remove unnecessary code

28778d7a · mir-of · dbc7f776 · dbc7f776 · dbc7f776 · dbc7f776
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cnn_benchmark/inceptionv3.py cnn_benchmark/inceptionv3.py +0 -650

io_test.sh io_test.sh +0 -28

of_e2e.sh of_e2e.sh +0 -36

of_val.sh of_val.sh +0 -29

run.sh run.sh +0 -24

test.sh test.sh +0 -19

未找到文件。
--- a/cnn_benchmark/inceptionv3.py
+++ b/cnn_benchmark/inceptionv3.py
--- a/io_test.sh
+++ b/io_test.sh
-rm -rf core.* 
-#DATA_ROOT=/mnt/13_nfs/xuan/ImageNet/ofrecord
-DATA_ROOT=/dataset/ImageNet/ofrecord
-#DATA_ROOT=/dataset/imagenet-mxnet
-  #python3 cnn_benchmark/of_cnn_train_val.py \
-#gdb --args \
-#nvprof -f -o resnet.nvvp \
-  python3 cnn_e2e/ofrecord_util.py \
-    --train_data_dir=$DATA_ROOT/train \
-    --train_data_part_num=256 \
-    --val_data_dir=$DATA_ROOT/validation \
-    --val_data_part_num=256 \
-    --num_nodes=1 \
-    --node_ips='11.11.1.13,11.11.1.14' \
-    --gpu_num_per_node=4 \
-    --optimizer="momentum-cosine-decay" \
-    --learning_rate=0.256 \
-    --loss_print_every_n_iter=20 \
-    --batch_size_per_device=64 \
-    --val_batch_size_per_device=125 \
-    --model="resnet50" 
-    #--use_fp16 true \
-    #--weight_l2=3.0517578125e-05 \
-    #--num_examples=1024 \
-    #--optimizer="momentum-decay" \
-    #--data_dir="/mnt/13_nfs/xuan/ImageNet/ofrecord/train"
-    #--data_dir="/mnt/dataset/xuan/ImageNet/ofrecord/train"
-    #--warmup_iter_num=10000 \
--- a/of_e2e.sh
+++ b/of_e2e.sh
-rm -rf core.* 
-rm -rf ./output/snapshots/*
-#DATA_ROOT=/DATA/disk1/of_imagenet_example
-#DATA_ROOT=/DATA/disk1/ImageNet/ofrecord
-DATA_ROOT=/dataset/ImageNet/ofrecord
-#DATA_ROOT=/dataset/imagenet-mxnet
-  #python3 cnn_benchmark/of_cnn_train_val.py \
-#nvprof -f -o resnet.nvvp \
-#gdb --args \
-  python3 cnn_e2e/of_cnn_train_val.py \
-    --train_data_dir=$DATA_ROOT/train \
-    --train_data_part_num=256 \
-    --val_data_dir=$DATA_ROOT/validation \
-    --val_data_part_num=256 \
-    --num_nodes=1 \
-    --node_ips='11.11.1.12,11.11.1.14' \
-    --gpu_num_per_node=4 \
-    --optimizer="momentum-cosine-decay" \
-    --learning_rate=0.256 \
-    --loss_print_every_n_iter=20 \
-    --batch_size_per_device=56 \
-    --val_batch_size_per_device=125 \
-    --use_boxing_v2=True \
-    --use_new_dataloader=True \
-    --model="resnet50" 
-    # --train_data_dir=$DATA_ROOT/train \
-    # --train_data_part_num=256 \
-    # --val_data_dir=$DATA_ROOT/validation \
-    # --val_data_part_num=256 \
-    #--use_fp16 true \
-    #--weight_l2=3.0517578125e-05 \
-    #--num_examples=1024 \
-    #--optimizer="momentum-decay" \
-    #--data_dir="/mnt/13_nfs/xuan/ImageNet/ofrecord/train"
-    #--data_dir="/mnt/dataset/xuan/ImageNet/ofrecord/train"
