaddleCV/PaddleDetection/tools/train.py b/PaddleCV/PaddleDetection/tools/train.py
index b9099210edecf41f4ff548166ae36c043dfc59b5..a96d50f4a4eb189762f994fe363ba5c9dbdb400d 100644
--- a/PaddleCV/PaddleDetection/tools/train.py
+++ b/PaddleCV/PaddleDetection/tools/train.py
@@ -22,19 +22,6 @@ import numpy as np
 import datetime
 from collections import deque
 
-
-def set_paddle_flags(**kwargs):
-    for key, value in kwargs.items():
-        if os.environ.get(key, None) is None:
-            os.environ[key] = str(value)
-
-
-# NOTE(paddle-dev): All of these flags should be set before
-# `import paddle`. Otherwise, it would not take any effect.
-set_paddle_flags(
-    FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
-)
-
 from paddle import fluid
 
 from ppdet.experimental import mixed_precision_context
diff --git a/PaddleCV/PaddleGAN/cycle_gan/train.py b/PaddleCV/PaddleGAN/cycle_gan/train.py
index a85da0ae2c97e95aa7d8de5a6ef5661988c84971..5b2b4e40a9b834d8a7d440cf1a390f43ee3edba3 100644
--- a/PaddleCV/PaddleGAN/cycle_gan/train.py
+++ b/PaddleCV/PaddleGAN/cycle_gan/train.py
@@ -35,13 +35,7 @@ else:
 # not take any effect. 
 set_paddle_flags({
     'FLAGS_cudnn_exhaustive_search': use_cudnn_exhaustive_search,
-    'FLAGS_conv_workspace_size_limit': 256,
-    'FLAGS_eager_delete_tensor_gb': 0,  # enable gc 
-    # You can omit the following settings, because the default
-    # value of FLAGS_memory_fraction_of_eager_deletion is 1,
-    # and default value of FLAGS_fast_eager_deletion_mode is 1 
-    'FLAGS_memory_fraction_of_eager_deletion': 1,
-    'FLAGS_fast_eager_deletion_mode': 1
+    'FLAGS_conv_workspace_size_limit': 256
 })
 
 import random
diff --git a/PaddleCV/PaddleGAN/scripts/run_SPADE.sh b/PaddleCV/PaddleGAN/scripts/run_SPADE.sh
index 3833dc7db480a8a5428abec19f35f96fe8b96ba9..312f48fd21452b6a835fbc4cb5b63579d88a3e81 100644
--- a/PaddleCV/PaddleGAN/scripts/run_SPADE.sh
+++ b/PaddleCV/PaddleGAN/scripts/run_SPADE.sh
@@ -1,4 +1,2 @@
-export FLAGS_eager_delete_tensor_gb=0.0
-export FLAGS_fast_eager_deletion_mode=1
 export FLAGS_fraction_of_gpu_memory_to_use=0.01
 CUDA_VISIBLE_DEVICES=0 python train.py --model_net SPADE --dataset cityscapes --train_list train_list --test_list val_list --crop_type Random --batch_size 1 --epoch 200 --load_height 612 --load_width 1124 --crop_height 512 --crop_width 1024 --label_nc 36
diff --git a/PaddleCV/PaddleVideo/models/bmn/README.md b/PaddleCV/PaddleVideo/models/bmn/README.md
index 36f0857dbf611741d5d58c3fe4d1fac99d2112a4..c146e650e3b9b624ecaa7c37a3d652eae799679a 100644
--- a/PaddleCV/PaddleVideo/models/bmn/README.md
+++ b/PaddleCV/PaddleVideo/models/bmn/README.md
@@ -29,9 +29,7 @@ BMN的训练数据采用ActivityNet1.3提供的数据集，数据下载及准备
 数据准备完毕后，可以通过如下两种方式启动训练：
 
     export CUDA_VISIBLE_DEVICES=0,1,2,3
-    export FLAGS_eager_delete_tensor_gb=0.0
     export FLAGS_fraction_of_gpu_memory_to_use=0.98
-    export FLAGS_fast_eager_deletion_mode=1
     python train.py --model_name=BMN \
                     --config=./configs/bmn.yaml \
                     --log_interval=10 \
diff --git a/PaddleCV/PaddleVideo/models/bsn/README.md b/PaddleCV/PaddleVideo/models/bsn/README.md
index a4d0374b29c6691fc03722a0300471177d7e5ee0..7e9572d4e56fa80b228077a987075b18deb111fc 100644
--- a/PaddleCV/PaddleVideo/models/bsn/README.md
+++ b/PaddleCV/PaddleVideo/models/bsn/README.md
@@ -30,9 +30,7 @@ TEM模块以snippet-level的特征序列作为输入，预测每一个时序位
 数据准备完毕后，可以通过如下两种方式启动训练：
 
     export CUDA_VISIBLE_DEVICES=0
-    export FLAGS_eager_delete_tensor_gb=0.0
     export FLAGS_fraction_of_gpu_memory_to_use=0.98
-    export FLAGS_fast_eager_deletion_mode=1
     python train.py --model_name=BsnTem \
                     --config=./configs/bsn_tem.yaml \
                     --log_interval=10 \
@@ -60,9 +58,7 @@ PEM模块以PGM模块输出的BSP特征作为输入，输出proposal包含动作
 数据准备完毕后，可以通过如下两种方式启动训练：
 
     export CUDA_VISIBLE_DEVICES=0
-    export FLAGS_eager_delete_tensor_gb=0.0
     export FLAGS_fraction_of_gpu_memory_to_use=0.98
-    export FLAGS_fast_eager_deletion_mode=1
     python train.py --model_name=BsnPem \
                     --config=./configs/bsn_pem.yaml \
                     --log_interval=10 \
diff --git a/PaddleCV/PaddleVideo/models/ctcn/README.md b/PaddleCV/PaddleVideo/models/ctcn/README.md
index bded28629ebfe5f5ffabcf461c020bf23901560a..b33e902b13e5256c4d36bae553f2c353b09398db 100644
--- a/PaddleCV/PaddleVideo/models/ctcn/README.md
+++ b/PaddleCV/PaddleVideo/models/ctcn/README.md
@@ -25,8 +25,6 @@ C-TCN的训练数据采用ActivityNet1.3提供的数据集，数据下载及准
 数据准备完毕后，可以通过如下两种方式启动训练：
 
     export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-    export FLAGS_fast_eager_deletion_mode=1
-    export FLAGS_eager_delete_tensor_gb=0.0
     export FLAGS_fraction_of_gpu_memory_to_use=0.98
     python train.py --model_name=CTCN \
                     --config=./configs/ctcn.yaml \
diff --git a/PaddleCV/PaddleVideo/models/tsm/README.md b/PaddleCV/PaddleVideo/models/tsm/README.md
index 0364799e6180db3ad28e7ac85b3deb6fe38f024e..3526b9bdf3395941cb9c557c275dc7faf291bb49 100644
--- a/PaddleCV/PaddleVideo/models/tsm/README.md
+++ b/PaddleCV/PaddleVideo/models/tsm/README.md
@@ -35,8 +35,6 @@ TSM的训练数据采用由DeepMind公布的Kinetics-400动作识别数据集。
 数据准备完毕后，可以通过如下两种方式启动训练：
 
