globvars in char-rnn

examples/GAN/Image2Image.py

@@ -26,7 +26,7 @@ To visualize:
 """
 
 SHAPE = 256
-BATCH = 16
+BATCH = 4
 IN_CH = 3
 OUT_CH = 3
 LAMBDA = 100
@@ -108,7 +108,7 @@ class Model(ModelDesc):
         self.g_loss = tf.add(self.g_loss, LAMBDA * errL1, name='total_g_loss')
         add_moving_summary(errL1, self.g_loss)
 
-        # visualization
+        # tensorboard visualization
         if IN_CH == 1:
             input = tf.image.grayscale_to_rgb(input)
         if OUT_CH == 1:
@@ -186,7 +186,7 @@ if __name__ == '__main__':
     parser.add_argument('--gpu', help='comma separated list of GPU(s) to use.')
     parser.add_argument('--load', help='load model')
     parser.add_argument('--sample', action='store_true', help='run sampling')
-    parser.add_argument('--data', help='A directory of images')
+    parser.add_argument('--data', help='A directory of 512x256 images')
     parser.add_argument('--mode', choices=['AtoB', 'BtoA'], default='AtoB')
     global args
     args = parser.parse_args()

examples/char-rnn/char-rnn.py

@@ -15,16 +15,11 @@ from six.moves import map, range
 from tensorpack import *
 from tensorpack.tfutils.gradproc import  *
 from tensorpack.utils.lut import LookUpTable
+from tensorpack.utils.globvars import globalns as param
 
 from tensorflow.python.ops import rnn_cell
 from tensorflow.python.ops import rnn
 
-if six.PY2:
-    class NS: pass  # this is a hack
-else:
-    import types
-    NS = types.SimpleNamespace  # this is what I wanted..
-param = NS()
 # some model hyperparams to set
 param.batch_size = 128
 param.rnn_size = 256
@@ -118,9 +113,7 @@ def get_config():
         dataset=ds,
         optimizer=tf.train.AdamOptimizer(lr),
         callbacks=Callbacks([
-            StatPrinter(),
-            ModelSaver(),
-            #HumanHyperParamSetter('learning_rate', 'hyper.txt')
+            StatPrinter(), ModelSaver(),
             ScheduledHyperParamSetter('learning_rate', [(25, 2e-4)])
         ]),
         model=Model(),
@@ -128,6 +121,7 @@ def get_config():
         max_epoch=50,
     )
 
+# TODO rewrite using Predictor interface
 def sample(path, start, length):
     """
     :param path: path to the model

tensorpack/utils/globvars.py

+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# File: globvars.py
+# Author: Yuxin Wu <ppwwyyxxc@gmail.com>
+
+import six
+
+__all__ = ['globalns']
+
+if six.PY2:
+    class NS: pass
+else:
+    import types
+    NS = types.SimpleNamespace
+
+globalns = NS()