SYMBOL INDEX (79 symbols across 12 files)

FILE: datasets/cifar10.py
  class Dataset (line 16) | class Dataset(object):
    method __init__ (line 18) | def __init__(self, ids, name='default',
    method get_data (line 38) | def get_data(self, id):
    method ids (line 45) | def ids(self):
    method __len__ (line 48) | def __len__(self):
    method __repr__ (line 51) | def __repr__(self):
  function create_default_splits (line 58) | def create_default_splits(is_train=True):
  function all_ids (line 66) | def all_ids(num_trains):

FILE: datasets/fashion_mnist.py
  class Dataset (line 16) | class Dataset(object):
    method __init__ (line 18) | def __init__(self, ids, name='default',
    method get_data (line 38) | def get_data(self, id):
    method ids (line 45) | def ids(self):
    method __len__ (line 48) | def __len__(self):
    method __repr__ (line 51) | def __repr__(self):
  function create_default_splits (line 58) | def create_default_splits(is_train=True):
  function all_ids (line 66) | def all_ids(num_trains):

FILE: datasets/imagenet.py
  class Dataset (line 19) | class Dataset(object):
    method __init__ (line 21) | def __init__(self, ids, name='default',
    method load_image (line 38) | def load_image(self, id):
    method get_data (line 51) | def get_data(self, id):
    method ids (line 57) | def ids(self):
    method __len__ (line 60) | def __len__(self):
    method __size__ (line 63) | def __size__(self):
    method __repr__ (line 66) | def __repr__(self):
  function create_default_splits (line 73) | def create_default_splits(is_train=True, ratio=0.8):
  function all_ids (line 83) | def all_ids():

FILE: datasets/mnist.py
  class Dataset (line 16) | class Dataset(object):
    method __init__ (line 18) | def __init__(self, ids, name='default',
    method get_data (line 38) | def get_data(self, id):
    method ids (line 45) | def ids(self):
    method __len__ (line 48) | def __len__(self):
    method __repr__ (line 51) | def __repr__(self):
  function create_default_splits (line 58) | def create_default_splits(is_train=True):
  function all_ids (line 66) | def all_ids(num_trains):

FILE: datasets/svhn.py
  class Dataset (line 16) | class Dataset(object):
    method __init__ (line 18) | def __init__(self, ids, name='default',
    method get_data (line 38) | def get_data(self, id):
    method ids (line 45) | def ids(self):
    method __len__ (line 48) | def __len__(self):
    method __repr__ (line 51) | def __repr__(self):
  function create_default_splits (line 58) | def create_default_splits(is_train=True):
  function all_ids (line 66) | def all_ids(num_trains):

FILE: datasets/tiny_imagenet.py
  class Dataset (line 18) | class Dataset(object):
    method __init__ (line 20) | def __init__(self, ids, name='default',
    method load_image (line 44) | def load_image(self, id):
    method get_data (line 63) | def get_data(self, id):
    method ids (line 69) | def ids(self):
    method __len__ (line 72) | def __len__(self):
    method __size__ (line 75) | def __size__(self):
    method __repr__ (line 78) | def __repr__(self):
  function create_default_splits (line 85) | def create_default_splits(is_train=True, ratio=0.8):
  function all_ids (line 93) | def all_ids():

FILE: download.py
  function prepare_h5py (line 15) | def prepare_h5py(train_image, train_label, test_image,
  function check_file (line 51) | def check_file(data_dir):
  function download_mnist (line 61) | def download_mnist(download_path, fashion_mnist=False):
  function download_svhn (line 115) | def download_svhn(download_path):
  function download_cifar10 (line 144) | def download_cifar10(download_path):

FILE: input_ops.py
  function check_data_id (line 6) | def check_data_id(dataset, data_id):
  function create_input_ops (line 23) | def create_input_ops(dataset,

FILE: model.py
  class Model (line 12) | class Model(object):
    method __init__ (line 14) | def __init__(self, config, debug_information=False, is_train=True):
    method get_feed_dict (line 38) | def get_feed_dict(self, batch_chunk, step=None, is_training=None):
    method build (line 48) | def build(self, is_train=True):

FILE: ops.py
  function norm (line 6) | def norm(x, norm_type, is_train, G=32, esp=1e-5):
  function lrelu (line 38) | def lrelu(x, leak=0.2, name="lrelu"):
  function selu (line 45) | def selu(x):
  function huber_loss (line 51) | def huber_loss(labels, predictions, delta=1.0):
  function conv2d (line 59) | def conv2d(input, output_shape, is_train, info=False,
  function fc (line 77) | def fc(input, output_shape, is_train, info=False,
  function residual_block (line 85) | def residual_block(input, output_shape, is_train, info=False, k=3, s=1,

FILE: trainer.py
  class Trainer (line 20) | class Trainer(object):
    method __init__ (line 21) | def __init__(self,
    method train (line 139) | def train(self):
    method run_single_step (line 177) | def run_single_step(self, batch, step, is_train=True, update_global_st...
    method run_test (line 197) | def run_test(self, batch, is_train=False, repeat_times=8):
    method log_step_message (line 212) | def log_step_message(self, step, accuracy, loss, step_time, is_train=T...
  function main (line 229) | def main():

FILE: util.py
  function _infov (line 45) | def _infov(self, msg, *args, **kwargs):
  function train_test_summary (line 51) | def train_test_summary(name, value, max_outputs=4, summary_type='scalar'):