SYMBOL INDEX (103 symbols across 12 files)

FILE: ch3/linear_regression_tf.py
  function pearson_r2_score (line 12) | def pearson_r2_score(y, y_pred):
  function rms_score (line 16) | def rms_score(y_true, y_pred):

FILE: ch4/fcnet_regression_tf.py
  function pearson_r2_score (line 8) | def pearson_r2_score(y, y_pred):

FILE: ch5/fcnet_func.py
  function eval_tox21_hyperparams (line 9) | def eval_tox21_hyperparams(n_hidden=50, n_layers=1, learning_rate=.001,

FILE: ch6/convolutional.py
  function download (line 47) | def download(filename):
  function extract_data (line 60) | def extract_data(filename, num_images):
  function extract_labels (line 80) | def extract_labels(filename, num_images):
  function error_rate (line 93) | def error_rate(predictions, labels):
  function model (line 103) | def model(data, train=False):
  function eval_in_batches (line 245) | def eval_in_batches(data, sess):

FILE: ch7/ptb_word_lm.py
  class PTBInput (line 75) | class PTBInput(object):
    method __init__ (line 78) | def __init__(self, config, data, name=None):
  class PTBModel (line 86) | class PTBModel(object):
    method __init__ (line 89) | def __init__(self, is_training, config, input_):
    method assign_lr (line 179) | def assign_lr(self, session, lr_value):
  class SmallConfig (line 183) | class SmallConfig(object):
  function run_epoch (line 199) | def run_epoch(session, model, eval_op=None, verbose=False):

FILE: ch7/reader.py
  function _read_words (line 29) | def _read_words(filename):
  function _build_vocab (line 37) | def _build_vocab(filename):
  function _file_to_word_ids (line 49) | def _file_to_word_ids(filename, word_to_id):
  function ptb_raw_data (line 54) | def ptb_raw_data(data_path=None):
  function ptb_producer (line 85) | def ptb_producer(raw_data, batch_size, num_steps, name=None):

FILE: ch8/a3c.py
  class A3CLoss (line 30) | class A3CLoss(Layer):
    method __init__ (line 33) | def __init__(self, value_weight, entropy_weight, **kwargs):
    method create_tensor (line 38) | def create_tensor(self, **kwargs):
  class A3C (line 52) | class A3C(object):
    method __init__ (line 80) | def __init__(self,
    method build_graph (line 124) | def build_graph(self, tf_graph, scope, model_dir):
    method fit (line 177) | def fit(self,
    method predict (line 227) | def predict(self, state):
    method select_action (line 245) | def select_action(self,
    method restore (line 273) | def restore(self):
    method create_feed_dict (line 284) | def create_feed_dict(self, state):
  class Worker (line 291) | class Worker(object):
    method __init__ (line 294) | def __init__(self, a3c, index):
    method run (line 316) | def run(self, step_count, total_steps):
    method create_rollout (line 324) | def create_rollout(self):
    method process_rollout (line 361) | def process_rollout(self, states, actions, rewards, values, step_count):
    method create_feed_dict (line 404) | def create_feed_dict(self, state):

FILE: ch8/environment.py
  class Environment (line 9) | class Environment(object):
    method __init__ (line 20) | def __init__(self, state_shape, n_actions, state_dtype=None):
  class TicTacToeEnvironment (line 34) | class TicTacToeEnvironment(Environment):
    method __init__ (line 48) | def __init__(self):
    method reset (line 54) | def reset(self):
    method step (line 63) | def step(self, action):
    method get_O_move (line 99) | def get_O_move(self):
    method check_winner (line 107) | def check_winner(self, player):
    method game_over (line 124) | def game_over(self):
    method display (line 131) | def display(self):

