add docs about logger (fix #998)

docs/conf.py

@@ -385,6 +385,7 @@ _DEPRECATED_NAMES = set([
     'PeriodicRunHooks',
     'get_nr_gpu',
     'start_test',  # TestDataSpeed
+    'ThreadedMapData',
 
     # deprecated or renamed symbolic code
     'ImageSample',

tensorpack/dataflow/parallel.py

@@ -141,7 +141,7 @@ class MultiProcessPrefetchData(ProxyDataFlow):
               This implies that there will be duplication, reordering, etc.
               You probably only want to use it for training.
 
-              For example, if your original dataflow produced the same first datapoint,
+              For example, if your original dataflow contains no randomness and produces the same first datapoint,
               then after parallel prefetching, the datapoint will be produced ``nr_proc`` times
               at the beginning.
               Even when your original dataflow is fully shuffled, you still need to be aware of the
@@ -238,7 +238,7 @@ class PrefetchDataZMQ(_MultiProcessZMQDataFlow):
               This implies that there will be duplication, reordering, etc.
               You probably only want to use it for training.
 
-              For example, if your original dataflow produced the same first datapoint,
+              For example, if your original dataflow contains no randomness and produces the same first datapoint,
               then after parallel prefetching, the datapoint will be produced ``nr_proc`` times
               at the beginning.
               Even when your original dataflow is fully shuffled, you still need to be aware of the
@@ -386,7 +386,7 @@ class MultiThreadPrefetchData(DataFlow):
               This implies that there will be duplication, reordering, etc.
               You probably only want to use it for training.
 
-              For example, if your original dataflow produced the same first datapoint,
+              For example, if your original dataflow contains no randomness and produces the same first datapoint,
               then after parallel prefetching, the datapoint will be produced ``nr_thread`` times
               at the beginning.
               Even when your original dataflow is fully shuffled, you still need to be aware of the

tensorpack/utils/logger.py

 # -*- coding: utf-8 -*-
 # File: logger.py
 
+"""
+The logger module itself has the common logging functions of Python's
+:class:`logging.Logger`. For example:
+
+.. code-block:: python
+
+    from tensorpack.utils import logger
+    logger.set_logger_dir('train_log/test')
+    logger.info("Test")
+    logger.error("Error happened!")
+"""
+
 
 import logging
 import os