fix some errors

tensorpack/models/conv2d.py

@@ -35,7 +35,7 @@ def Conv2D(x, out_channel, kernel_shape,
     if b_init is None:
         b_init = tf.constant_initializer()
 
-    W = tf.get_variable('W', filter_shape, initializer=W_init) # TODO collections
+    W = tf.get_variable('W', filter_shape, initializer=W_init)
     b = tf.get_variable('b', [out_channel], initializer=b_init)
 
     if split == 1:

tensorpack/models/fc.py

@@ -23,4 +23,4 @@ def FullyConnected(x, out_dim, W_init=None, b_init=None, nl=tf.nn.relu):
 
     W = tf.get_variable('W', [in_dim, out_dim], initializer=W_init)
     b = tf.get_variable('b', [out_dim], initializer=b_init)
-    return nl(tf.matmul(x, W) + b)
+    return nl(tf.matmul(x, W) + b, name=tf.get_variable_scope().name + '_output')

tensorpack/train.py

@@ -87,7 +87,7 @@ def start_train(config):
     # start training:
     coord = tf.train.Coordinator()
     # a thread that keeps filling the queue
-    input_th = EnqueueThread(sess, coord, enqueue_op, dataset)
+    input_th = EnqueueThread(sess, coord, enqueue_op, dataset, input_queue)
     model_th = tf.train.start_queue_runners(
         sess=sess, coord=coord, daemon=True, start=True)
     input_th.start()
@@ -101,7 +101,9 @@ def start_train(config):
                     if coord.should_stop():
                         return
                     fetches = [train_op, cost_var] + output_vars + model_inputs
+                    print 'before'
                     results = sess.run(fetches)
+                    print 'after'
                     cost = results[1]
                     outputs = results[2:2 + len(output_vars)]
                     inputs = results[-len(model_inputs):]

tensorpack/utils/concurrency.py

@@ -25,13 +25,15 @@ class StoppableThread(threading.Thread):
 
 
 class EnqueueThread(threading.Thread):
-    def __init__(self, sess, coord, enqueue_op, dataflow):
+    def __init__(self, sess, coord, enqueue_op, dataflow, queue):
         super(EnqueueThread, self).__init__()
         self.sess = sess
         self.coord = coord
         self.input_vars = sess.graph.get_collection(INPUT_VARS_KEY)
         self.dataflow = dataflow
         self.op = enqueue_op
+        self.queue = queue
+
         self.daemon = True
 
     def run(self):
@@ -45,8 +47,8 @@ class EnqueueThread(threading.Thread):
         except tf.errors.CancelledError as e:
             pass
         except Exception:
-            # TODO close queue.
             logger.exception("Exception in EnqueueThread:")
+            self.queue.close(cancel_pending_enqueues=True)
             self.coord.request_stop()
 
 @contextmanager

tensorpack/utils/sessinit.py

@@ -35,6 +35,7 @@ class ParamRestore(SessionInit):
         self.prms = param_dict
 
     def init(self, sess):
+        sess.run(tf.initialize_all_variables())
         variables = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES)
         var_dict = dict([v.name, v] for v in variables)
         for name, value in self.prms.iteritems():