fix LinearWrap imports. use varreplace in DoReFa.

.travis.yml

 language: "python"
 python:
    - "2.7"
+   - "3.5"
 sudo: false
 cache: pip
 
-before_script:
+install:
   - pip install flake8
+
+before_script:
   - flake8 --version
+
 script:
   - flake8 .
   - cd examples && flake8 .

examples/DoReFa-Net/alexnet-dorefa.py

@@ -15,6 +15,7 @@ import sys
 from tensorpack import *
 from tensorpack.tfutils.symbolic_functions import *
 from tensorpack.tfutils.summary import *
+from tensorpack.tfutils.varreplace import replace_get_variable
 from dorefa import get_dorefa
 
 """
@@ -82,9 +83,10 @@ class Model(ModelDesc):
         image = image / 255.0
 
         fw, fa, fg = get_dorefa(BITW, BITA, BITG)
-        # monkey-patch tf.get_variable to apply fw
+
         old_get_variable = tf.get_variable
 
+        # monkey-patch tf.get_variable to apply fw
         def new_get_variable(name, shape=None, **kwargs):
             v = old_get_variable(name, shape, **kwargs)
             # don't binarize first and last layer
@@ -93,7 +95,6 @@ class Model(ModelDesc):
             else:
                 logger.info("Binarizing weight {}".format(v.op.name))
                 return fw(v)
-        tf.get_variable = new_get_variable
 
         def nonlin(x):
             if BITA == 32:
@@ -103,7 +104,8 @@ class Model(ModelDesc):
         def activate(x):
             return fa(nonlin(x))
 
-        with argscope(BatchNorm, decay=0.9, epsilon=1e-4), \
+        with replace_get_variable(new_get_variable), \
+                argscope(BatchNorm, decay=0.9, epsilon=1e-4), \
                 argscope([Conv2D, FullyConnected], use_bias=False, nl=tf.identity):
             logits = (LinearWrap(image)
                       .Conv2D('conv0', 96, 12, stride=4, padding='VALID')
@@ -141,7 +143,6 @@ class Model(ModelDesc):
                       .BatchNorm('bnfc1')
                       .apply(nonlin)
                       .FullyConnected('fct', 1000, use_bias=True)())
-        tf.get_variable = old_get_variable
 
         prob = tf.nn.softmax(logits, name='output')
 

examples/DoReFa-Net/svhn-digit-dorefa.py

@@ -11,6 +11,7 @@ import os
 from tensorpack import *
 from tensorpack.tfutils.symbolic_functions import *
 from tensorpack.tfutils.summary import *
+from tensorpack.tfutils.varreplace import replace_get_variable
 from dorefa import get_dorefa
 
 """
@@ -52,9 +53,10 @@ class Model(ModelDesc):
         is_training = get_current_tower_context().is_training
 
         fw, fa, fg = get_dorefa(BITW, BITA, BITG)
-        # monkey-patch tf.get_variable to apply fw
+
         old_get_variable = tf.get_variable
 
+        # monkey-patch tf.get_variable to apply fw
         def new_get_variable(name, shape=None, **kwargs):
             v = old_get_variable(name, shape, **kwargs)
             # don't binarize first and last layer
@@ -63,7 +65,6 @@ class Model(ModelDesc):
             else:
                 logger.info("Binarizing weight {}".format(v.op.name))
                 return fw(v)
-        tf.get_variable = new_get_variable
 
         def cabs(x):
             return tf.minimum(1.0, tf.abs(x), name='cabs')
@@ -73,7 +74,8 @@ class Model(ModelDesc):
 
         image = image / 256.0
 
-        with argscope(BatchNorm, decay=0.9, epsilon=1e-4), \
+        with replace_get_variable(new_get_variable), \
+                argscope(BatchNorm, decay=0.9, epsilon=1e-4), \
                 argscope(Conv2D, use_bias=False, nl=tf.identity):
             logits = (LinearWrap(image)
                       .Conv2D('conv0', 48, 5, padding='VALID', use_bias=True)
@@ -108,7 +110,6 @@ class Model(ModelDesc):
                       .apply(fg).BatchNorm('bn6')
                       .apply(cabs)
                       .FullyConnected('fc1', 10, nl=tf.identity)())
-        tf.get_variable = old_get_variable
         prob = tf.nn.softmax(logits, name='output')
 
         # compute the number of failed samples

tensorpack/models/__init__.py

@@ -7,6 +7,8 @@ from types import ModuleType
 import six
 import os
 import os.path
+# this line is necessary for TFModuleFunc to work
+import tensorflow as tf  # noqa: F401
 from ..utils import logger
 
 __all__ = ['LinearWrap']

tensorpack/tfutils/varreplace.py

+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# File: varreplace.py
+# Credit: Qinyao He
+
+import tensorflow as tf
+from tensorflow.python.ops import variable_scope
+from contextlib import contextmanager
+
+__all__ = ['replace_get_variable']
+
+
+@contextmanager
+def replace_get_variable(fn):
+    old_getv = tf.get_variable
+    old_vars_getv = variable_scope.get_variable
+
+    tf.get_variable = fn
+    variable_scope.get_variable = fn
+    yield
+    tf.get_variable = old_getv
+    variable_scope.get_variable = old_vars_getv