SYMBOL INDEX (31 symbols across 3 files)

FILE: inference.py
  function get_arguments (line 22) | def get_arguments():
  function read_labelcolours (line 31) | def read_labelcolours(matfn):
  function decode_labels (line 39) | def decode_labels(mask, num_images=1, num_classes=150):
  function load (line 55) | def load(saver, sess, ckpt_path):
  function main (line 59) | def main():

FILE: model.py
  class DeepLabResNetModel (line 9) | class DeepLabResNetModel(Network):
    method setup (line 10) | def setup(self, is_training, num_classes):

FILE: network.py
  function layer (line 8) | def layer(op):
  class Network (line 33) | class Network(object):
    method __init__ (line 35) | def __init__(self, inputs, trainable=True, is_training=False, num_clas...
    method setup (line 50) | def setup(self, is_training):
    method load (line 54) | def load(self, data_path, session, ignore_missing=False):
    method feed (line 71) | def feed(self, *args):
    method get_output (line 86) | def get_output(self):
    method get_unique_name (line 90) | def get_unique_name(self, prefix):
    method make_var (line 97) | def make_var(self, name, shape):
    method validate_padding (line 101) | def validate_padding(self, padding):
    method conv (line 106) | def conv(self,
    method atrous_conv (line 149) | def atrous_conv(self,
    method relu (line 191) | def relu(self, input, name):
    method max_pool (line 195) | def max_pool(self, input, k_h, k_w, s_h, s_w, name, padding=DEFAULT_PA...
    method avg_pool (line 204) | def avg_pool(self, input, k_h, k_w, s_h, s_w, name, padding=DEFAULT_PA...
    method lrn (line 213) | def lrn(self, input, radius, alpha, beta, name, bias=1.0):
    method concat (line 222) | def concat(self, inputs, axis, name):
    method add (line 226) | def add(self, inputs, name):
    method fc (line 230) | def fc(self, input, num_out, name, relu=True):
    method softmax (line 248) | def softmax(self, input, name):
    method batch_normalization (line 261) | def batch_normalization(self, input, name, is_training, activation_fn=...
    method dropout (line 273) | def dropout(self, input, keep_prob, name):
    method resize_bilinear (line 278) | def resize_bilinear(self, input, size, name):
    method global_average_pooling (line 282) | def global_average_pooling(self, input, name):