update some examples

examples/A3C-Gym/train-atari.py

@@ -18,6 +18,7 @@ import tensorflow as tf
 import six
 from six.moves import queue
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.utils.concurrency import *
 from tensorpack.utils.serialize import *
@@ -303,5 +304,5 @@ if __name__ == '__main__':
         config = get_config()
         if args.load:
             config.session_init = get_model_loader(args.load)
-        trainer = QueueInputTrainer if config.nr_tower == 1 else AsyncMultiGPUTrainer
-        trainer(config).train()
+        trainer = SimpleTrainer() if config.nr_tower == 1 else AsyncMultiGPUTrainer(config.tower)
+        launch_train_with_config(config, trainer)

examples/CTC-TIMIT/train-timit.py

@@ -12,6 +12,7 @@ import operator
 import six
 from six.moves import map, range
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.tfutils.gradproc import SummaryGradient, GlobalNormClip
 from tensorpack.utils.globvars import globalns as param
@@ -94,7 +95,7 @@ def get_data(path, isTrain, stat_file):
 
 def get_config(ds_train, ds_test):
     return TrainConfig(
-        dataflow=ds_train,
+        data=QueueInput(ds_train),
         callbacks=[
             ModelSaver(),
             StatMonitorParamSetter('learning_rate', 'error',
@@ -128,4 +129,4 @@ if __name__ == '__main__':
     config = get_config(ds_train, ds_test)
     if args.load:
         config.session_init = SaverRestore(args.load)
-    QueueInputTrainer(config).train()
+    launch_train_with_config(config, SimpleTrainer())

examples/Char-RNN/char-rnn.py

@@ -12,6 +12,7 @@ import operator
 import six
 from six.moves import map, range
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.tfutils import symbolic_functions, summary, optimizer
 from tensorpack.tfutils.gradproc import GlobalNormClip
@@ -116,7 +117,7 @@ def get_config():
     ds = BatchData(ds, param.batch_size)
 
     return TrainConfig(
-        dataflow=ds,
+        data=QueueInput(ds),
         callbacks=[
             ModelSaver(),
             ScheduledHyperParamSetter('learning_rate', [(25, 2e-4)])
@@ -190,4 +191,4 @@ if __name__ == '__main__':
         config = get_config()
         if args.load:
             config.session_init = SaverRestore(args.load)
-        QueueInputTrainer(config).train()
+        launch_train_with_config(config, SimpleTrainer())

examples/DeepQNetwork/DQN.py

@@ -16,6 +16,7 @@ import multiprocessing
 import threading
 from collections import deque
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.utils.concurrency import *
 import tensorflow as tf
@@ -105,7 +106,7 @@ def get_config():
     )
 
     return TrainConfig(
-        dataflow=expreplay,
+        data=QueueInput(expreplay),
         model=Model(),
         callbacks=[
             ModelSaver(),
@@ -166,4 +167,4 @@ if __name__ == '__main__':
         config = get_config()
         if args.load:
             config.session_init = get_model_loader(args.load)
-        QueueInputTrainer(config).train()
+        launch_train_with_config(config, SimpleTrainer())

examples/DisturbLabel/mnist-disturb.py

@@ -8,6 +8,7 @@ import os
 import sys
 import argparse
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.dataflow import dataset
 import tensorflow as tf
@@ -65,4 +66,4 @@ if __name__ == '__main__':
         os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
 
     config = get_config()
-    QueueInputTrainer(config).train()
+    launch_train_with_config(config, SimpleTrainer())

examples/DisturbLabel/svhn-disturb.py

@@ -8,6 +8,7 @@ import numpy as np
 import os
 import imp
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.dataflow import dataset
 
@@ -56,4 +57,4 @@ if __name__ == '__main__':
         os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
     config = get_config(args.prob)
-    QueueInputTrainer(config).train()
+    launch_train_with_config(config, SimpleTrainer())

examples/DoReFa-Net/alexnet-dorefa.py

@@ -11,6 +11,7 @@ import multiprocessing
 import os
 import sys
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.tfutils.symbolic_functions import *
 from tensorpack.tfutils.summary import *
@@ -322,4 +323,4 @@ if __name__ == '__main__':
     if args.load:
         config.session_init = SaverRestore(args.load)
     config.nr_tower = nr_tower
-    SyncMultiGPUTrainer(config).train()
+    launch_train_with_config(configi, SyncMultiGPUTrainer(list(range(nr_tower))))

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

@@ -7,6 +7,7 @@ import argparse
 import numpy as np
 import os
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.tfutils.symbolic_functions import *
 from tensorpack.tfutils.summary import *
@@ -163,7 +164,7 @@ def get_config():
     data_test = BatchData(data_test, 128, remainder=True)
 
     return TrainConfig(
-        dataflow=data_train,
+        data=QueueInput(data_train),
         callbacks=[
             ModelSaver(),
             InferenceRunner(data_test,
@@ -183,4 +184,4 @@ if __name__ == '__main__':
 
