You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@singa.apache.org by wa...@apache.org on 2021/03/07 02:34:29 UTC
[singa] branch dev updated: Update the allowable values for the
argument and README.md for two CNN examples
This is an automated email from the ASF dual-hosted git repository.
wangwei pushed a commit to branch dev
in repository https://gitbox.apache.org/repos/asf/singa.git
The following commit(s) were added to refs/heads/dev by this push:
new 2ed8e08 Update the allowable values for the argument and README.md for two CNN examples
new 7ab8331 Merge pull request #834 from lzjpaul/cnn_argument_readme
2ed8e08 is described below
commit 2ed8e085730442f800ddd218cbfba217147ec033
Author: zhaojing <zh...@comp.nus.edu.sg>
AuthorDate: Sat Mar 6 20:27:01 2021 +0800
Update the allowable values for the argument and README.md for two CNN examples
---
examples/cnn/train_cnn.py | 4 ++--
examples/cnn/train_mpi.py | 4 ++--
examples/largedataset_cnn/README.md | 6 +++---
3 files changed, 7 insertions(+), 7 deletions(-)
diff --git a/examples/cnn/train_cnn.py b/examples/cnn/train_cnn.py
index 6345fdb..0fbf8f3 100644
--- a/examples/cnn/train_cnn.py
+++ b/examples/cnn/train_cnn.py
@@ -272,10 +272,10 @@ if __name__ == '__main__':
description='Training using the autograd and graph.')
parser.add_argument(
'model',
- choices=['resnet', 'xceptionnet', 'cnn', 'mlp', 'alexnet'],
+ choices=['cnn', 'resnet', 'xceptionnet', 'mlp', 'alexnet'],
default='cnn')
parser.add_argument('data',
- choices=['cifar10', 'cifar100', 'mnist'],
+ choices=['mnist', 'cifar10', 'cifar100'],
default='mnist')
parser.add_argument('-p',
choices=['float32', 'float16'],
diff --git a/examples/cnn/train_mpi.py b/examples/cnn/train_mpi.py
index 7c09d12..4f71dad 100644
--- a/examples/cnn/train_mpi.py
+++ b/examples/cnn/train_mpi.py
@@ -31,9 +31,9 @@ if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Training using the autograd and graph.')
parser.add_argument('model',
- choices=['resnet', 'xceptionnet', 'cnn', 'mlp'],
+ choices=['cnn', 'resnet', 'xceptionnet', 'mlp'],
default='cnn')
- parser.add_argument('data', choices=['cifar10', 'cifar100', 'mnist'], default='mnist')
+ parser.add_argument('data', choices=['mnist', 'cifar10', 'cifar100'], default='mnist')
parser.add_argument('-p',
choices=['float32', 'float16'],
default='float32',
diff --git a/examples/largedataset_cnn/README.md b/examples/largedataset_cnn/README.md
index d872044..915d361 100644
--- a/examples/largedataset_cnn/README.md
+++ b/examples/largedataset_cnn/README.md
@@ -21,16 +21,16 @@
Examples inside this folder show how to train CNN models using SINGA for image classification.
-It read the dataset from the filesystem defined by `process_data.py`. Hence, users can modify `process_data.py`
+It reads the dataset from the filesystem defined by `process_data.py`. Hence, users can modify `process_data.py`
for their perference of dataset format.
-In the current setting, 'classes.txt' contains the names of the classes at each line. For example, if it is food dataset containing three classes, 'classes.txt' may read like this:
+In the current setting, 'classes.txt' contains the names of the classes at each line. For example, if it is a food dataset containing three classes, 'classes.txt' may read like this:
Fish_and_chips
bagel_and_croissant
bak_kut_teh
-Then, the directory '/Data/' contains all the folders for images of different classes, while each of the folder names should be the same as that appeared in 'classes.txt'. The name of an image file should not be a concern, but it should be placed inside the folder of the class it belongs to. For the same example above, the folder structure may look like this:
+Then, the directory '/Data/' contains all the folders for images of different classes, while each folder name should be the same as that appeared in 'classes.txt'. The name of an image file should not be a concern, but it should be placed inside the folder of the class it belongs to. For the same example above, the folder structure may look like this:
Data/
Fish_and_chips/