Still scratching

bob/learn/tensorflow/layers/Conv2D.py

+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+# @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
+# @date: Wed 11 May 2016 17:38 CEST
+
+import tensoflow as tf
+from bob.learn.tensorflow.util import *
+from .Layer import Layer
+
+
+class Conv2D(Layer):
+
+    """
+    2D Convolution
+    """
+
+    def __init__(self, input, activation=None,
+                 kernel_size=3,
+                 filters=8,
+                 initialization='xavier',
+                 use_gpu=False,
+                 seed=10
+                 ):
+        """
+        Base constructor
+
+        **Parameters**
+        input: Layer input
+        activation: Tensor Flow activation
+        kernel_size: Size of the convolutional kernel
+        filters: Number of filters
+        initialization: Initialization type
+        use_gpu: Store data in the GPU
+        seed: Seed for the Random number generation
+        """
+        super(Conv2D, self).__init__(input, initialization='xavier', use_gpu=False, seed=10)
+        self.activation = activation
+
+        self.W = create_weight_variables([kernel_size, kernel_size, 1, filters],
+                                         seed=seed, name="conv", use_gpu=use_gpu)
+
+        if activation is not None:
+            self.b = create_bias_variables([filters], name="bias", use_gpu=self.use_gpu)
+
+    def get_graph(self):
+        with tf.name_scope('conv'):
+            conv = tf.nn.conv2d(self.input, self.W, strides=[1, 1, 1, 1], padding='SAME')
+
+        with tf.name_scope('activation'):
+            non_linearity = tf.nn.tanh(tf.nn.bias_add(conv, self.b))
+
+        return non_linearity

bob/learn/tensorflow/layers/Layer.py

+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+# @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
+# @date: Wed 11 May 2016 17:38 CEST
+
+import tensoflow as tf
+
+
+class Layer(object):
+
+    """
+    Layer base class
+    """
+
+    def __init__(self, input, initialization='xavier', use_gpu=False, seed=10):
+        """
+        Base constructor
+
+        **Parameters**
+        input: Layer input
+
+        """
+        self.input = input
+        self.initialization = initialization
+        self.use_gpu = use_gpu
+        self.seed = seed
+
+    def get_graph(self):
+        NotImplementedError("Please implement this function in derived classes")

bob/learn/tensorflow/layers/Layers.py

-# see https://docs.python.org/3/library/pkgutil.html
-from pkgutil import extend_path
-__path__ = extend_path(__path__, __name__)
-
-from DataShuffler import *
-
-

bob/learn/tensorflow/layers/MaxPooling.py

+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+# @author: Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
+# @date: Wed 11 May 2016 17:38 CEST
+
+import tensoflow as tf
+from bob.learn.tensorflow.util import *
+from .Layer import Layer
+
+
+class MaxPooling(Layer):
+
+    
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