mdb

src/encoders_decoders.py

@@ -14,7 +14,7 @@
 from tflearn.layers.normalization import batch_normalization
 from tflearn.layers.core import fully_connected, dropout
 
-from .. fundamentals.utils import expand_scope_by_name, replicate_parameter_for_all_layers
+from . tf_utils import expand_scope_by_name, replicate_parameter_for_all_layers
 
 
 def encoder_with_convs_and_symmetry_new(in_signal, n_filters=[64, 128, 256, 1024], filter_sizes=[1], strides=[1],

src/tf_utils.py

@@ -0,0 +1,42 @@
+'''
+Created on November 26, 2017
+
+@author: optas
+'''
+
+import tensorflow as tf
+import numpy as np
+
+
+def expand_scope_by_name(scope, name):
+    """ expand tf scope by given name.
+    """
+
+    if isinstance(scope, basestring):
+        scope += '/' + name
+        return scope
+
+    if scope is not None:
+        return scope.name + '/' + name
+    else:
+        return scope
+
+
+def replicate_parameter_for_all_layers(parameter, n_layers):
+    if parameter is not None and len(parameter) != n_layers:
+        if len(parameter) != 1:
+            raise ValueError()
+        parameter = np.array(parameter)
+        parameter = parameter.repeat(n_layers).tolist()
+    return parameter
+
+
+def leaky_relu(alpha):
+    if not (alpha < 1 and alpha > 0):
+        raise ValueError()
+
+    return lambda x: tf.maximum(alpha * x, x)
+
+
+def safe_log(x, eps=1e-12):
+    return tf.log(tf.maximum(x, eps))