     BITW, BITA, BITG = map(int, args.dorefa.split(','))
     config = get_config()
-    QueueInputTrainer(config).train()
+    launch_train_with_config(config, SimpleTrainer())

examples/DynamicFilterNetwork/steering-filter.py

@@ -6,10 +6,12 @@ import argparse
 import numpy as np
 import tensorflow as tf
 import cv2
+import os
 from scipy.signal import convolve2d
 from six.moves import range, zip
 import multiprocessing
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.utils import logger
 from tensorpack.utils.viz import *
@@ -262,5 +264,4 @@ if __name__ == '__main__':
         config = get_config()
         if args.load:
             config.session_init = SaverRestore(args.load)
-        config.nr_tower = NR_GPU
-        SyncMultiGPUTrainer(config).train()
+        launch_train_with_config(config, SyncMultiGPUTrainer(list(range(NR_GPU))))

examples/FasterRCNN/train.py

@@ -13,6 +13,7 @@ import numpy as np
 import json
 import tensorflow as tf
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 import tensorpack.tfutils.symbolic_functions as symbf
 from tensorpack.tfutils.summary import add_moving_summary
@@ -300,6 +301,6 @@ if __name__ == '__main__':
             steps_per_epoch=stepnum,
             max_epoch=205000 * factor // stepnum,
             session_init=get_model_loader(args.load) if args.load else None,
-            nr_tower=get_nr_gpu()
         )
-        SyncMultiGPUTrainerReplicated(cfg, gpu_prefetch=False).train()
+        trainer = SyncMultiGPUTrainerReplicated(range(len(get_nr_gpu())))
+        launch_train_with_config(cfg, trainer)

examples/HED/hed.py

@@ -11,6 +11,7 @@ from six.moves import zip
 import os
 import sys
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 import tensorpack.tfutils.symbolic_functions as symbf
 from tensorpack.dataflow import dataset
@@ -231,5 +232,6 @@ if __name__ == '__main__':
         config = get_config()
         if args.load:
             config.session_init = get_model_loader(args.load)
-        config.nr_tower = max(get_nr_gpu(), 1)
-        SyncMultiGPUTrainer(config).train()
+        launch_train_with_config(
+            config,
+            SyncMultiGPUTrainer(range(max(get_nr_gpu(), 1))))

examples/boilerplate.py

@@ -5,6 +5,7 @@
 import os
 import argparse
 import tensorflow as tf
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 
 """
@@ -51,7 +52,7 @@ def get_config():
 
     return TrainConfig(
         model=Model(),
-        dataflow=ds_train,
+        data=QueueInput(ds_train),
         callbacks=[
             ModelSaver(),
             InferenceRunner(ds_test, [ScalarStats('total_costs')]),
@@ -77,4 +78,4 @@ if __name__ == '__main__':
     if args.load:
         config.session_init = SaverRestore(args.load)
 
-    SyncMultiGPUTrainer(config).train()
+    launch_train_with_config(config, SimpleTrainer())

examples/mnist-tfslim.py

@@ -14,6 +14,7 @@ the only differences are:
     2. use slim names to summarize weights
 """
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.dataflow import dataset
 import tensorflow as tf
@@ -101,4 +102,4 @@ if __name__ == '__main__':
         os.environ['CUDA_VISIBLE_DEVICES'] = args.gpu
 
     config = get_config()
-    SimpleTrainer(config).train()
+    launch_train_with_config(config, SimpleTrainer())

examples/mnist-visualizations.py

@@ -11,6 +11,7 @@ import argparse
 MNIST ConvNet example with weights/activations visualization.
 """
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.dataflow import dataset
 import tensorflow as tf
@@ -161,4 +162,4 @@ if __name__ == '__main__':
     config = get_config()
     if args.load:
         config.session_init = SaverRestore(args.load)
-    SimpleTrainer(config).train()
+    launch_train_with_config(config, SimpleTrainer())

examples/svhn-digit-convnet.py

@@ -7,6 +7,7 @@ import argparse
 import numpy as np
 import os
 
+os.environ['TENSORPACK_TRAIN_API'] = 'v2'   # will become default soon
 from tensorpack import *
 from tensorpack.tfutils.symbolic_functions import prediction_incorrect
 from tensorpack.dataflow import dataset
@@ -99,7 +100,7 @@ def get_config():
 
     return TrainConfig(
         model=Model(),
-        dataflow=data_train,
+        data=QueueInput(data_train),
         callbacks=[
             ModelSaver(),
             InferenceRunner(data_test,
@@ -125,4 +126,4 @@ if __name__ == '__main__':
         config = get_config()
         if args.load:
             config.session_init = SaverRestore(args.load)
-        QueueInputTrainer(config).train()
+        launch_train_with_config(config, SimpleTrainer())

tensorpack/train/interface.py

@@ -43,12 +43,12 @@ def apply_default_prefetch(input_source_or_dataflow, trainer, towers):
 
 def launch_train_with_config(config, trainer):
     """
-    Train with a :class:`TrainConfig` and a new version of :class:`Trainer`, to
+    Train with a :class:`TrainConfig` and a :class:`Trainer`, to
     mimic the old training interface.
 
     Args:
         config (TrainConfig):
-        trainer (Trainer): an instance of the new trainer
+        trainer (Trainer): an instance of a SingleCostTrainer
 
     Examples: