update docs

.github/ISSUE_TEMPLATE/unexpected-problems---bugs.md

@@ -35,7 +35,7 @@ For example, CPU/GPU utilization, output images, tensorboard curves, if relevant
 ### 4. Your environment:
   + Python version:
   + TF version: `python -c 'import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)'`.
-  + Tensorpack version: `python -c 'import tensorpack; print(tensorpack.__version__)'`.
+  + Tensorpack version: `python -c 'import tensorpack; print(tensorpack.__version__);'`.
       You can install Tensorpack master by `pip install -U git+https://github.com/ppwwyyxx/tensorpack.git`
       and see if your issue is already solved.
   + If you're not using tensorpack under a normal command line shell (e.g.,

README.md

@@ -67,7 +67,7 @@ Dependencies:
 + TensorFlow >= 1.3. (If you only want to use `tensorpack.dataflow` alone as a data processing library, TensorFlow is not needed)
 ```
 pip install --upgrade git+https://github.com/tensorpack/tensorpack.git
-# or add `--user` to avoid system-wide installation.
+# or add `--user` to install to user's local directories
 ```
 
 ## Citing Tensorpack:

examples/FasterRCNN/README.md

@@ -12,7 +12,7 @@ with the support of:
 + [Group Normalization](https://arxiv.org/abs/1803.08494)
 
 ## Dependencies
-+ Python 3; OpenCV.
++ Python 3.3+; OpenCV.
 + TensorFlow >= 1.6 (1.4 or 1.5 can run but may crash due to a TF bug);
 + pycocotools: `pip install 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'`
 + Pre-trained [ImageNet ResNet model](http://models.tensorpack.com/FasterRCNN/)

tensorpack/__init__.py

@@ -2,7 +2,7 @@
 # File: __init__.py
 
 
-from tensorpack.libinfo import __version__, _HAS_TF
+from tensorpack.libinfo import __version__, __git_version__, _HAS_TF
 
 from tensorpack.utils import *
 from tensorpack.dataflow import *

tensorpack/dataflow/common.py

@@ -687,7 +687,7 @@ class PrintData(ProxyDataFlow):
                   ...
     """
 
-    def __init__(self, ds, num=1, label=None, name=None, max_depth=3, max_list=3):
+    def __init__(self, ds, num=1, name=None, max_depth=3, max_list=3):
         """
         Args:
             ds (DataFlow): input DataFlow.
@@ -698,11 +698,6 @@ class PrintData(ProxyDataFlow):
         """
         super(PrintData, self).__init__(ds)
         self.num = num
-
-        if label:
-            log_deprecated("PrintData(label, ...", "Use PrintData(name, ...  instead.", "2018-05-01")
-            self.name = label
-        else:
         self.name = name
         self.cnt = 0
         self.max_depth = max_depth

tensorpack/libinfo.py

@@ -57,6 +57,7 @@ except ImportError:
     _HAS_TF = False
 
 
-# This line has to be the last line of the file.
-# setup.py will use it to determine the version
+# These lines will be programatically read/write by setup.py
+# Don't touch them.
 __version__ = '0.9.0.1'
+__git_version__ = __version__

tensorpack/tfutils/common.py

@@ -147,7 +147,7 @@ def gpu_available_in_session():
     return False
 
 
-@deprecated("You should use get_tf_version_tuple instead due to the existence of TF 1.10")
+@deprecated("Use get_tf_version_tuple instead.", "2019-01-31")
 def get_tf_version_number():
     return float('.'.join(tf.VERSION.split('.')[:2]))
 

tensorpack/train/config.py

@@ -11,7 +11,7 @@ from ..callbacks import (
 from ..dataflow.base import DataFlow
 from ..graph_builder.model_desc import ModelDescBase
 from ..utils import logger
-from ..tfutils.sessinit import SessionInit, SaverRestore, JustCurrentSession
+from ..tfutils.sessinit import SessionInit, SaverRestore
 from ..tfutils.sesscreate import NewSessionCreator
 from ..input_source import InputSource
 
@@ -154,25 +154,6 @@ class TrainConfig(object):
             self.tower = [0]
         assert len(kwargs) == 0, "Unknown arguments: {}".format(kwargs.keys())
 
-    @property
-    def nr_tower(self):
-        logger.warn("TrainConfig.nr_tower was deprecated! Set the number of GPUs on the trainer instead!")
-        logger.warn("See https://github.com/tensorpack/tensorpack/issues/458 for more information.")
-        return len(self.tower)
-
-    @nr_tower.setter
-    def nr_tower(self, value):
-        logger.warn("TrainConfig.nr_tower was deprecated! Set the number of GPUs on the trainer instead!")
-        logger.warn("See https://github.com/tensorpack/tensorpack/issues/458 for more information.")
-        self.tower = list(range(value))
-
-    def _deprecated_parsing(self):
-        self.callbacks = self.callbacks or []
-        self.extra_callbacks = DEFAULT_CALLBACKS() if self.extra_callbacks is None else self.extra_callbacks
-        self.callbacks.extend(self.extra_callbacks)
-        self.monitors = DEFAULT_MONITORS() if self.monitors is None else self.monitors
-        self.session_init = self.session_init or JustCurrentSession()
-
 
 class AutoResumeTrainConfig(TrainConfig):
     """

tensorpack/train/trainers.py

@@ -11,7 +11,7 @@ from ..tfutils.sesscreate import NewSessionCreator
 
 from ..utils import logger
 from ..utils.argtools import map_arg
-from ..utils.develop import HIDE_DOC
+from ..utils.develop import HIDE_DOC, log_deprecated
 from ..tfutils import get_global_step_var
 from ..tfutils.distributed import get_distributed_session_creator
 from ..tfutils.tower import TrainTowerContext
@@ -171,7 +171,7 @@ class SyncMultiGPUTrainerReplicated(SingleCostTrainer):
 
         if use_nccl is not None:
             mode = 'nccl' if use_nccl else None
-            logger.warn("use_nccl option was deprecated! Use the `mode` option instead!")
+            log_deprecated("use_nccl option", "Use the `mode` option instead!", "2019-01-31")
         if mode is None:
             mode = 'hierarchical' if len(gpus) >= 8 else 'nccl'
         mode = mode.lower()