From 1005c2107fb4de6d61e8ca0e70f9e8154ead7d14 Mon Sep 17 00:00:00 2001 From: wukesong Date: Thu, 4 Jun 2020 19:16:46 +0800 Subject: [PATCH] remove --mode --- example/alexnet_cifar10/README.md | 2 +- example/lenet_mnist/README.md | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/example/alexnet_cifar10/README.md b/example/alexnet_cifar10/README.md index e6649e40553..f3333ccabd9 100644 --- a/example/alexnet_cifar10/README.md +++ b/example/alexnet_cifar10/README.md @@ -39,7 +39,7 @@ epoch: 1 step: 1538, loss is 1.0221305 Then, evaluate AlexNet according to network model ```python # evaluate AlexNet, 1 epoch training accuracy is up to 51.1%; 10 epoch training accuracy is up to 81.2% -python eval.py --data_path cifar-10-verify-bin --mode test --ckpt_path checkpoint_alexnet-1_1562.ckpt +python eval.py --data_path cifar-10-verify-bin --ckpt_path checkpoint_alexnet-1_1562.ckpt ``` ## Note diff --git a/example/lenet_mnist/README.md b/example/lenet_mnist/README.md index 88c8769e055..750956e74b7 100644 --- a/example/lenet_mnist/README.md +++ b/example/lenet_mnist/README.md @@ -44,7 +44,7 @@ epoch: 1 step: 1741, loss is 0.05018193 Then, evaluate LeNet according to network model ```python # evaluate LeNet, after 1 epoch training, the accuracy is up to 96.5% -python eval.py --data_path MNIST_Data --mode test --ckpt_path checkpoint_lenet-1_1875.ckpt +python eval.py --data_path MNIST_Data --ckpt_path checkpoint_lenet-1_1875.ckpt ``` ## Note