improve documents

docs/conf.py

@@ -14,6 +14,7 @@
 
 import sys, os, re
 import mock
+import inspect
 
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the
@@ -339,15 +340,29 @@ def process_signature(app, what, name, obj, options, signature,
         # replace Mock function names
         signature = re.sub('<Mock name=\'([^\']+)\'.*>', '\g<1>', signature)
         signature = re.sub('tensorflow', 'tf', signature)
+
+        # add scope name to layer signatures:
         if hasattr(obj, 'use_scope') and hasattr(obj, 'symbolic_function'):
             if obj.use_scope:
                 signature = signature[0] + 'name, ' + signature[1:]
     # signature: arg list
     return signature, return_annotation
 
+def autodoc_skip_member(app, what, name, obj, skip, options):
+    if name in ['get_data', 'size', 'reset_state']:
+        # skip these methods with empty docstring
+        if not obj.__doc__ and inspect.isfunction(obj):
+            # https://stackoverflow.com/questions/3589311/get-defining-class-of-unbound-method-object-in-python-3
+            cls = getattr(inspect.getmodule(obj),
+                          obj.__qualname__.split('.<locals>', 1)[0].rsplit('.', 1)[0])
+            if issubclass(cls, tensorpack.DataFlow):
+                return True
+    return None
+
 def setup(app):
     from recommonmark.transform import AutoStructify
     app.connect('autodoc-process-signature', process_signature)
+    app.connect('autodoc-skip-member', autodoc_skip_member)
     app.add_config_value(
         'recommonmark_config',
         {'url_resolver': lambda url: \

docs/requirements.txt

@@ -3,7 +3,7 @@ numpy
 tqdm
 decorator
 tensorflow
-Sphinx>=1.5.1
+Sphinx>=1.6
 recommonmark==0.4.0
 sphinx_rtd_theme
 mock

tensorpack/dataflow/prefetch.py

@@ -108,7 +108,7 @@ class PrefetchDataZMQ(ProxyDataFlow):
     communication.
 
     A local directory is needed to put the ZMQ pipes.
-    You can set this with env var $TENSORPACK_PIPEDIR if you're running on non-local FS such as NFS or GlusterFS.
+    You can set this with env var ``$TENSORPACK_PIPEDIR`` if you're running on non-local FS such as NFS or GlusterFS.
 
     Note that this dataflow is not fork-safe. You cannot nest this dataflow
     into another PrefetchDataZMQ or PrefetchData.

tensorpack/models/batch_norm.py

@@ -87,8 +87,7 @@ def BatchNorm(x, use_local_stat=None, decay=0.9, epsilon=1e-5,
     Variable Names:
 
     * ``beta``: the bias term. Will be zero-inited by default.
-    * ``gamma``: the scale term. Will be one-inited by default.
-        Input will be transformed by ``x * gamma + beta``.
+    * ``gamma``: the scale term. Will be one-inited by default. Input will be transformed by ``x * gamma + beta``.
     * ``mean/EMA``: the moving average of mean.
     * ``variance/EMA``: the moving average of variance.
 

tensorpack/models/common.py

@@ -11,7 +11,6 @@ import copy
 from ..tfutils.argscope import get_arg_scope
 from ..tfutils.model_utils import get_shape_str
 from ..utils import logger
-# from ..utils.develop import building_rtfd
 
 # make sure each layer is only logged once
 _LAYER_LOGGED = set()
@@ -147,9 +146,4 @@ def layer_register(
         _register(func.__name__, wrapped_func)
         return wrapped_func
 
-    # if building_rtfd():
-        # # preserve argspec
-        # from decorator import decorator
-        # wrapper = decorator(wrapper)
-
     return wrapper