util routine

pinky/src/data.py

@@ -257,7 +257,8 @@ class PileData(DataGenerator):
 
 
 
-class OnTheFlyData(DataGenerator):
+class GFData(DataGenerator):
+    swarm = swarm.Swarm.T()
     gf_engine = Engine.T()
     n_sources = Int.T(default=100)
     onset_phase = String.T(default='p')
@@ -294,8 +295,6 @@ class OnTheFlyData(DataGenerator):
         return (n, e, source.depth)
 
     def generate(self):
-        swarm = synthi.setup(self.gf_engine, self.n_sources)
-
         sources = swarm.get_effective_sources()
         self.tensor_shape = (len(self.targets), self.n_samples_max)
 

pinky/src/model.py

@@ -14,6 +14,11 @@ import shutil
 logger = logging.getLogger('pinky.model')
 
 
+def delete_if_exists(dirname):
+    if os.path.exists(dirname):
+        logger.info('deleting directory: %s' % dirname)
+        shutil.rmtree(dirname)
+
 class Model(Object):
 
     data_generator = DataGeneratorBase.T()
@@ -29,16 +34,19 @@ class Model(Object):
     def __init__(self, tf_config=None, debug=False, **kwargs):
         super().__init__(**kwargs)
 
-        if self.auto_clear and os.path.exists(self.summary_outdir):
-            logger.info('deleting directory: %s' % self.summary_outdir)
-            shutil.rmtree(self.summary_outdir)
-            logger.info('deleting directory: %s' % self.outdir)
-            shutil.rmtree(self.outdir)
+        if self.auto_clear:
+            delete_if_exists(self.summary_outdir)
+            delete_if_exists(self.outdir)
 
         self.tf_config = tf_config
         self.debug = debug
         self.sess = tf.Session(config=tf_config)
 
+        # initializer = tf.truncated_normal_initializer(
+        self.initializer = tf.random_normal_initializer(
+            # mean=0.5, stddev=0.1)
+            mean=0.0, stddev=0.1)
+
     def generate_input(self):
         dataset = self.data_generator.get_dataset()
         dataset = dataset.batch(self.batch_size)
@@ -55,6 +63,7 @@ class Model(Object):
         CNN along horizontal axis
 
         :param cross_channel_kernel: convolution kernel size accross channels
+        :param n_filters: 
 
         (Needs some debugging and checking)
         '''
@@ -64,17 +73,13 @@ class Model(Object):
             cross_channel_kernel = n_channels
 
         with tf.variable_scope('conv_layer%s' %name):
-            # initializer = tf.truncated_normal_initializer(
-            initializer = tf.random_normal_initializer(
-                # mean=0.5, stddev=0.1)
-                mean=0.0, stddev=0.1)
 
             input = tf.layers.conv2d(
                 inputs=input,
                 filters=n_filters,
                 kernel_size=(cross_channel_kernel, kernel_width),    # use identity (1) along channels
                 activation=tf.nn.relu,
-                bias_initializer=initializer,
+                bias_initializer=self.initializer,
                 name=name)
 
             input = tf.layers.batch_normalization(input, training=training)
@@ -203,7 +208,7 @@ def main():
     tf_config = None
     if args.cpu:
         tf_config = tf.ConfigProto(
-            device_count = {'GPU': 0}
+            device_count={'GPU': 0}
         )
 
     if args.show_data:
@@ -237,7 +242,7 @@ def main():
             store_superdirs=['/data/stores'],
             default_store_id='vogtland_001')
 
-        data_generator = OnTheFlyData(fn_stations='stations.pf', gf_engine=gf_engine)
+        data_generator = GFData(fn_stations='stations.pf', gf_engine=gf_engine)
         model = Model(tf_config=tf_config, data_generator=data_generator)
         model.regularize()
         model.dump(filename=fn_config)