name scope improvements for StagingInput

examples/ResNet/imagenet-resnet.py

@@ -10,7 +10,7 @@ from tensorpack import logger, QueueInput
 from tensorpack.models import *
 from tensorpack.callbacks import *
 from tensorpack.train import (
-    TrainConfig, SyncMultiGPUTrainerParameterServer, launch_train_with_config)
+    TrainConfig, SyncMultiGPUTrainerReplicated, launch_train_with_config)
 from tensorpack.dataflow import FakeData
 from tensorpack.tfutils import argscope, get_model_loader
 from tensorpack.utils.gpu import get_nr_gpu
@@ -128,10 +128,10 @@ if __name__ == '__main__':
             logger.set_logger_dir(os.path.join('train_log', 'tmp'), 'd')
         else:
             logger.set_logger_dir(
-                os.path.join('train_log', 'imagenet-resnet-d' + str(args.depth)))
+                os.path.join('train_log', 'imagenet-{}-d{}'.format(args.mode, args.depth)))
 
         config = get_config(model, fake=args.fake)
         if args.load:
             config.session_init = get_model_loader(args.load)
-        trainer = SyncMultiGPUTrainerParameterServer(max(get_nr_gpu(), 1))
+        trainer = SyncMultiGPUTrainerReplicated(max(get_nr_gpu(), 1))
         launch_train_with_config(config, trainer)

tensorpack/input_source/input_source.py

@@ -546,16 +546,18 @@ class StagingInput(FeedfreeInput):
             # TODO tensorflow/benchmarks use static shapes here,
             # though it doesn't seem to help. We can use it when it's known.
             stage = StagingArea(dtypes, shapes=None)
-            self._stage_ops.append(stage.put(inputs))
-            self._areas.append(stage)
-            outputs = stage.get()
-            if isinstance(outputs, tf.Tensor):  # when size=1, TF doesn't return a list
-                outputs = [outputs]
-            for vin, vout in zip(inputs, outputs):
-                vout.set_shape(vin.get_shape())
-            self._unstage_ops.append(outputs)
-            # self._size_ops.append(stage.size())
-            return outputs
+
+        # put & get automatically inherit the name scope from the area
+        self._stage_ops.append(stage.put(inputs))
+        self._areas.append(stage)
+        outputs = stage.get()
+        if isinstance(outputs, tf.Tensor):  # when size=1, TF doesn't return a list
+            outputs = [outputs]
+        for vin, vout in zip(inputs, outputs):
+            vout.set_shape(vin.get_shape())
+        self._unstage_ops.append(outputs)
+        # self._size_ops.append(stage.size())
+        return outputs
 
     def _get_stage_op(self):
         with self.cached_name_scope():

tensorpack/input_source/input_source_base.py

@@ -165,7 +165,7 @@ class InputSource(object):
             with tf.name_scope(self._name_scope):
                 yield self._name_scope
         else:
-            name = type(self).__name__
+            name = type(self).__name__ + '/'
             with tf.name_scope(name) as ns:
                 self._name_scope = ns
                 yield ns