diff --git a/bob/learn/tensorflow/network/Dummy.py b/bob/learn/tensorflow/network/Dummy.py index 900c65eb6b1c64627e6dba513138b97232c554d5..201d809e195f46ba59e0b54712cb225ae95b19be 100755 --- a/bob/learn/tensorflow/network/Dummy.py +++ b/bob/learn/tensorflow/network/Dummy.py @@ -4,33 +4,34 @@ import tensorflow as tf -def dummy(conv1_kernel_size=3, conv1_output=1, fc1_output=2, seed=10): + +def dummy(inputs, reuse=False): """ Create all the necessary variables for this CNN **Parameters** - conv1_kernel_size: - conv1_output: - fc1_output: - seed = 10 + inputs: + + reuse: """ slim = tf.contrib.slim - end_points = dict() - initializer = tf.contrib.layers.xavier_initializer(uniform=False, dtype=tf.float32, seed=seed) - - graph = slim.conv2d(inputs, conv1_output, conv1_kernel_size, activation_fn=tf.nn.relu, - stride=1, - weights_initializer=initializer, - scope='conv1') + + initializer = tf.contrib.layers.xavier_initializer() + + graph = slim.conv2d(inputs, 10, [3, 3], activation_fn=tf.nn.relu, stride=1, scope='conv1', + weights_initializer=initializer, reuse=reuse) end_points['conv1'] = graph - + + graph = slim.max_pool2d(graph, [4, 4], scope='pool1') + end_points['pool1'] = graph + graph = slim.flatten(graph, scope='flatten1') end_points['flatten1'] = graph - graph = slim.fully_connected(graph, fc1_output, + graph = slim.fully_connected(graph, 50, weights_initializer=initializer, activation_fn=None, scope='fc1')