Add under_nam_socpe decorator

examples/ResNet/imagenet_resnet_utils.py

@@ -44,7 +44,8 @@ class GoogleNetResize(imgaug.ImageAugmentor):
                 out = img[y1:y1 + hh, x1:x1 + ww]
                 out = cv2.resize(out, (224, 224), interpolation=cv2.INTER_CUBIC)
                 return out
-        out = cv2.resize(img, (224, 224), interpolation=cv2.INTER_CUBIC)
+        out = imgaug.ResizeShortestEdge(224, interp=cv2.INTER_CUBIC).augment(img)
+        out = imgaug.CenterCrop(224).augment(out)
         return out
 
 
@@ -73,7 +74,7 @@ def fbresnet_augmentor(isTrain):
         ]
     else:
         augmentors = [
-            imgaug.ResizeShortestEdge(256),
+            imgaug.ResizeShortestEdge(256, cv2.INTER_CUBIC),
             imgaug.CenterCrop((224, 224)),
         ]
     return augmentors

tensorpack/models/common.py

@@ -87,8 +87,6 @@ def layer_register(
         log_shape=False,
         use_scope=True):
     """
-    Register a layer.
-
     Args:
         log_shape (bool): log input/output shape of this layer
         use_scope (bool or None):
@@ -97,6 +95,17 @@ def layer_register(
             the scope name argument.
             It will try to figure out by checking if the first argument
             is string or not.
+
+    Returns:
+        A decorator used to register a layer.
+
+    Examples:
+
+    .. code-block:: python
+
+        @layer_register(use_scope=True)
+        def add10(x):
+            return x + tf.get_variable('W', shape=[10])
     """
 
     def wrapper(func):

tensorpack/tfutils/scope_utils.py

@@ -14,8 +14,22 @@ __all__ = ['auto_reuse_variable_scope', 'cached_name_scope']
 
 def auto_reuse_variable_scope(func):
     """
-    A decorator which automatically reuse the current variable scope if the
+    A decorator which automatically reuses the current variable scope if the
     function has been called with the same variable scope before.
+
+    Examples:
+
+    .. code-block:: python
+
+        @auto_reuse_variable_scope
+        def myfunc(x):
+            return tf.layers.conv2d(x, 128, 3)
+
+        myfunc(x1)  # will inherit parent scope reuse
+        myfunc(x2)  # will reuse
+        with tf.variable_scope('newscope'):
+            myfunc(x3)  # will inherit parent scope reuse
+            myfunc(x4)  # will reuse
     """
     used_scope = set()
 
@@ -34,6 +48,35 @@ def auto_reuse_variable_scope(func):
     return wrapper
 
 
+def under_name_scope():
+    """
+    Returns:
+        A decorator which makes the function happen under a name scope,
+        which is named by the function itself.
+
+    Examples:
+
+    .. code-block:: python
+
+        @under_name_scope()
+        def rms(x):
+            return tf.sqrt(  # will be under name scope 'rms'
+                tf.reduce_mean(tf.square(x)))
+
+    Todo:
+        Add a reuse option.
+    """
+
+    def _impl(func):
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            name = func.__name__
+            with tf.name_scope(name):
+                return func(*args, **kwargs)
+        return wrapper
+    return _impl
+
+
 @graph_memoized
 def _get_cached_ns(name):
     with tf.name_scope(None):