forked from mindspore-Ecosystem/mindspore
modify alexnet script shell
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@ -110,7 +110,7 @@ Major parameters in train.py and config.py as follows:
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- running on Ascend
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- running on Ascend
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```
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```
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python train.py --data_path cifar-10-batches-bin --ckpt_path ckpt > log.txt 2>&1 &
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python train.py --data_path cifar-10-batches-bin --ckpt_path ckpt > log 2>&1 &
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# or enter script dir, and run the script
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# or enter script dir, and run the script
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sh run_standalone_train_ascend.sh cifar-10-batches-bin ckpt
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sh run_standalone_train_ascend.sh cifar-10-batches-bin ckpt
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```
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```
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@ -118,7 +118,7 @@ Major parameters in train.py and config.py as follows:
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After training, the loss value will be achieved as follows:
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After training, the loss value will be achieved as follows:
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```
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```
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# grep "loss is " train.log
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# grep "loss is " log
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epoch: 1 step: 1, loss is 2.2791853
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epoch: 1 step: 1, loss is 2.2791853
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...
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...
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epoch: 1 step: 1536, loss is 1.9366643
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epoch: 1 step: 1536, loss is 1.9366643
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@ -132,7 +132,7 @@ Major parameters in train.py and config.py as follows:
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- running on GPU
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- running on GPU
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```
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```
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python train.py --device_target "GPU" --data_path cifar-10-batches-bin --ckpt_path ckpt > log.txt 2>&1 &
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python train.py --device_target "GPU" --data_path cifar-10-batches-bin --ckpt_path ckpt > log 2>&1 &
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# or enter script dir, and run the script
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# or enter script dir, and run the script
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sh run_standalone_train_for_gpu.sh cifar-10-batches-bin ckpt
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sh run_standalone_train_for_gpu.sh cifar-10-batches-bin ckpt
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```
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```
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@ -140,7 +140,7 @@ Major parameters in train.py and config.py as follows:
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After training, the loss value will be achieved as follows:
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After training, the loss value will be achieved as follows:
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```
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```
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# grep "loss is " train.log
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# grep "loss is " log
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epoch: 1 step: 1, loss is 2.3125906
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epoch: 1 step: 1, loss is 2.3125906
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...
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...
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epoch: 30 step: 1560, loss is 0.6687547
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epoch: 30 step: 1560, loss is 0.6687547
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@ -158,30 +158,30 @@ Before running the command below, please check the checkpoint path used for eval
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- running on Ascend
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- running on Ascend
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```
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```
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python eval.py --data_path cifar-10-verify-bin --ckpt_path ckpt/checkpoint_alexnet-1_1562.ckpt > log.txt 2>&1 &
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python eval.py --data_path cifar-10-verify-bin --ckpt_path ckpt/checkpoint_alexnet-1_1562.ckpt > eval_log.txt 2>&1 &
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# or enter script dir, and run the script
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# or enter script dir, and run the script
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sh run_standalone_eval_ascend.sh cifar-10-verify-bin ckpt/checkpoint_alexnet-1_1562.ckpt
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sh run_standalone_eval_ascend.sh cifar-10-verify-bin ckpt/checkpoint_alexnet-1_1562.ckpt
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```
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```
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You can view the results through the file "log.txt". The accuracy of the test dataset will be as follows:
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You can view the results through the file "eval_log". The accuracy of the test dataset will be as follows:
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```
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```
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# grep "Accuracy: " log.txt
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# grep "Accuracy: " eval_log
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'Accuracy': 0.8832
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'Accuracy': 0.8832
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```
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```
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- running on GPU
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- running on GPU
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```
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```
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python eval.py --device_target "GPU" --data_path cifar-10-verify-bin --ckpt_path ckpt/checkpoint_alexnet-30_1562.ckpt > log.txt 2>&1 &
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python eval.py --device_target "GPU" --data_path cifar-10-verify-bin --ckpt_path ckpt/checkpoint_alexnet-30_1562.ckpt > eval_log 2>&1 &
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# or enter script dir, and run the script
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# or enter script dir, and run the script
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sh run_standalone_eval_for_gpu.sh cifar-10-verify-bin ckpt/checkpoint_alexnet-30_1562.ckpt
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sh run_standalone_eval_for_gpu.sh cifar-10-verify-bin ckpt/checkpoint_alexnet-30_1562.ckpt
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```
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```
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You can view the results through the file "log.txt". The accuracy of the test dataset will be as follows:
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You can view the results through the file "eval_log". The accuracy of the test dataset will be as follows:
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```
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```
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# grep "Accuracy: " log.txt
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# grep "Accuracy: " eval_log
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'Accuracy': 0.88512
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'Accuracy': 0.88512
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```
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```
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@ -26,4 +26,4 @@ export CKPT_PATH=$3
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export DEVICE_ID=$4
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export DEVICE_ID=$4
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python eval.py --dataset_name=$DATASET_NAME --data_path=$DATA_PATH --ckpt_path=$CKPT_PATH \
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python eval.py --dataset_name=$DATASET_NAME --data_path=$DATA_PATH --ckpt_path=$CKPT_PATH \
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--device_id=$DEVICE_ID --device_target="Ascend" > log.txt 2>&1 &
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--device_id=$DEVICE_ID --device_target="Ascend" > eval_log 2>&1 &
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@ -26,4 +26,4 @@ export CKPT_PATH=$3
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export DEVICE_ID=$4
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export DEVICE_ID=$4
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python eval.py --dataset_name=$DATASET_NAME --data_path=$DATA_PATH --ckpt_path=$CKPT_PATH \
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python eval.py --dataset_name=$DATASET_NAME --data_path=$DATA_PATH --ckpt_path=$CKPT_PATH \
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--device_id=$DEVICE_ID --device_target="GPU" > log.txt 2>&1 &
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--device_id=$DEVICE_ID --device_target="GPU" > eval_log 2>&1 &
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@ -25,4 +25,4 @@ export DATA_PATH=$2
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export DEVICE_ID=$3
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export DEVICE_ID=$3
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python train.py --dataset_name=$DATASET_NAME --data_path=$DATA_PATH \
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python train.py --dataset_name=$DATASET_NAME --data_path=$DATA_PATH \
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--device_id=$DEVICE_ID --device_target="Ascend" > log.txt 2>&1 &
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--device_id=$DEVICE_ID --device_target="Ascend" > log 2>&1 &
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@ -25,4 +25,4 @@ export DATA_PATH=$2
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export DEVICE_ID=$3
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export DEVICE_ID=$3
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python train.py --dataset_name=$DATASET_NAME --data_path=$DATA_PATH \
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python train.py --dataset_name=$DATASET_NAME --data_path=$DATA_PATH \
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--device_id=$DEVICE_ID --device_target="GPU" > log.txt 2>&1 &
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--device_id=$DEVICE_ID --device_target="GPU" > log 2>&1 &
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