zbessinger

from tensorflow.contrib import slim
from tensorflow.contrib.slim.nets import resnet_v2

def _res_net_tfslim(self, x, n_outputs, reg=None, activation_fn=tf.nn.relu, reuse=False, is_training=True):
    
    with slim.arg_scope(self.resnet_arg_scope(is_training)):
        net, end_points = resnet_v2.resnet_v2_50(x, num_classes=n_outputs, reuse=reuse)
        net = tf.squeeze(net) # Comes out as 4D by default
        # Final linear layer
        net = fc_layer('fully_connected', net, n_outputs, activation_fn=None, reg=reg, reuse=reuse,

eamartin