misc small fixes

docs/_static/build_toc_group.js

@@ -17,7 +17,7 @@ $(function (){
       if (fullname.startsWith('tensorpack.'))
         fullname = fullname.substr(11);
 
-      if (fullname == "tensorpack.dataflow.MultiProcessMapData") {
+      if (fullname == "dataflow.MultiProcessMapData") {
         groupName = "parallel_map";
       }
 

examples/GAN/BEGAN.py

@@ -11,7 +11,7 @@ from tensorpack.tfutils.summary import add_moving_summary
 from tensorpack.utils.gpu import get_num_gpu
 
 import DCGAN
-from GAN import GANModelDesc, GANTrainer, MultiGPUGANTrainer
+from GAN import GANModelDesc, GANTrainer
 
 """
 Boundary Equilibrium GAN.
@@ -139,11 +139,7 @@ if __name__ == '__main__':
         input = QueueInput(DCGAN.get_data())
         model = Model()
         nr_tower = max(get_num_gpu(), 1)
-        if nr_tower == 1:
-            trainer = GANTrainer(input, model)
-        else:
-            trainer = MultiGPUGANTrainer(nr_tower, input, model)
-
+        trainer = GANTrainer(input, model, num_gpu=nr_tower)
         trainer.train_with_defaults(
             callbacks=[
                 ModelSaver(),

examples/GAN/GAN.py

@@ -105,7 +105,7 @@ class GANTrainer(TowerTrainer):
         not needed. Just calling model.build_graph directly is OK.
         """
         # Build the graph
-        self.tower_func = TowerFuncWrapper(model.build_graph, model.get_input_signature())
+        self.tower_func = TowerFuncWrapper(model.build_graph, model.inputs())
         with TowerContext('', is_training=True):
             self.tower_func(*input.get_input_tensors())
         opt = model.get_optimizer()
@@ -167,7 +167,7 @@ class SeparateGANTrainer(TowerTrainer):
         self.register_callback(cbs)
 
         # Build the graph
-        self.tower_func = TowerFuncWrapper(model.build_graph, model.get_input_signature())
+        self.tower_func = TowerFuncWrapper(model.build_graph, model.inputs())
         with TowerContext('', is_training=True), \
                 argscope(BatchNorm, ema_update='internal'):
             # should not hook the EMA updates to both train_op, it will hurt training speed.

examples/GAN/Improved-WGAN.py

@@ -93,7 +93,7 @@ if __name__ == '__main__':
         logger.auto_set_dir()
         SeparateGANTrainer(
             QueueInput(DCGAN.get_data()),
-            M, g_period=6).train_with_defaults(
+            M, g_period=5).train_with_defaults(
             callbacks=[ModelSaver()],
             steps_per_epoch=300,
             max_epoch=200,

examples/GAN/README.md

@@ -63,6 +63,7 @@ Train a simple GAN on mnist, conditioned on the class labels.
 ## [WGAN.py](WGAN.py), [Improved-WGAN.py](Improved-WGAN.py), [BEGAN.py](BEGAN.py)
 
 These variants are implemented by some small modifications on top of DCGAN.py.
+BEGAN has the best visual quality among them.
 Some BEGAN samples:
 
 ![began-sample](demo/BEGAN-CelebA-samples.jpg)

scripts/dump-model-params.py

@@ -3,7 +3,6 @@
 # File: dump-model-params.py
 
 import argparse
-import sys
 import numpy as np
 import os
 import six
@@ -21,7 +20,7 @@ def _import_external_ops(message):
         logger.info("Importing horovod ...")
         import horovod.tensorflow  # noqa
         return
-    if  "MaxBytesInUse" in message:
+    if "MaxBytesInUse" in message:
         logger.info("Importing memory_stats ...")
         from tensorflow.contrib.memory_stats import MaxBytesInUse  # noqa
         return
@@ -34,9 +33,9 @@ def _import_external_ops(message):
                 pass
             else:
                 _validate_and_load_nccl_so()
-            from tensorflow.contrib.nccl.ops import gen_nccl_ops
+            from tensorflow.contrib.nccl.ops import gen_nccl_ops  # noqa
         else:
-            from tensorflow.python.ops import gen_nccl_ops
+            from tensorflow.python.ops import gen_nccl_ops  # noqa
         return