expose layer_register() in common.py

tensorpack/RL/simulator.py

@@ -13,7 +13,7 @@ from collections import defaultdict
 import six
 from six.moves import queue
 
-from ..models._common import disable_layer_logging
+from ..models.common import disable_layer_logging
 from ..callbacks import Callback
 from ..tfutils.varmanip import SessionUpdate
 from ..predict import OfflinePredictor

tensorpack/models/batch_norm.py

@@ -10,7 +10,7 @@ from tensorflow.python.training import moving_averages
 from ..tfutils.common import get_tf_version
 from ..tfutils.tower import get_current_tower_context
 from ..utils import logger, building_rtfd
-from ._common import layer_register
+from .common import layer_register
 
 __all__ = ['BatchNorm', 'BatchNormV1', 'BatchNormV2']
 

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

 # -*- coding: UTF-8 -*-
-# File: _common.py
+# File: common.py
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 import tensorflow as tf
@@ -11,15 +11,19 @@ from ..tfutils.argscope import get_arg_scope
 from ..tfutils.modelutils import get_shape_str
 from ..tfutils.summary import add_activation_summary
 from ..utils import logger, building_rtfd
-from ..utils.argtools import shape2d
 
 # make sure each layer is only logged once
 _layer_logged = set()
 
+__all__ = ['layer_register', 'disable_layer_logging']
+
 
 def disable_layer_logging():
+    """
+    Disable the shape logging for all layers from this moment on. Can be
+    useful when creating multiple towers.
+    """
     class ContainEverything:
-
         def __contains__(self, x):
             return True
     # can use nonlocal in python3, but how
@@ -32,12 +36,15 @@ def layer_register(
         use_scope=True):
     """
     Register a layer.
-    :param summary_activation: Define the default behavior of whether to
+
+    Args:
+        summary_activation (bool): Define the default behavior of whether to
             summary the output(activation) of this layer.
             Can be overriden when creating the layer.
-    :param log_shape: log input/output shape of this layer
-    :param use_scope: whether to call this layer with an extra first argument as scope
-        if set to False, will try to figure out whether the first argument is scope name
+        log_shape (bool): log input/output shape of this layer
+        use_scope (bool): whether to call this layer with an extra first argument as scope.
+            If set to False, will try to figure out whether the first argument
+            is scope name or not.
     """
 
     def wrapper(func):
@@ -104,8 +111,3 @@ def layer_register(
         wrapper = decorator(wrapper)
 
     return wrapper
-
-
-def shape4d(a):
-    # for use with tensorflow NHWC ops
-    return [1] + shape2d(a) + [1]

tensorpack/models/conv2d.py

@@ -4,7 +4,8 @@
 # Author: Yuxin Wu <ppwwyyxx@gmail.com>
 
 import tensorflow as tf
-from ._common import layer_register, shape2d, shape4d
+from .common import layer_register
+from ..utils.argtools import shape2d, shape4d
 
 __all__ = ['Conv2D', 'Deconv2D']
 

tensorpack/models/fc.py

@@ -5,7 +5,7 @@
 
 import tensorflow as tf
 
-from ._common import layer_register
+from .common import layer_register
 from ..tfutils import symbolic_functions as symbf
 
 __all__ = ['FullyConnected']

tensorpack/models/image_sample.py

@@ -5,7 +5,7 @@
 
 import tensorflow as tf
 
-from ._common import layer_register
+from .common import layer_register
 from ._test import TestModel
 
 __all__ = ['ImageSample']

tensorpack/models/nonlin.py

@@ -5,7 +5,7 @@
 
 import tensorflow as tf
 
-from ._common import layer_register
+from .common import layer_register
 from .batch_norm import BatchNorm
 
 __all__ = ['Maxout', 'PReLU', 'LeakyReLU', 'BNReLU']

tensorpack/models/pool.py

@@ -5,8 +5,8 @@
 import tensorflow as tf
 import numpy as np
 
-from ._common import layer_register, shape4d
-from ..utils.argtools import shape2d
+from .common import layer_register
+from ..utils.argtools import shape2d, shape4d
 from ..tfutils import symbolic_functions as symbf
 from ._test import TestModel
 

tensorpack/models/regularize.py

@@ -8,7 +8,7 @@ import re
 from ..utils import logger
 from ..utils.argtools import memoized
 from ..tfutils.tower import get_current_tower_context
-from ._common import layer_register
+from .common import layer_register
 
 __all__ = ['regularize_cost', 'l2_regularizer', 'l1_regularizer', 'Dropout']
 

tensorpack/models/shapes.py

@@ -4,7 +4,7 @@
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>
 
 import tensorflow as tf
-from ._common import layer_register
+from .common import layer_register
 
 __all__ = ['ConcatWith']
 

tensorpack/models/softmax.py

@@ -4,7 +4,7 @@
 # Author: Yuxin Wu <ppwwyyxxc@gmail.com>
 
 import tensorflow as tf
-from ._common import layer_register
+from .common import layer_register
 
 __all__ = ['SoftMax']
 

tensorpack/predict/concurrency.py

@@ -45,7 +45,7 @@ class MultiProcessPredictWorker(multiprocessing.Process):
             have workers that run on multiGPUs
         """
         if self.idx != 0:
-            from tensorpack.models._common import disable_layer_logging
+            from tensorpack.models.common import disable_layer_logging
             disable_layer_logging()
         self.predictor = OfflinePredictor(self.config)
         if self.idx == 0:

tensorpack/utils/argtools.py

@@ -12,7 +12,8 @@ if six.PY2:
 else:
     import functools
 
-__all__ = ['map_arg', 'memoized', 'shape2d', 'memoized_ignoreargs', 'log_once']
+__all__ = ['map_arg', 'memoized', 'shape2d', 'shape4d',
+           'memoized_ignoreargs', 'log_once']
 
 
 def map_arg(**maps):
@@ -85,6 +86,19 @@ def shape2d(a):
     raise RuntimeError("Illegal shape: {}".format(a))
 
 
+def shape4d(a):
+    """
+    Ensuer a 4D shape, to use with NHWC functions.
+
+    Args:
+        a: a int or tuple/list of length 2
+
+    Returns:
+        list: of length 4. if ``a`` is a int, return ``[1, a, a, 1]``.
+    """
+    return [1] + shape2d(a) + [1]
+
+
 @memoized
 def log_once(message, func):
     """