#!/usr/bin/env python
[docs]def scratch_network(inputs, end_point="fc1", reuse=False):
import tensorflow as tf
slim = tf.contrib.slim
# Creating a random network
initializer = tf.contrib.layers.xavier_initializer(seed=10)
end_points = dict()
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, 10, activation_fn=None, scope='fc1',
weights_initializer=initializer, reuse=reuse)
end_points["fc1"] = graph
return end_points[end_point]
[docs]def get_config():
"""Returns a string containing the configuration information.
"""
import bob.extension
return bob.extension.get_config(__name__)
from .Extractor import Extractor
from .FaceNet import FaceNet
from .DrGanMSU import DrGanMSUExtractor
# gets sphinx autodoc done right - don't remove it
def __appropriate__(*args):
"""Says object was actually declared here, and not in the import module.
Fixing sphinx warnings of not being able to find classes, when path is
shortened. Parameters:
*args: An iterable of objects to modify
Resolves `Sphinx referencing issues
<https://github.com/sphinx-doc/sphinx/issues/3048>`
"""
for obj in args:
obj.__module__ = __name__
__appropriate__(
Extractor,
FaceNet,
DrGanMSUExtractor,
)
# gets sphinx autodoc done right - don't remove it
__all__ = [_ for _ in dir() if not _.startswith('_')]