     export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-    export FLAGS_fast_eager_deletion_mode=1
-    export FLAGS_eager_delete_tensor_gb=0.0
     export FLAGS_fraction_of_gpu_memory_to_use=0.98
     python train.py --model_name=TSM \
                     --config=./configs/tsm.yaml \
diff --git a/PaddleCV/PaddleVideo/models/tsn/README.md b/PaddleCV/PaddleVideo/models/tsn/README.md
index 80ca3268886b98a225f194bed5e8b6e88ea37b69..52bc4ff01977402f3d4cbf723f8a76a194b5754b 100644
--- a/PaddleCV/PaddleVideo/models/tsn/README.md
+++ b/PaddleCV/PaddleVideo/models/tsn/README.md
@@ -26,8 +26,6 @@ TSN的训练数据采用由DeepMind公布的Kinetics-400动作识别数据集。
 数据准备完毕后，可以通过如下两种方式启动训练：
 
     export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-    export FLAGS_fast_eager_deletion_mode=1
-    export FLAGS_eager_delete_tensor_gb=0.0
     export FLAGS_fraction_of_gpu_memory_to_use=0.98
     python train.py --model_name=TSN \
                     --config=./configs/tsn.yaml \
diff --git a/PaddleCV/PaddleVideo/run.sh b/PaddleCV/PaddleVideo/run.sh
index 635e3a38439706f21adb877625bbb8a61b99dc58..66698277ec6e03e648f880b983df6a8ecd878101 100644
--- a/PaddleCV/PaddleVideo/run.sh
+++ b/PaddleCV/PaddleVideo/run.sh
@@ -25,8 +25,6 @@ weights="" #set the path of weights to enable eval and predicut, just ignore thi
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
 #export CUDA_VISIBLE_DEVICES=0,1,2,3
 #export CUDA_VISIBLE_DEVICES=0
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 if [ "$mode"x == "train"x ]; then
diff --git a/PaddleCV/PaddleVideo/run_ce.sh b/PaddleCV/PaddleVideo/run_ce.sh
index e848755d432c91e125061e11506cecd61e20c15b..548562e9ab4333b3b7b881ade83f953e55d8cd7d 100755
--- a/PaddleCV/PaddleVideo/run_ce.sh
+++ b/PaddleCV/PaddleVideo/run_ce.sh
@@ -1,7 +1,5 @@
 #!/bin/bash
 
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 export CUDA_VISIBLE_DEVICES=0
 
diff --git a/PaddleCV/deeplabv3+/train.py b/PaddleCV/deeplabv3+/train.py
index e0a1f10b8d3caecf504b95230d4fa8ac9e2e9fd9..be46915fdaa38ce8c89edfcdb895d69b1df9bc1e 100755
--- a/PaddleCV/deeplabv3+/train.py
+++ b/PaddleCV/deeplabv3+/train.py
@@ -27,12 +27,6 @@ def set_paddle_flags(flags):
 # set before `import paddle`. Otherwise, it would
 # not take any effect. 
 set_paddle_flags({
-    'FLAGS_eager_delete_tensor_gb': 0,  # enable GC 
-    # You can omit the following settings, because the default
-    # value of FLAGS_memory_fraction_of_eager_deletion is 1,
-    # and default value of FLAGS_fast_eager_deletion_mode is 1 
-    'FLAGS_memory_fraction_of_eager_deletion': 1,
-    'FLAGS_fast_eager_deletion_mode': 1,
     # Setting the default used gpu memory
     'FLAGS_fraction_of_gpu_memory_to_use': 0.98
 })
diff --git a/PaddleCV/face_detection/train.py b/PaddleCV/face_detection/train.py
index c74cc8c62c63a0aca7c831f05e4b5cfaca1f7b92..4eecabe07ab7a5f29e310ee11e69baacb5ed4329 100644
--- a/PaddleCV/face_detection/train.py
+++ b/PaddleCV/face_detection/train.py
@@ -21,21 +21,6 @@ import numpy as np
 import time
 import argparse
 import functools
-
-
-def set_paddle_flags(**kwargs):
-    for key, value in kwargs.items():
-        if os.environ.get(key, None) is None:
-            os.environ[key] = str(value)
-
-
-# NOTE(paddle-dev): All of these flags should be
-# set before `import paddle`. Otherwise, it would
-# not take any effect. 
-set_paddle_flags(
-    FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
-)
-
 import paddle
 import paddle.fluid as fluid
 from pyramidbox import PyramidBox
diff --git a/PaddleCV/image_classification/scripts/train/AlexNet.sh b/PaddleCV/image_classification/scripts/train/AlexNet.sh
index 6919f2b969f8f67f7de666a8f133cc7b4b779dbe..ac950db66986e7206a1253f51a0dca9a24f6d13c 100644
--- a/PaddleCV/image_classification/scripts/train/AlexNet.sh
+++ b/PaddleCV/image_classification/scripts/train/AlexNet.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® P40  8cards 120epochs 55h
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #AlexNet:
diff --git a/PaddleCV/image_classification/scripts/train/EfficientNetB0.sh b/PaddleCV/image_classification/scripts/train/EfficientNetB0.sh
index 37a5d9a4524e06e4dfa77c1527d2dc5d7be6a222..18dce3ac10fdde5ce496150b641f3544ba5a04ed 100644
--- a/PaddleCV/image_classification/scripts/train/EfficientNetB0.sh
+++ b/PaddleCV/image_classification/scripts/train/EfficientNetB0.sh
@@ -1,6 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.96
 
 
diff --git a/PaddleCV/image_classification/scripts/train/GoogLeNet.sh b/PaddleCV/image_classification/scripts/train/GoogLeNet.sh
index 63171b31691466bcf6c66a7153faf3dc2f80d203..d7c8c445906d4a31df2dfa25a74f3c7ccd1c0153 100644
--- a/PaddleCV/image_classification/scripts/train/GoogLeNet.sh
+++ b/PaddleCV/image_classification/scripts/train/GoogLeNet.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100 4cards 200epochs 132h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #GoogLeNet:
diff --git a/PaddleCV/image_classification/scripts/train/InceptionV4.sh b/PaddleCV/image_classification/scripts/train/InceptionV4.sh
index ba3c4954c62cd494dba3822eb0a41429023ce33a..17bf5ed9f14568bcccb370bad8129f004e746f7e 100644
--- a/PaddleCV/image_classification/scripts/train/InceptionV4.sh
+++ b/PaddleCV/image_classification/scripts/train/InceptionV4.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100 8cards 200epochs 367h
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #InceptionV4
diff --git a/PaddleCV/image_classification/scripts/train/MobileNetV1.sh b/PaddleCV/image_classification/scripts/train/MobileNetV1.sh
index 8d00ce7c8c073fdbbdc220d8c8bf4289ff4ba659..02167a855d55568ccfbce34358e344701a5ab163 100644
--- a/PaddleCV/image_classification/scripts/train/MobileNetV1.sh
+++ b/PaddleCV/image_classification/scripts/train/MobileNetV1.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100 4cards 120epochs 55h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 
diff --git a/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_25.sh b/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_25.sh
index aa7f74ba8eb394f28a296fff7b26b13972e49afe..d3e61d656ef86df72e19e84601a48ec378667668 100644
--- a/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_25.sh
+++ b/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_25.sh
@@ -1,6 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 
diff --git a/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_5.sh b/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_5.sh
index 85fdbfdc255b618ad000063931f62f42ae43c380..56f8418b75298ce12bbe4a2a3c39d2160c502697 100644
--- a/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_5.sh
+++ b/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_5.sh
@@ -1,6 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 
diff --git a/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_75.sh b/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_75.sh
index ceeba7449b09a8b87ebb4d6d829907d641f698c0..14a36158041b2d02842b43024c995ae7e9ca1eb1 100644
--- a/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_75.sh
+++ b/PaddleCV/image_classification/scripts/train/MobileNetV1_x0_75.sh
@@ -1,6 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 
diff --git a/PaddleCV/image_classification/scripts/train/MobileNetV2.sh b/PaddleCV/image_classification/scripts/train/MobileNetV2.sh
index 7a0ce41cadb54030f06534ea5f64cffc1b171bf0..cd116ac7b118ba3fcd0f58f954fc2f1890c39382 100644
--- a/PaddleCV/image_classification/scripts/train/MobileNetV2.sh
+++ b/PaddleCV/image_classification/scripts/train/MobileNetV2.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100 4cards 240epochs 135h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 
diff --git a/PaddleCV/image_classification/scripts/train/MobileNetV2_x0_75.sh b/PaddleCV/image_classification/scripts/train/MobileNetV2_x0_75.sh
index 511cfa71e5189e2dc0b34e7606e216e5fc97a1d3..092adf10fe2e705b16e3a0ed73a7068f472ce9a1 100644
--- a/PaddleCV/image_classification/scripts/train/MobileNetV2_x0_75.sh
+++ b/PaddleCV/image_classification/scripts/train/MobileNetV2_x0_75.sh
@@ -1,6 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 
diff --git a/PaddleCV/image_classification/scripts/train/ResNeXt101_32x4d.sh b/PaddleCV/image_classification/scripts/train/ResNeXt101_32x4d.sh
index 91d8b5bbae3cb6a580d2bdc9c808c8386a4bb4a5..192157c9f4096f959b0378892ef1e2dac455fdaf 100644
--- a/PaddleCV/image_classification/scripts/train/ResNeXt101_32x4d.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNeXt101_32x4d.sh
@@ -1,8 +1,6 @@
 #Training details
 #Missed
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNeXt101_32x4d
diff --git a/PaddleCV/image_classification/scripts/train/ResNeXt101_64x4d.sh b/PaddleCV/image_classification/scripts/train/ResNeXt101_64x4d.sh
index f5aeb3a308719bad13f83f930a8d9c0e12d8daad..0c35add3067886959b09dab5d10d5e509216e7c9 100644
--- a/PaddleCV/image_classification/scripts/train/ResNeXt101_64x4d.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNeXt101_64x4d.sh
@@ -1,8 +1,6 @@
 #Training details
 #Missed
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNeXt101_64x4d
diff --git a/PaddleCV/image_classification/scripts/train/ResNeXt101_vd_32x4d.sh b/PaddleCV/image_classification/scripts/train/ResNeXt101_vd_32x4d.sh
index 5e9344808d2e4e826805ea2c2ff7793f554c59db..6db60b84fee7a571941ff58b2fec96add6e3b625 100644
--- a/PaddleCV/image_classification/scripts/train/ResNeXt101_vd_32x4d.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNeXt101_vd_32x4d.sh
@@ -1,8 +1,6 @@
 #Training details
 #Missed
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNeXt101_vd_32x4d
diff --git a/PaddleCV/image_classification/scripts/train/ResNeXt101_vd_64x4d.sh b/PaddleCV/image_classification/scripts/train/ResNeXt101_vd_64x4d.sh
index f3d117798edf33acd9f4d9b8e29bdd987a9ece9c..eff719517c1cff6f88478f5b1a839ee324fda101 100644
--- a/PaddleCV/image_classification/scripts/train/ResNeXt101_vd_64x4d.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNeXt101_vd_64x4d.sh
@@ -1,8 +1,6 @@
 #Training details
 #Missed
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNeXt101_vd_64x4d
diff --git a/PaddleCV/image_classification/scripts/train/ResNeXt152_64x4d.sh b/PaddleCV/image_classification/scripts/train/ResNeXt152_64x4d.sh
index 0a1bd5180de93f702b29b80072c2e00425bb90fc..39e8a39e62d068d851e68337a314e835cc98cbae 100644
--- a/PaddleCV/image_classification/scripts/train/ResNeXt152_64x4d.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNeXt152_64x4d.sh
@@ -1,7 +1,5 @@
 #Training details
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNeXt152_64x4d
diff --git a/PaddleCV/image_classification/scripts/train/ResNet101.sh b/PaddleCV/image_classification/scripts/train/ResNet101.sh
index a2af43854b4464da1b2c7077d89e8b155d207e9f..28b8ccfa0de3caa3fe73e6dbd638cd5b96f2f42f 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet101.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet101.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® V100 4cards 120epochs 100h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNet101:
diff --git a/PaddleCV/image_classification/scripts/train/ResNet101_vd.sh b/PaddleCV/image_classification/scripts/train/ResNet101_vd.sh
index b9bdf778481b6fe1b6bace474bab31053f87c6c2..a7dc7983eeeaf180049c5417c6bb04e7420e7732 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet101_vd.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet101_vd.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100  4cards 200epochs 182h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNet101_vd
diff --git a/PaddleCV/image_classification/scripts/train/ResNet152.sh b/PaddleCV/image_classification/scripts/train/ResNet152.sh
index 44275753a3eab22f78bfc02305c98dff59d55508..373cecb84f63b44128a1c3b2dcddb8a7a22d9061 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet152.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet152.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® P40 8cards 120epochs 200h
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNet152:
diff --git a/PaddleCV/image_classification/scripts/train/ResNet152_vd.sh b/PaddleCV/image_classification/scripts/train/ResNet152_vd.sh
index b4cb84ad191ee57749fdfad08428fa5e328bbdf0..500b4628db420297359f6184b1e38b5a5456ce87 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet152_vd.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet152_vd.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® P40 8cards 200epochs 346h
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 python train.py \
diff --git a/PaddleCV/image_classification/scripts/train/ResNet18.sh b/PaddleCV/image_classification/scripts/train/ResNet18.sh