FILE: ch8/tensorgraph.py
  class TensorGraph (line 22) | class TensorGraph(object):
    method __init__ (line 24) | def __init__(self,
    method _add_layer (line 75) | def _add_layer(self, layer):
    method topsort (line 86) | def topsort(self):
    method build (line 101) | def build(self):
    method set_loss (line 115) | def set_loss(self, layer):
    method add_output (line 119) | def add_output(self, layer):
    method set_optimizer (line 123) | def set_optimizer(self, optimizer):
    method get_layer_variables (line 127) | def get_layer_variables(self, layer):
    method get_global_step (line 137) | def get_global_step(self):
    method _get_tf (line 140) | def _get_tf(self, obj):
    method restore (line 170) | def restore(self):
    method __del__ (line 181) | def __del__(self):
  class Layer (line 184) | class Layer(object):
    method __init__ (line 186) | def __init__(self, in_layers=None, **kwargs):
    method create_tensor (line 199) | def create_tensor(self, in_layers=None, **kwargs):
    method _get_input_tensors (line 202) | def _get_input_tensors(self, in_layers):
  function _convert_layer_to_tensor (line 220) | def _convert_layer_to_tensor(value, dtype=None, name=None, as_ref=False):
  class Dense (line 226) | class Dense(Layer):
    method __init__ (line 228) | def __init__(
    method create_tensor (line 261) | def create_tensor(self, in_layers=None, **kwargs):
  class Squeeze (line 280) | class Squeeze(Layer):
    method __init__ (line 282) | def __init__(self, in_layers=None, squeeze_dims=None, **kwargs):
    method create_tensor (line 286) | def create_tensor(self, in_layers=None, **kwargs):
  class BatchNorm (line 293) | class BatchNorm(Layer):
    method __init__ (line 295) | def __init__(self, in_layers=None, **kwargs):
    method create_tensor (line 298) | def create_tensor(self, in_layers=None, **kwargs):
  class Flatten (line 305) | class Flatten(Layer):
    method __init__ (line 308) | def __init__(self, in_layers=None, **kwargs):
    method create_tensor (line 311) | def create_tensor(self, in_layers=None, **kwargs):
  class SoftMax (line 325) | class SoftMax(Layer):
    method __init__ (line 327) | def __init__(self, in_layers=None, **kwargs):
    method create_tensor (line 330) | def create_tensor(self, in_layers=None, **kwargs):
  class Input (line 339) | class Input(Layer):
    method __init__ (line 341) | def __init__(self, shape, dtype=tf.float32, **kwargs):
    method create_tensor (line 346) | def create_tensor(self, in_layers=None, **kwargs):

FILE: ch8/tictactoe.py
  function eval_tic_tac_toe (line 13) | def eval_tic_tac_toe(value_weight,
  function main (line 64) | def main():

FILE: ch9/cifar10.py
  function distorted_inputs (line 81) | def distorted_inputs():
  function read_cifar10 (line 98) | def read_cifar10(filename_queue):
  function _distorted_inputs (line 160) | def _distorted_inputs(data_dir, batch_size):
  function inputs (line 224) | def inputs(eval_data):
  function _inputs (line 245) | def _inputs(eval_data, data_dir, batch_size):
  function maybe_download_and_extract (line 301) | def maybe_download_and_extract():
  function _generate_image_and_label_batch (line 321) | def _generate_image_and_label_batch(image, label, min_queue_examples,

FILE: ch9/cifar10_multi_gpu_train.py
  function _activation_summary (line 65) | def _activation_summary(x):
  function _variable_on_cpu (line 84) | def _variable_on_cpu(name, shape, initializer):
  function _variable_with_weight_decay (line 100) | def _variable_with_weight_decay(name, shape, stddev, wd):
  function inference (line 125) | def inference(images):
  function loss (line 210) | def loss(logits, labels):
  function tower_loss (line 233) | def tower_loss(scope, images, labels):
  function average_gradients (line 270) | def average_gradients(tower_grads):
  function train (line 308) | def train():
  function main (line 437) | def main(argv=None):  # pylint: disable=unused-argument