rename EmptyObject

tensorpack/models/common.py

@@ -16,10 +16,11 @@ from ..utils.develop import building_rtfd
 _LAYER_LOGGED = set()
 _LAYER_REGISTERED = {}
 
-__all__ = ['layer_register', 'disable_layer_logging', 'get_registered_layer', 'EmptyObject']
+__all__ = ['layer_register', 'disable_layer_logging', 'get_registered_layer', 'VariableHolder']
 
 
-class EmptyObject(object):
+class VariableHolder(object):
+    """ A proxy to access variables defined in a layer. """
     pass
 
 

tensorpack/models/conv2d.py

@@ -4,7 +4,7 @@
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 import tensorflow as tf
-from .common import layer_register, EmptyObject
+from .common import layer_register, VariableHolder
 from ..utils.argtools import shape2d, shape4d
 
 __all__ = ['Conv2D', 'Deconv2D']
@@ -72,7 +72,7 @@ def Conv2D(x, out_channel, kernel_shape,
         conv = tf.concat(outputs, channel_axis)
 
     ret = nl(tf.nn.bias_add(conv, b, data_format=data_format) if use_bias else conv, name='output')
-    ret.variables = EmptyObject()
+    ret.variables = VariableHolder()
     ret.variables.W = W
     if use_bias:
         ret.variables.b = b
@@ -166,7 +166,7 @@ def Deconv2D(x, out_shape, kernel_shape,
     conv.set_shape(tf.TensorShape([None] + shp3_static))
     ret = nl(tf.nn.bias_add(conv, b, data_format=data_format) if use_bias else conv, name='output')
 
-    ret.variables = EmptyObject()
+    ret.variables = VariableHolder()
     ret.variables.W = W
     if use_bias:
         ret.variables.b = b

tensorpack/models/fc.py

@@ -5,7 +5,7 @@
 
 import tensorflow as tf
 
-from .common import layer_register, EmptyObject
+from .common import layer_register, VariableHolder
 from ..tfutils import symbolic_functions as symbf
 
 __all__ = ['FullyConnected']
@@ -48,7 +48,7 @@ def FullyConnected(x, out_dim,
     prod = tf.nn.xw_plus_b(x, W, b) if use_bias else tf.matmul(x, W)
 
     ret = nl(prod, name='output')
-    ret.variables = EmptyObject()
+    ret.variables = VariableHolder()
     ret.variables.W = W
     if use_bias:
         ret.variables.b = b

tensorpack/models/nonlin.py

@@ -5,7 +5,7 @@
 
 import tensorflow as tf
 
-from .common import layer_register, EmptyObject
+from .common import layer_register, VariableHolder
 from .batch_norm import BatchNorm
 
 __all__ = ['Maxout', 'PReLU', 'LeakyReLU', 'BNReLU']
@@ -56,7 +56,7 @@ def PReLU(x, init=0.001, name='output'):
     x = ((1 + alpha) * x + (1 - alpha) * tf.abs(x))
     ret = tf.multiply(x, 0.5, name=name)
 
-    ret.variables = EmptyObject()
+    ret.variables = VariableHolder()
     ret.variables.alpha = alpha
     return ret