index b3d1018ce0daa0f4f3871e0109bdc293f5d6f81d..e6cfe9a7696d850c67356f6e21c31251f990a3da 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet18.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet18.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® V100 4cards 120epochs 67h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNet18:
diff --git a/PaddleCV/image_classification/scripts/train/ResNet18_vd.sh b/PaddleCV/image_classification/scripts/train/ResNet18_vd.sh
index c95b9325ead9ff30b8f61d9f247f5abc56c6bd3e..4bc122d2b3fb9a160474c2698303974ac2063fa2 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet18_vd.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet18_vd.sh
@@ -1,6 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 python train.py \
diff --git a/PaddleCV/image_classification/scripts/train/ResNet200_vd.sh b/PaddleCV/image_classification/scripts/train/ResNet200_vd.sh
index 464db8ac77cc80d6fd441d638d5ee74e2ed3cdf0..cb9f14da066e9e45b2f5c16947b286548d303e19 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet200_vd.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet200_vd.sh
@@ -1,8 +1,6 @@
 #Training details
 #Machine: Missed
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNet200_vd
diff --git a/PaddleCV/image_classification/scripts/train/ResNet34.sh b/PaddleCV/image_classification/scripts/train/ResNet34.sh
index 5ce4689be4c2c67a9d20c3187ba93064fb536b26..f4f2b0d6499da35b9bff4a6fb90dfb25e0d1c641 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet34.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet34.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100 4cards 120epochs 73h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 #ResNet34:
 python train.py \
diff --git a/PaddleCV/image_classification/scripts/train/ResNet34_vd.sh b/PaddleCV/image_classification/scripts/train/ResNet34_vd.sh
index 56a31b699d19f39987f6f4be79a5e0b8e9c4e07d..14df38da0416ce808936bf12d2052d3d55b7b5f8 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet34_vd.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet34_vd.sh
@@ -1,6 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 python train.py \
diff --git a/PaddleCV/image_classification/scripts/train/ResNet50.sh b/PaddleCV/image_classification/scripts/train/ResNet50.sh
index 470630757aa4446fecd42bd45e11a77d89c453fa..1c68daec344c4e70b90796704ae1c0ffaeebe76e 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet50.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet50.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® V100 4cards 120epochs 67h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNet50:
diff --git a/PaddleCV/image_classification/scripts/train/ResNet50_vc.sh b/PaddleCV/image_classification/scripts/train/ResNet50_vc.sh
index d5d0cc5e5df1e5eb130bc73d9358c343b140abed..b12c0dbe0acb5c74a0e4509923470f50595dbecd 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet50_vc.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet50_vc.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® V100 4cards 200epochs 141h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #ResNet50_vc
diff --git a/PaddleCV/image_classification/scripts/train/ResNet50_vd.sh b/PaddleCV/image_classification/scripts/train/ResNet50_vd.sh
index 968e3dd02e96c5c5ade62c4df59cd0194787ea89..83df74731f978742a31bd1f59991fbe3811cd169 100644
--- a/PaddleCV/image_classification/scripts/train/ResNet50_vd.sh
+++ b/PaddleCV/image_classification/scripts/train/ResNet50_vd.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100 4cards 200epochs 120h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 python train.py \
diff --git a/PaddleCV/image_classification/scripts/train/SENet154_vd.sh b/PaddleCV/image_classification/scripts/train/SENet154_vd.sh
index a363a108e57b940f0c1dea2ec0a69fabf608110a..7ad2b502248cfd63cd6ad6475c6489a7ef505208 100644
--- a/PaddleCV/image_classification/scripts/train/SENet154_vd.sh
+++ b/PaddleCV/image_classification/scripts/train/SENet154_vd.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® P40 8cards 200epochs 916h
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #SE_154
diff --git a/PaddleCV/image_classification/scripts/train/SE_ResNeXt101_32x4d.sh b/PaddleCV/image_classification/scripts/train/SE_ResNeXt101_32x4d.sh
index a385814a55a527d4e1f268a2b974df9fa8cc8f2b..387011209f7c78b6ed2667dedfcc60eab7ecb1fb 100644
--- a/PaddleCV/image_classification/scripts/train/SE_ResNeXt101_32x4d.sh
+++ b/PaddleCV/image_classification/scripts/train/SE_ResNeXt101_32x4d.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® P40 8cards 120epochs 566h
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #SE_ResNeXt101_32x4d:
diff --git a/PaddleCV/image_classification/scripts/train/SE_ResNeXt50_32x4d.sh b/PaddleCV/image_classification/scripts/train/SE_ResNeXt50_32x4d.sh
index acfadb80d983f9571cf93e825958cbbd7864b711..f0d3b61b5b5891763cfe4becdba4abafee36c138 100644
--- a/PaddleCV/image_classification/scripts/train/SE_ResNeXt50_32x4d.sh
+++ b/PaddleCV/image_classification/scripts/train/SE_ResNeXt50_32x4d.sh
@@ -1,8 +1,6 @@
 #Training details
 #Machine:V100 4cards 200epochs 282h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 
diff --git a/PaddleCV/image_classification/scripts/train/ShuffleNetV2.sh b/PaddleCV/image_classification/scripts/train/ShuffleNetV2.sh
index 369e58791e410a82431dfb2413a8b911f7e1e48b..91a95ab213fdef55ba640b68cb4bcc7517bb15e6 100644
--- a/PaddleCV/image_classification/scripts/train/ShuffleNetV2.sh
+++ b/PaddleCV/image_classification/scripts/train/ShuffleNetV2.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® K40 4cards 240epochs 156h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 python train.py \
diff --git a/PaddleCV/image_classification/scripts/train/ShuffleNetV2_swish.sh b/PaddleCV/image_classification/scripts/train/ShuffleNetV2_swish.sh
index b3e29dd31bcdabda41ec8a18e8f6316813d37c1b..c2f13db1a072418e916cd1389dc4b6aaa145f62b 100644
--- a/PaddleCV/image_classification/scripts/train/ShuffleNetV2_swish.sh
+++ b/PaddleCV/image_classification/scripts/train/ShuffleNetV2_swish.sh
@@ -1,8 +1,6 @@
 ##Training details
 #GPU: NVIDIA® Tesla® K40 4cards 240epochs 156h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 python train.py \
diff --git a/PaddleCV/image_classification/scripts/train/VGG11.sh b/PaddleCV/image_classification/scripts/train/VGG11.sh
index ad8934e4b0b6687f0839bb325537ad815dc263db..f4b79a3d56bddedd4589f839865a9f0ef04efe29 100644
--- a/PaddleCV/image_classification/scripts/train/VGG11.sh
+++ b/PaddleCV/image_classification/scripts/train/VGG11.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® P40 8cards 90epochs 52h
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #VGG11:
diff --git a/PaddleCV/image_classification/scripts/train/VGG13.sh b/PaddleCV/image_classification/scripts/train/VGG13.sh
index 24960f888d46d3761dbb2712a740f1f3be71581c..17784de7e5c4665389d47e26b39a4bb2b41399c1 100644
--- a/PaddleCV/image_classification/scripts/train/VGG13.sh
+++ b/PaddleCV/image_classification/scripts/train/VGG13.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100 4cards 90epochs 58h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #VGG13:
diff --git a/PaddleCV/image_classification/scripts/train/VGG16.sh b/PaddleCV/image_classification/scripts/train/VGG16.sh
index ebf5a35627049f10c4afc1a24d7e9f2a9f6f425a..4f12a7e46f214cfbe64c3ba41d39ad9215295011 100644
--- a/PaddleCV/image_classification/scripts/train/VGG16.sh
+++ b/PaddleCV/image_classification/scripts/train/VGG16.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® P40 8cards 90epochs 72h
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #VGG16:
diff --git a/PaddleCV/image_classification/scripts/train/VGG19.sh b/PaddleCV/image_classification/scripts/train/VGG19.sh
index bca6a002f1eb3acc196f024834117155deeb6191..6bbacc1f4edf0fc29af233091e3feddcc51cf6fa 100644
--- a/PaddleCV/image_classification/scripts/train/VGG19.sh
+++ b/PaddleCV/image_classification/scripts/train/VGG19.sh
@@ -1,8 +1,6 @@
 #Training details
 #GPU: NVIDIA® Tesla® V100 4cards 150epochs 173h
 export CUDA_VISIBLE_DEVICES=0,1,2,3
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export FLAGS_fraction_of_gpu_memory_to_use=0.98
 
 #VGG19:
diff --git a/PaddleCV/image_classification/train.py b/PaddleCV/image_classification/train.py
index dfd0f591986ef53e46b438897828097b0dbfba0b..ec002ff27ca5545bf68cac5addedfec3f5694cc7 100755
--- a/PaddleCV/image_classification/train.py
+++ b/PaddleCV/image_classification/train.py
@@ -31,7 +31,6 @@ def set_paddle_flags(flags):
 # set before `import paddle`. Otherwise, it would
 # not take any effect. 
 set_paddle_flags({
-    'FLAGS_eager_delete_tensor_gb': 0,  # enable gc 
     'FLAGS_fraction_of_gpu_memory_to_use': 0.98
 })
 
diff --git a/PaddleCV/rcnn/train.py b/PaddleCV/rcnn/train.py
index 705ad33a0eeaa1e645d4e943ad2584de7c9dcd38..f2d62062d1f0a705683c2bdcafea90910810d319 100644
--- a/PaddleCV/rcnn/train.py
+++ b/PaddleCV/rcnn/train.py
@@ -26,8 +26,6 @@ def set_paddle_flags(flags):
 
 set_paddle_flags({
     'FLAGS_conv_workspace_size_limit': 500,
-    'FLAGS_eager_delete_tensor_gb': 0,  # enable gc
-    'FLAGS_memory_fraction_of_eager_deletion': 1,
     'FLAGS_fraction_of_gpu_memory_to_use': 0.98
 })
 
diff --git a/PaddleCV/ssd/train.py b/PaddleCV/ssd/train.py
index 7bbb0fdaf6c80dbc5902690fdac916c622903c0e..0e7c79580f516b177388f6963cd2eec77a58a2aa 100644
--- a/PaddleCV/ssd/train.py
+++ b/PaddleCV/ssd/train.py
@@ -20,20 +20,6 @@ import shutil
 import math
 import multiprocessing
 
-
-def set_paddle_flags(**kwargs):
-    for key, value in kwargs.items():
-        if os.environ.get(key, None) is None:
-            os.environ[key] = str(value)
-
-
-# NOTE(paddle-dev): All of these flags should be
-# set before `import paddle`. Otherwise, it would
-# not take any effect. 
-set_paddle_flags(
-    FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
-)
-
 import paddle
 import paddle.fluid as fluid
 import reader
diff --git a/PaddleCV/yolov3/train.py b/PaddleCV/yolov3/train.py
index 5f2284cf0c264e261c1cd6cab1a675c59b1981a7..9bb9c062ec12a36f8537794e0bed43cd2d395ccf 100644
--- a/PaddleCV/yolov3/train.py
+++ b/PaddleCV/yolov3/train.py
@@ -25,8 +25,6 @@ def set_paddle_flags(flags):
 
 
 set_paddle_flags({
-    'FLAGS_eager_delete_tensor_gb': 0,  # enable gc
-    'FLAGS_memory_fraction_of_eager_deletion': 1,
     'FLAGS_fraction_of_gpu_memory_to_use': 0.98
 })
 
diff --git a/PaddleNLP/Research/ACL2018-DAM/run.sh b/PaddleNLP/Research/ACL2018-DAM/run.sh
index 47395cb7dd55743ccac55bc173550f0762d478f6..4c42b0475b7517844d923119de916ac0aa1dc125 100755
--- a/PaddleNLP/Research/ACL2018-DAM/run.sh
+++ b/PaddleNLP/Research/ACL2018-DAM/run.sh
@@ -1,5 +1,4 @@
 export CUDA_VISIBLE_DEVICES=3
-export FLAGS_eager_delete_tensor_gb=0.0
 
 #train on ubuntu 
 python -u main.py \
diff --git a/PaddleNLP/Research/ACL2018-DAM/run_CPU.sh b/PaddleNLP/Research/ACL2018-DAM/run_CPU.sh
index 091eda1f2b0e41c2d767ba5fae0930baeab6ee78..220ec6a1a71cfae075224e80bd618433278d33d0 100755
--- a/PaddleNLP/Research/ACL2018-DAM/run_CPU.sh
+++ b/PaddleNLP/Research/ACL2018-DAM/run_CPU.sh
@@ -1,5 +1,4 @@
 export CPU_NUM=1
-export FLAGS_eager_delete_tensor_gb=0.0
 
 #train on ubuntu 
 python -u main.py \
diff --git a/PaddleNLP/Research/MRQA2019-BASELINE/run_finetuning.sh b/PaddleNLP/Research/MRQA2019-BASELINE/run_finetuning.sh
index bbe9bfe1fa65507dd17320c25743b944b9c33295..71e191f5d6ef3a951c02157659abf6f7d2d17792 100644
--- a/PaddleNLP/Research/MRQA2019-BASELINE/run_finetuning.sh
+++ b/PaddleNLP/Research/MRQA2019-BASELINE/run_finetuning.sh
@@ -18,7 +18,6 @@
 set -xe
 
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 
 # set CUDA_VISIBLE_DEVICES
 export CUDA_VISIBLE_DEVICES=0
diff --git a/PaddleNLP/Research/MRQA2019-BASELINE/run_predict.sh b/PaddleNLP/Research/MRQA2019-BASELINE/run_predict.sh
index df5e86b5ea7f086ffbe24f1f588882f283e4fee0..6c11820e8e771921d1d57a644af12befb62e88b4 100644
--- a/PaddleNLP/Research/MRQA2019-BASELINE/run_predict.sh
+++ b/PaddleNLP/Research/MRQA2019-BASELINE/run_predict.sh
@@ -18,7 +18,6 @@
 set -xe
 
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 
 # set CUDA_VISIBLE_DEVICES
 export CUDA_VISIBLE_DEVICES=0
diff --git a/PaddleNLP/Research/MRQA2019-D-NET/knowledge_distillation/run_distill.sh b/PaddleNLP/Research/MRQA2019-D-NET/knowledge_distillation/run_distill.sh
index 9042506c4d5c4a30f7618d92e10d4467b9ddd5b9..8b040392386bfcca7268c1c5ead2e64bdce1e9c7 100755
--- a/PaddleNLP/Research/MRQA2019-D-NET/knowledge_distillation/run_distill.sh
+++ b/PaddleNLP/Research/MRQA2019-D-NET/knowledge_distillation/run_distill.sh
@@ -1,7 +1,6 @@
 #!/bin/bash
 
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
 if  [ ! "$CUDA_VISIBLE_DEVICES" ]
diff --git a/PaddleNLP/Research/MRQA2019-D-NET/multi_task_learning/run_multi_task.sh b/PaddleNLP/Research/MRQA2019-D-NET/multi_task_learning/run_multi_task.sh
index e65d4cc2dd15c7e05b16ca9e4feabb4d7f26bfdf..fe9d9023ed294895edd435173ef2ac30fb4162bb 100755
--- a/PaddleNLP/Research/MRQA2019-D-NET/multi_task_learning/run_multi_task.sh
+++ b/PaddleNLP/Research/MRQA2019-D-NET/multi_task_learning/run_multi_task.sh
@@ -2,7 +2,6 @@
 
 # for gpu memory optimization
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
 
diff --git a/PaddleNLP/Research/MRQA2019-D-NET/server/xlnet_server/serve.sh b/PaddleNLP/Research/MRQA2019-D-NET/server/xlnet_server/serve.sh
index ff56192b5237ba1f3a08f046c3598b2fa679a782..f9beecea2c60d65e07708eceb367e995e302f8fe 100755
--- a/PaddleNLP/Research/MRQA2019-D-NET/server/xlnet_server/serve.sh
+++ b/PaddleNLP/Research/MRQA2019-D-NET/server/xlnet_server/serve.sh
@@ -1,5 +1,4 @@
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 export FLAGS_fraction_of_gpu_memory_to_use=0.1
 
 python serve.py ./infer_model_800_bs128 5001 &
diff --git a/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/.run_ce.sh b/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/.run_ce.sh
index fea71c7a316a0a85c231a7dbea5a11bf1ddcfe80..5b4881ce07b96ffe71ef00efb5cc62202b44853c 100644
--- a/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/.run_ce.sh
+++ b/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/.run_ce.sh
@@ -1,7 +1,6 @@
 #!/bin/bash
 
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1.0
 
 export CUDA_VISIBLE_DEVICES=0
 
diff --git a/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/README.md b/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/README.md
index 88e4eb64f218b8dc8c9eabca2fb2911f1c5c69d6..bd3fbcd47a4f2e023dbde49daf7d921f7f5a74e5 100644
--- a/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/README.md
+++ b/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/README.md
@@ -156,7 +156,6 @@ export CUDA_VISIBLE_DEVICES=0,1,2,3
 
 ```
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1  #开启显存优化
 
 export CUDA_VISIBLE_DEVICES=0  #GPU单卡训练
 #export CUDA_VISIBLE_DEVICES=0,1,2,3  #GPU多卡训练
@@ -222,7 +221,6 @@ task_type: train、predict、evaluate、inference, 选择4个参数选项中任
 
 ```
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1  #开启显存优化
 
 export CUDA_VISIBLE_DEVICES=0  #GPU单卡训练
 #export CUDA_VISIBLE_DEVICES=0,1,2,3  #GPU多卡训练
@@ -298,7 +296,6 @@ export CUDA_VISIBLE_DEVICES=0 #用户可自行指定空闲的卡
 
 ```
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1  #开启显存优化
 
 export CUDA_VISIBLE_DEVICES=0  #单卡预测
 #export CUDA_VISIBLE_DEVICES=  #CPU预测
@@ -346,7 +343,6 @@ task_type: train、predict、evaluate、inference, 选择4个参数选项中任
 
 ```
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1  #开启显存优化
 
 export CUDA_VISIBLE_DEVICES=0  #单卡预测
 #export CUDA_VISIBLE_DEVICES=  #CPU预测
diff --git a/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/run.sh b/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/run.sh
index 78f8da406ebe670a5b7a04077b2479c523cebc4e..52c30b7b7a1be355114a591ce73c3ec622abb9e5 100755
--- a/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/run.sh
+++ b/PaddleNLP/dialogue_model_toolkit/auto_dialogue_evaluation/run.sh
@@ -1,7 +1,6 @@
 #!/bin/bash
 
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1.0
 
 export CUDA_VISIBLE_DEVICES=0
 
diff --git a/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/.run_ce.sh b/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/.run_ce.sh
index 8ce98ff79af297f621612ad37887eec25c930cac..4feb95607607e6863ca61936b3ae683bb61f2497 100644
--- a/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/.run_ce.sh
+++ b/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/.run_ce.sh
@@ -52,12 +52,6 @@ train_mrda(){
   --enable_ce=store_true 
 }
 
-# FIXME(zjl): this model would fail when GC is enabled,
-# but it seems that this error is from the model itself.
-# See issue here: https://github.com/PaddlePaddle/Paddle/issues/18994#event-2532039900       
-# To fix ce, disable gc in this model temporarily.  
-export FLAGS_eager_delete_tensor_gb=1
-
 cudaid=${multi:=0,1,2,3}
 export CUDA_VISIBLE_DEVICES=$cudaid
 train_atis_slot | python _ce.py
diff --git a/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/README.md b/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/README.md
index 77783058744e5b34d4b212df9d4be60b2e70a9f7..68f4b8e7601e4453dce26611270baea4f917f1c5 100644
--- a/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/README.md
+++ b/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/README.md
@@ -177,7 +177,6 @@ export CUDA_VISIBLE_DEVICES=0,1,2,3
 
 ```
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1  #开启显存优化
 
 export CUDA_VISIBLE_DEVICES=0  #GPU单卡训练
 #export CUDA_VISIBLE_DEVICES=0,1,2,3  #GPU多卡训练
@@ -259,7 +258,6 @@ export CUDA_VISIBLE_DEVICES=0
 
 ```
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1  #开启显存优化
 
 export CUDA_VISIBLE_DEVICES=0  #单卡预测
 #export CUDA_VISIBLE_DEVICES=  #CPU预测
diff --git a/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/run.sh b/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/run.sh
index 1cf3aa3fcbbdf83e707a337854dbe09fa391c9f1..824674770c0bb2e00db6f15a6a23dc42cb8c544b 100644
--- a/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/run.sh
+++ b/PaddleNLP/dialogue_model_toolkit/dialogue_general_understanding/run.sh
@@ -1,7 +1,6 @@
 #!/bin/bash
 
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 
 export CUDA_VISIBLE_DEVICES=0
 if  [ ! "$CUDA_VISIBLE_DEVICES" ]
diff --git a/PaddleNLP/language_representations_kit/BERT/README.md b/PaddleNLP/language_representations_kit/BERT/README.md
index b7eb9d8c3182555dccca0f7312851a7e325e0e59..64df088258bc2ed7b7c3d7d27154613e00cdce7c 100644
--- a/PaddleNLP/language_representations_kit/BERT/README.md
+++ b/PaddleNLP/language_representations_kit/BERT/README.md
@@ -147,7 +147,6 @@ export current_endpoint=192.168.0.17:9185
 
 ```shell
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
 
 BERT_BASE_PATH="chinese_L-12_H-768_A-12"
@@ -209,7 +208,6 @@ SQuAD v1.1
 
  ```shell
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 export CUDA_VISIBLE_DEVICES=0,1,2,3
 
 BERT_BASE_PATH="uncased_L-12_H-768_A-12"
@@ -255,7 +253,6 @@ python ${SQUAD_PATH}/evaluate-v1.1.py ${SQUAD_PATH}/dev-v1.1.json ${CHECKPOINT_P
 
 ```shell
 export FLAGS_sync_nccl_allreduce=0
-export FLAGS_eager_delete_tensor_gb=1
 export CUDA_VISIBLE_DEVICES=0,1,2,3
 BERT_BASE_PATH="uncased_L-12_H-768_A-12"
 CHECKPOINT_PATH=/path/to/save/checkpoints/
diff --git a/PaddleNLP/language_representations_kit/ELMo/LAC_demo/run.sh b/PaddleNLP/language_representations_kit/ELMo/LAC_demo/run.sh
index 4d71d0c6ba426c007402e94ab4a538504c62f7d8..6e3cb62916320ee43b7f80b3ead0f070e37aa3cb 100755
--- a/PaddleNLP/language_representations_kit/ELMo/LAC_demo/run.sh
+++ b/PaddleNLP/language_representations_kit/ELMo/LAC_demo/run.sh
@@ -1,6 +1,4 @@
 export FLAGS_fraction_of_gpu_memory_to_use=0.5
-export FLAGS_eager_delete_tensor_gb=0.0 
-export FLAGS_fast_eager_deletion_mode=1
 export CUDA_VISIBLE_DEVICES=0
 
 python train.py \
diff --git a/PaddleNLP/lexical_analysis/.run_ce.sh b/PaddleNLP/lexical_analysis/.run_ce.sh
index 73f0005aff4aee71e4f2cee3e957c185952a0791..cbf7a03ae07d7fd8072997ecc016e30bde42b83c 100644
--- a/PaddleNLP/lexical_analysis/.run_ce.sh
+++ b/PaddleNLP/lexical_analysis/.run_ce.sh
@@ -1,7 +1,5 @@
 #!/bin/bash
 export FLAGS_fraction_of_gpu_memory_to_use=0.5
-export FLAGS_eager_delete_tensor_gb=0.0
-export FLAGS_fast_eager_deletion_mode=1
 
 
 train()
diff --git a/PaddleNLP/lexical_analysis/run.sh b/PaddleNLP/lexical_analysis/run.sh
index 614b8ce68166c8dda67507a98b390c21663d1be2..99bf7b637a7c9d08403587938a704372e61f5ce9 100644
--- a/PaddleNLP/lexical_analysis/run.sh
+++ b/PaddleNLP/lexical_analysis/run.sh
@@ -1,7 +1,5 @@
 #!/bin/bash
 export FLAGS_fraction_of_gpu_memory_to_use=0.02
-export FLAGS_eager_delete_tensor_gb=0.0
-export FLAGS_fast_eager_deletion_mode=1
 export CUDA_VISIBLE_DEVICES=0,1,2,3     #   which GPU to use
 
 function run_train() {
diff --git a/PaddleNLP/lexical_analysis/run_ernie.sh b/PaddleNLP/lexical_analysis/run_ernie.sh
index 61a8e8e9f6f85df2c4704ad5bf83cf2994b3569d..2203f4d66282bf55f66b95fde950ce7495ec8ac8 100644
--- a/PaddleNLP/lexical_analysis/run_ernie.sh
+++ b/PaddleNLP/lexical_analysis/run_ernie.sh
@@ -1,7 +1,5 @@
 #set -eux
 export FLAGS_fraction_of_gpu_memory_to_use=0.02
-export FLAGS_eager_delete_tensor_gb=0.0
-export FLAGS_fast_eager_deletion_mode=1
 # export FLAGS_sync_nccl_allreduce=1
 # export NCCL_DEBUG=INFO
 # export NCCL_IB_GID_INDEX=3
diff --git a/PaddleNLP/neural_machine_translation/transformer/README.md b/PaddleNLP/neural_machine_translation/transformer/README.md
index 27c59a9705ede5903358b4f7eb5bbcacd96bf9ba..e541305928e9c9bcbf01c2017000ad005abee9ed 100644
--- a/PaddleNLP/neural_machine_translation/transformer/README.md
+++ b/PaddleNLP/neural_machine_translation/transformer/README.md
@@ -68,8 +68,6 @@
 以提供的英德翻译数据为例，可以执行以下命令进行模型训练：
 
 ```sh
-# open garbage collection to save memory
-export FLAGS_eager_delete_tensor_gb=0.0
 # setting visible devices for training
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
 
@@ -86,8 +84,6 @@ python -u main.py \
 以上命令中传入了执行训练（`do_train`）、训练轮数（`epoch`）和训练数据文件路径（注意请正确设置，支持通配符）等参数，更多参数的使用以及支持的模型超参数可以参见 `transformer.yaml` 配置文件，其中默认提供了 Transformer base model 的配置，如需调整可以在配置文件中更改或通过命令行传入（命令行传入内容将覆盖配置文件中的设置）。可以通过以下命令来训练 Transformer 论文中的 big model：
 
 ```sh
-# open garbage collection to save memory
-export FLAGS_eager_delete_tensor_gb=0.0
 # setting visible devices for training
 export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
 
@@ -124,8 +120,6 @@ python -u main.py \
 以英德翻译数据为例，模型训练完成后可以执行以下命令对指定文件中的文本进行翻译：
 
 ```sh
-# open garbage collection to save memory
-export FLAGS_eager_delete_tensor_gb=0.0
 # setting visible devices for prediction
 export CUDA_VISIBLE_DEVICES=0
 