-    #--warmup_iter_num=10000 \
--- a/of_val.sh
+++ b/of_val.sh
-rm -rf core.* 
-#DATA_ROOT=/mnt/13_nfs/xuan/ImageNet/ofrecord
-DATA_ROOT=/dataset/ImageNet/ofrecord
-#DATA_ROOT=/dataset/imagenet-mxnet
-  #python3 cnn_benchmark/of_cnn_train_val.py \
-#gdb --args \
-#nvprof -f -o resnet.nvvp \
-  python3 cnn_e2e/of_cnn_val.py \
-    --model_load_dir=output/snapshots_0323 \
-    --train_data_dir=$DATA_ROOT/train \
-    --train_data_part_num=256 \
-    --val_data_dir=$DATA_ROOT/validation \
-    --val_data_part_num=256 \
-    --num_nodes=1 \
-    --node_ips='11.11.1.13,11.11.1.14' \
-    --gpu_num_per_node=4 \
-    --optimizer="momentum-cosine-decay" \
-    --learning_rate=0.256 \
-    --loss_print_every_n_iter=20 \
-    --batch_size_per_device=32 \
-    --val_batch_size_per_device=125 \
-    --model="resnet50" 
-    #--use_fp16 true \
-    #--weight_l2=3.0517578125e-05 \
-    #--num_examples=1024 \
-    #--optimizer="momentum-decay" \
-    #--data_dir="/mnt/13_nfs/xuan/ImageNet/ofrecord/train"
-    #--data_dir="/mnt/dataset/xuan/ImageNet/ofrecord/train"
-    #--warmup_iter_num=10000 \
--- a/run.sh
+++ b/run.sh
-rm -rf core.* 
-#gdb --args \
-DATA_ROOT=/mnt/13_nfs/xuan/ImageNet/mxnet
-#DATA_ROOT=/dataset/imagenet-mxnet
-  #python3 cnn_benchmark/of_cnn_train_val.py \
-#nvprof -f -o resnet.nvvp \
-  python3 cnn_benchmark/of_cnn_train_val_consistent.py \
-    --data_train=$DATA_ROOT/train.rec \
-    --data_train_idx=$DATA_ROOT/train.idx \
-    --data_val=$DATA_ROOT/val.rec \
-    --data_val_idx=$DATA_ROOT/val.idx \
-    --gpu_num_per_node=4 \
-    --optimizer="momentum-cosine-decay" \
-    --learning_rate=0.256 \
-    --loss_print_every_n_iter=20 \
-    --batch_size_per_device=64 \
-    --val_batch_size_per_device=125 \
-    --model="resnet50" 
-    #--weight_l2=3.0517578125e-05 \
-    #--num_examples=1024 \
-    #--optimizer="momentum-decay" \
-    #--data_dir="/mnt/13_nfs/xuan/ImageNet/ofrecord/train"
-    #--data_dir="/mnt/dataset/xuan/ImageNet/ofrecord/train"
-    #--warmup_iter_num=10000 \
--- a/test.sh
+++ b/test.sh
-rm -rf core.*
-#gdb --args \
-#DATA_ROOT=/dataset/imagenet_10pics
-DATA_ROOT=/dataset/imagenet_1pic
-python cnn_e2e/test_data_loader.py \
-  --data_train=$DATA_ROOT/mxnet/train.rec \
-  --data_train_idx=$DATA_ROOT/mxnet/train.idx \
-  --data_val=$DATA_ROOT/mxnet/train.rec \
-  --data_val_idx=$DATA_ROOT/mxnet/train.idx \
-  --train_data_dir=$DATA_ROOT/ofrecord \
-  --train_data_part_num=1 \
-  --val_data_dir=$DATA_ROOT/ofrecord \
-  --val_data_part_num=1 \
-  --val_batch_size_per_device=1 \
-  --batch_size_per_device=1 \
-  --num_examples=1 \
-  --num_val_examples=1 \
-  --gpu_num_per_node=1 \
-  --num_epochs=1