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authorEvan Shelhamer <shelhamer@imaginarynumber.net>2014-09-03 15:18:21 -0700
committerEvan Shelhamer <shelhamer@imaginarynumber.net>2014-09-03 15:19:05 -0700
commit0766cd97f8a4d97ad1f1bdd62a8b310121cb0859 (patch)
tree859c8ca19eb0ff62bdc6bb148d94e12b3e8706d3 /examples
parent945a8497be046b3f5fcba36444bf1bf46af83c42 (diff)
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[example] drop stale mentions of glog env var
Diffstat (limited to 'examples')
-rw-r--r--examples/cifar10/readme.md2
-rw-r--r--examples/mnist/readme.md2
2 files changed, 2 insertions, 2 deletions
diff --git a/examples/cifar10/readme.md b/examples/cifar10/readme.md
index d0b0b766..bf64ce89 100644
--- a/examples/cifar10/readme.md
+++ b/examples/cifar10/readme.md
@@ -43,7 +43,7 @@ Training the model is simple after you have written the network definition proto
cd $CAFFE_ROOT/examples/cifar10
./train_quick.sh
-`train_quick.sh` is a simple script, so have a look inside. `GLOG_logtostderr=1` is the google logging flag that prints all the logging messages directly to stderr. The main tool for training is `caffe.bin` with the `train` action, and the solver protobuf text file as its argument.
+`train_quick.sh` is a simple script, so have a look inside. The main tool for training is `caffe` with the `train` action, and the solver protobuf text file as its argument.
When you run the code, you will see a lot of messages flying by like this:
diff --git a/examples/mnist/readme.md b/examples/mnist/readme.md
index ae294cff..d4fb62d9 100644
--- a/examples/mnist/readme.md
+++ b/examples/mnist/readme.md
@@ -211,7 +211,7 @@ Training the model is simple after you have written the network definition proto
cd $CAFFE_ROOT/examples/mnist
./train_lenet.sh
-`train_lenet.sh` is a simple script, but here are a few explanations: `GLOG_logtostderr=1` is the google logging flag that prints all the logging messages directly to stderr. The main tool for training is `caffe.bin` with action `train`, with the solver protobuf text file as its argument.
+`train_lenet.sh` is a simple script, but here is a quick explanation: the main tool for training is `caffe` with action `train` and the solver protobuf text file as its argument.
When you run the code, you will see a lot of messages flying by like this: