move to a new folder

example_cifar10.py

@@ -3,26 +3,19 @@
 # File: example_cifar10.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
-# use user-space protobuf
-import sys
-import os
-sys.path.insert(0, os.path.expanduser('~/.local/lib/python2.7/site-packages'))
-
 import tensorflow as tf
-from tensorflow.python.ops import control_flow_ops
-
+import argparse
 import numpy as np
 import os
 
-from models import *
-from utils import *
-from utils.symbolic_functions import *
-from utils.summary import *
-from utils.callback import *
-from utils.validation_callback import *
-from utils.concurrency import *
-from dataflow.dataset import Cifar10
-from dataflow import *
+from tensorpack.models import *
+from tensorpack.utils import *
+from tensorpack.utils.symbolic_functions import *
+from tensorpack.utils.summary import *
+from tensorpack.utils.callback import *
+from tensorpack.utils.validation_callback import *
+from tensorpack.dataflow.dataset import Cifar10
+from tensorpack.dataflow import *
 
 BATCH_SIZE = 128
 MIN_AFTER_DEQUEUE = 500
@@ -136,5 +129,14 @@ def get_config():
     )
 
 if __name__ == '__main__':
-    from train import main
-    main(get_config)
+    from tensorpack import train
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.') # nargs='*' in multi mode
+    args = parser.parse_args()
+    if args.gpu:
+        os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
+
+    with tf.Graph().as_default():
+        train.prepare()
+        config = get_config()
+        train.start_train(config)

example_mnist.py

@@ -8,16 +8,16 @@ from tensorflow.python.ops import control_flow_ops
 
 import numpy as np
 import os, sys
+import argparse
 
-from models import *
-from utils import *
-from utils.symbolic_functions import *
-from utils.summary import *
-from utils.callback import *
-from utils.validation_callback import *
-from utils.concurrency import *
-from dataflow.dataset import Mnist
-from dataflow import *
+from tensorpack.models import *
+from tensorpack.utils import *
+from tensorpack.utils.symbolic_functions import *
+from tensorpack.utils.summary import *
+from tensorpack.utils.callback import *
+from tensorpack.utils.validation_callback import *
+from tensorpack.dataflow.dataset import Mnist
+from tensorpack.dataflow import *
 
 BATCH_SIZE = 128
 MIN_AFTER_DEQUEUE = 500
@@ -142,5 +142,14 @@ def get_config():
     )
 
 if __name__ == '__main__':
-    from train import main
-    main(get_config)
+    from tensorpack import train
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.') # nargs='*' in multi mode
+    args = parser.parse_args()
+    if args.gpu:
+        os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
+
+    with tf.Graph().as_default():
+        train.prepare()
+        config = get_config()
+        train.start_train(config)

dataflow/dataset/cifar10.py → tensorpack/dataflow/dataset/cifar10.py

@@ -14,8 +14,8 @@ import numpy
 from six.moves import urllib
 import tarfile
 
-from utils import logger
-from dataflow.base import DataFlow
+from ...utils import logger
+from ..base import DataFlow
 
 __all__ = ['Cifar10']
 

dataflow/dataset/mnist.py → tensorpack/dataflow/dataset/mnist.py

@@ -8,9 +8,9 @@ import gzip
 
 import numpy
 from six.moves import urllib
-from utils import logger
 
-from dataflow.base import DataFlow
+from ...utils import logger
+from ..base import DataFlow
 
 __all__ = ['Mnist']
 

models/_common.py → tensorpack/models/_common.py

@@ -4,9 +4,9 @@
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 import tensorflow as tf
-from utils.modelutils import *
-from utils.summary import *
-from utils import logger
+from ..utils.modelutils import *
+from ..utils.summary import *
+from ..utils import logger
 
 # make sure each layer is only logged once
 _layer_logged = set()

models/fc.py → tensorpack/models/fc.py

@@ -3,12 +3,12 @@
 # File: fc.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
-
-from ._common import layer_register
 import tensorflow as tf
-from utils.symbolic_functions import *
 import math
 
+from ._common import layer_register
+from ..utils.symbolic_functions import *
+
 __all__ = ['FullyConnected']
 
 @layer_register(summary_activation=True)

models/regularize.py → tensorpack/models/regularize.py

@@ -5,7 +5,8 @@
 
 import tensorflow as tf
 import re
-from utils import logger
+
+from ..utils import logger
 
 __all__ = ['regularize_cost']
 

train.py → tensorpack/train.py

@@ -111,14 +111,3 @@ def start_train(config):
                 # note that summary_op will take a data from the queue.
                 callbacks.trigger_epoch()
 
-def main(get_config_func):
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.') # nargs='*' in multi mode
-    args = parser.parse_args()
-    if args.gpu:
-        os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
-
-    with tf.Graph().as_default():
-        prepare()
-        config = get_config_func()
-        start_train(config)