@@ -145,8 +139,6 @@ python -u main.py \
  由 `predict_file` 指定的文件中文本的翻译结果会输出到 `output_file` 指定的文件。执行预测时需要设置 `init_from_params` 来给出模型所在目录，更多参数的使用可以在 `transformer.yaml` 文件中查阅注释说明并进行更改设置。注意若在执行预测时设置了模型超参数，应与模型训练时的设置一致，如若训练时使用 big model 的参数设置，则预测时对应类似如下命令：
 
 ```sh
-# open garbage collection to save memory
-export FLAGS_eager_delete_tensor_gb=0.0
 # setting visible devices for prediction
 export CUDA_VISIBLE_DEVICES=0
 
diff --git a/PaddleNLP/neural_machine_translation/transformer/train.py b/PaddleNLP/neural_machine_translation/transformer/train.py
index 57fa3b91db165d88720b629ecd3e963266e27c60..74f825043d4e8b54a07764f816cbc278f914b580 100644
--- a/PaddleNLP/neural_machine_translation/transformer/train.py
+++ b/PaddleNLP/neural_machine_translation/transformer/train.py
@@ -32,8 +32,6 @@ import dist_utils
 import reader
 from transformer import create_net, position_encoding_init
 
-if os.environ.get('FLAGS_eager_delete_tensor_gb', None) is None:
-    os.environ['FLAGS_eager_delete_tensor_gb'] = '0'
 # num_trainers is used for multi-process gpu training
 num_trainers = int(os.environ.get('PADDLE_TRAINERS_NUM', 1))
 
diff --git a/PaddleNLP/unarchived/deep_attention_matching_net/.run_ce.sh b/PaddleNLP/unarchived/deep_attention_matching_net/.run_ce.sh
index 6c1c0a344dd84b2d252b77b8d0f5de94bb0da13c..0b927bdb9c4c43564e833b468d82c1328d42f6af 100755
--- a/PaddleNLP/unarchived/deep_attention_matching_net/.run_ce.sh
+++ b/PaddleNLP/unarchived/deep_attention_matching_net/.run_ce.sh
@@ -3,7 +3,6 @@
 
 export CE_MODE_X=1
 export CUDA_VISIBLE_DEVICES=0
-export FLAGS_eager_delete_tensor_gb=0.0
 if  [ ! -e data_small.pkl ]; then
     wget -c http://dam-data.bj.bcebos.com/data_small.pkl
 fi
diff --git a/PaddleNLP/unarchived/deep_attention_matching_net/douban/train.sh b/PaddleNLP/unarchived/deep_attention_matching_net/douban/train.sh
index 6ed91319a7880f00a1f8b202ebe057ca1145f615..eb8a7d3a8b9446cc1c66cd9183dc83f874a22903 100644
--- a/PaddleNLP/unarchived/deep_attention_matching_net/douban/train.sh
+++ b/PaddleNLP/unarchived/deep_attention_matching_net/douban/train.sh
@@ -1,5 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0
-export FLAGS_eager_delete_tensor_gb=0.0
 python -u ../train_and_evaluate.py --use_cuda \
                 --data_path ./data/data.pkl \
                 --ext_eval \
diff --git a/PaddleNLP/unarchived/deep_attention_matching_net/ubuntu/train.sh b/PaddleNLP/unarchived/deep_attention_matching_net/ubuntu/train.sh
index 66ebc2e62f66276f808ac36dfad31470950fd9b9..4d8b54b93feccdddc3ed1b9d3efecbf31db173ae 100644
--- a/PaddleNLP/unarchived/deep_attention_matching_net/ubuntu/train.sh
+++ b/PaddleNLP/unarchived/deep_attention_matching_net/ubuntu/train.sh
@@ -1,5 +1,4 @@
 export CUDA_VISIBLE_DEVICES=0
-export FLAGS_eager_delete_tensor_gb=0.0
 python -u ../train_and_evaluate.py --use_cuda \
                 --data_path ./data/data.pkl \
                 --word_emb_init ./data/word_embedding.pkl \
diff --git a/PaddleNLP/unarchived/neural_machine_translation/transformer/README_cn.md b/PaddleNLP/unarchived/neural_machine_translation/transformer/README_cn.md
index bdac7cb0b7c4f9d51bbc281b351232c6edc75a36..8db20d95bc6d6dba3cb4a55377d6aacd5b0d3c6b 100644
--- a/PaddleNLP/unarchived/neural_machine_translation/transformer/README_cn.md
+++ b/PaddleNLP/unarchived/neural_machine_translation/transformer/README_cn.md
@@ -98,8 +98,6 @@ python train.py --help
 ```sh
 # 显存使用的比例，显存不足可适当增大，最大为1
 export FLAGS_fraction_of_gpu_memory_to_use=1.0
-# 显存清理的阈值，显存不足可适当减小，最小为0，为负数时不启用
-export FLAGS_eager_delete_tensor_gb=0.8
 python -u train.py \
   --src_vocab_fpath gen_data/wmt16_ende_data_bpe/vocab_all.bpe.32000 \
   --trg_vocab_fpath gen_data/wmt16_ende_data_bpe/vocab_all.bpe.32000 \
diff --git a/PaddleSlim/.run_ce.sh b/PaddleSlim/.run_ce.sh
index 3e20348057d61996ef7044aad753a26ac9eecaf2..b45fbaf6c6046a524288a4e4d9b1b57c1f47c6f7 100755
--- a/PaddleSlim/.run_ce.sh
+++ b/PaddleSlim/.run_ce.sh
@@ -1,7 +1,6 @@
 #!/bin/bash
 # This file is only used for continuous evaluation.
 
-export FLAGS_eager_delete_tensor_gb=0.0
 export CUDA_VISIBLE_DEVICES=3
 
 if [ ! -d 'pretrain' ]; then
diff --git a/PaddleSlim/classification/distillation/run.sh b/PaddleSlim/classification/distillation/run.sh
index e9d88f501932a302390c9344b0bf0cbab183d6de..dc899cccf063039e9f7af3cda23754642e44f160 100644
--- a/PaddleSlim/classification/distillation/run.sh
+++ b/PaddleSlim/classification/distillation/run.sh
@@ -18,10 +18,6 @@ fi
 
 cd -
 
-# enable GC strategy
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
-
 # for distillation
 #-----------------
 export CUDA_VISIBLE_DEVICES=0,1,2,3
diff --git a/PaddleSlim/classification/quantization/run.sh b/PaddleSlim/classification/quantization/run.sh
index adf67f382b19ca314b4413b353c6396716ae8db6..bbe24e6267377189bec1ad511d3ecd9ba6c9180f 100644
--- a/PaddleSlim/classification/quantization/run.sh
+++ b/PaddleSlim/classification/quantization/run.sh
@@ -30,10 +30,6 @@ fi
 
 cd -
 
-# enable GC strategy
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
-
 export CUDA_VISIBLE_DEVICES=0
 
 ## for quantization for mobilenet_v1
diff --git a/PaddleSlim/light_nas/run.sh b/PaddleSlim/light_nas/run.sh
index 396247cfe26bb2139a64eb2cd10b39d639349824..5b4b425740426f10311192fd33bde0dd572b2ddc 100644
--- a/PaddleSlim/light_nas/run.sh
+++ b/PaddleSlim/light_nas/run.sh
@@ -1,5 +1,2 @@
-# enable GC strategy
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
 export CUDA_VISIBLE_DEVICES=0,1,2,3
 python search.py
diff --git a/PaddleSlim/run.sh b/PaddleSlim/run.sh
index 89bffa4d0ec26cecd67c04ccf92b01683d4630ad..fa909323dae04c844e059cf2d0f4d873950c0886 100644
--- a/PaddleSlim/run.sh
+++ b/PaddleSlim/run.sh
@@ -24,10 +24,6 @@ fi
 
 cd -
 
-# enable GC strategy
-export FLAGS_fast_eager_deletion_mode=1
-export FLAGS_eager_delete_tensor_gb=0.0
-
 # for distillation
 #-----------------
 export CUDA_VISIBLE_DEVICES=0,1,2,3
diff --git a/PaddleSlim/ssd/train.py b/PaddleSlim/ssd/train.py
index 96810ae04bb08bb63da6668434121aeaf412c116..c4494b5c3f37199f9e39b2f70b5c4f413302ed97 100644
--- a/PaddleSlim/ssd/train.py
+++ b/PaddleSlim/ssd/train.py
@@ -21,20 +21,6 @@ import math
 import multiprocessing
 from paddle.fluid.contrib.slim import Compressor
 
-
-def set_paddle_flags(**kwargs):
-    for key, value in kwargs.items():
-        if os.environ.get(key, None) is None:
-            os.environ[key] = str(value)
-
-
-# NOTE(paddle-dev): All of these flags should be
-# set before `import paddle`. Otherwise, it would
-# not take any effect. 
-set_paddle_flags(
-    FLAGS_eager_delete_tensor_gb=0,  # enable GC to save memory
-)
-
 import paddle
 import paddle.fluid as fluid
 import reader