remove all_variables

tensorpack/callbacks/param.py

@@ -43,12 +43,7 @@ class GraphVarParam(HyperParam):
         self._readable_name, self.var_name = get_op_var_name(name)
 
     def setup_graph(self):
-        try:
-            all_vars = tf.global_variables()
-        except:
-            # TODO
-            all_vars = tf.all_variables()
-
+        all_vars = tf.global_variables()
         for v in all_vars:
             if v.name == self.var_name:
                 self.var = v

tensorpack/models/_test.py

@@ -10,7 +10,7 @@ import unittest
 class TestModel(unittest.TestCase):
     def run_variable(self, var):
         sess = tf.Session()
-        sess.run(tf.initialize_all_variables())
+        sess.run(tf.global_variables_initializer())
         if isinstance(var, list):
             return sess.run(var)
         else:

tensorpack/models/image_sample.py

@@ -151,7 +151,7 @@ if __name__ == '__main__':
     mapv = tf.Variable(mapping)
     output = ImageSample('sample', [imv, mapv], borderMode='constant')
     sess = tf.Session()
-    sess.run(tf.initialize_all_variables())
+    sess.run(tf.global_variables_initializer())
 
     #out = sess.run(tf.gradients(tf.reduce_sum(output), mapv))
     #out = sess.run(output)

tensorpack/tfutils/sessinit.py

@@ -46,7 +46,7 @@ class NewSession(SessionInit):
     initializer.
     """
     def _init(self, sess):
-        sess.run(tf.initialize_all_variables())
+        sess.run(tf.global_variables_initializer())
 
 class SaverRestore(SessionInit):
     """
@@ -85,10 +85,7 @@ class SaverRestore(SessionInit):
         for dic in SaverRestore._produce_restore_dict(vars_map):
             # multiple saver under same name scope would cause error:
             # training/saver.py: assert restore_op.name.endswith("restore_all"), restore_op.name
-            try:
-                saver = tf.train.Saver(var_list=dic, name=str(id(dic)), write_version=2)
-            except:
-                saver = tf.train.Saver(var_list=dic, name=str(id(dic)))
+            saver = tf.train.Saver(var_list=dic, name=str(id(dic)), write_version=2)
             saver.restore(sess, self.path)
 
     def set_path(self, model_path):
@@ -124,10 +121,7 @@ class SaverRestore(SessionInit):
         :param vars_available: varaible names available in the checkpoint, for existence checking
         :returns: a dict of {var_name: [var, var]} to restore
         """
-        try:
-            vars_to_restore = tf.global_variables()
-        except AttributeError:
-            vars_to_restore = tf.all_variables()
+        vars_to_restore = tf.global_variables()
         var_dict = defaultdict(list)
         chkpt_vars_used = set()
         for v in vars_to_restore:

tensorpack/train/base.py

@@ -119,10 +119,7 @@ class Trainer(object):
 
         logger.info("Initializing graph variables ...")
         # TODO newsession + sessinit?
-        try:
-            initop = tf.global_variables_initializer()
-        except:
-            initop = tf.initialize_all_variables()
+        initop = tf.global_variables_initializer()
         self.sess.run(initop)
         self.config.session_init.init(self.sess)