hide some internal functions from import

tensorpack/callbacks/inference.py

@@ -8,7 +8,7 @@ import six
 from six.moves import zip
 
 from ..utils.stats import RatioCounter, BinaryStatistics
-from ..tfutils import get_op_tensor_name
+from ..tfutils.common import get_op_tensor_name
 
 __all__ = ['ScalarStats', 'Inferencer',
            'ClassificationError', 'BinaryClassificationStats']

tensorpack/callbacks/param.py

@@ -11,7 +11,7 @@ import os
 
 from .base import Callback
 from ..utils import logger
-from ..tfutils import get_op_tensor_name
+from ..tfutils.common import get_op_tensor_name
 
 __all__ = ['HyperParam', 'GraphVarParam', 'ObjAttrParam',
            'HyperParamSetter', 'HumanHyperParamSetter',

tensorpack/callbacks/stats.py

@@ -7,7 +7,7 @@ import numpy as np
 
 from .base import Callback
 from ..utils import logger
-from ..tfutils import get_op_tensor_name
+from ..tfutils.common import get_op_tensor_name
 
 __all__ = ['SendStat', 'DumpParamAsImage', 'InjectShell']
 

tensorpack/graph_builder/input_source.py

@@ -15,7 +15,7 @@ from six.moves import range, zip
 from .input_source_base import InputSource
 from ..dataflow import DataFlow, RepeatedData
 from ..tfutils.summary import add_moving_summary
-from ..tfutils import get_op_tensor_name
+from ..tfutils.common import get_op_tensor_name
 from ..tfutils.tower import get_current_tower_context
 from ..utils import logger
 from ..utils.concurrency import ShareSessionThread

tensorpack/predict/concurrency.py

@@ -10,7 +10,7 @@ import tensorflow as tf
 
 from ..utils import logger
 from ..utils.concurrency import DIE, StoppableThread, ShareSessionThread
-from ..tfutils.model_utils import describe_model
+from ..tfutils.model_utils import describe_trainable_vars
 from .base import OnlinePredictor, OfflinePredictor, AsyncPredictorBase
 
 __all__ = ['MultiProcessPredictWorker', 'MultiProcessQueuePredictWorker',
@@ -41,7 +41,7 @@ class MultiProcessPredictWorker(multiprocessing.Process):
         self.predictor = OfflinePredictor(self.config)
         if self.idx == 0:
             with self.predictor.graph.as_default():
-                describe_model()
+                describe_trainable_vars()
 
 
 class MultiProcessQueuePredictWorker(MultiProcessPredictWorker):

tensorpack/tfutils/common.py

@@ -10,10 +10,10 @@ from ..utils.argtools import graph_memoized
 __all__ = ['get_default_sess_config',
            'get_global_step_value',
            'get_global_step_var',
-           'get_op_tensor_name',
-           'get_tensors_by_names',
-           'get_op_or_tensor_by_name',
-           'get_tf_version_number',
+           # 'get_op_tensor_name',
+           # 'get_tensors_by_names',
+           # 'get_op_or_tensor_by_name',
+           # 'get_tf_version_number',
            ]
 
 

tensorpack/tfutils/model_utils.py

@@ -8,10 +8,10 @@ from tabulate import tabulate
 
 from ..utils import logger
 
-__all__ = ['describe_model', 'get_shape_str']
+__all__ = []
 
 
-def describe_model():
+def describe_trainable_vars():
     """
     Print a description of the current model parameters.
     Skip variables starting with "tower".

tensorpack/tfutils/scope_utils.py

@@ -12,7 +12,7 @@ if six.PY2:
 else:
     import functools
 
-__all__ = ['get_name_scope_name', 'auto_reuse_variable_scope']
+__all__ = ['auto_reuse_variable_scope']
 
 
 @deprecated("Use tf.get_default_graph().get_name_scope() (available since 1.2.1).")

tensorpack/tfutils/summary.py

@@ -16,8 +16,8 @@ from ..utils.naming import MOVING_SUMMARY_OPS_KEY
 from .tower import get_current_tower_context
 from .symbolic_functions import rms
 
-__all__ = ['create_scalar_summary', 'add_param_summary', 'add_activation_summary',
-           'add_moving_summary']
+__all__ = ['create_scalar_summary', 'add_param_summary',
+           'add_activation_summary', 'add_moving_summary']
 
 
 def create_scalar_summary(name, v):

tensorpack/tfutils/symbolic_functions.py

@@ -6,6 +6,8 @@ import tensorflow as tf
 from contextlib import contextmanager
 import numpy as np
 
+__all__ = []
+
 
 # this function exists for backwards-compatibilty
 def prediction_incorrect(logits, label, topk=1, name='incorrect_vector'):

tensorpack/tfutils/varmanip.py

@@ -13,7 +13,7 @@ from ..utils import logger
 from .common import get_op_tensor_name
 
 __all__ = ['SessionUpdate', 'dump_session_params', 'dump_chkpt_vars',
-           'get_savename_from_varname', 'is_training_name',
+           # 'get_savename_from_varname', 'is_training_name',
            'get_checkpoint_path']
 
 

tensorpack/train/base.py

@@ -16,7 +16,7 @@ from ..utils import logger
 from ..callbacks import Callback, Callbacks, MaintainStepCounter
 from ..callbacks.monitor import Monitors, TrainingMonitor
 from ..tfutils import get_global_step_value
-from ..tfutils.model_utils import describe_model
+from ..tfutils.model_utils import describe_trainable_vars
 from ..tfutils.sesscreate import ReuseSessionCreator
 from ..tfutils.sessinit import JustCurrentSession
 
@@ -127,7 +127,7 @@ class Trainer(object):
         self.monitors = Monitors(self.monitors)
         self.register_callback(self.monitors)
 
-        describe_model()
+        describe_trainable_vars()
 
         # some final operations that might modify the graph
         logger.info("Setup callbacks graph ...")