SYMBOL INDEX (288 symbols across 31 files)

FILE: data/data_generators/cifar_generator.py
  function download (line 35) | def download(v100):
  function maybe_download (line 50) | def maybe_download(files, v100):
  function read_files (line 59) | def read_files(files, v100):
  function cifar_generator (line 86) | def cifar_generator(v100, mode):
  function generate (line 120) | def generate(train_name, eval_name, test_name, hparams):

FILE: data/data_generators/generator_utils.py
  function to_example (line 12) | def to_example(dictionary):
  function generate_files (line 28) | def generate_files(generator,

FILE: data/data_generators/mnist_generator.py
  function download_files (line 25) | def download_files(filenames):
  function read_images (line 43) | def read_images(filepath, num_images):
  function read_labels (line 52) | def read_labels(filepath, num_labels):
  function mnist_generator (line 60) | def mnist_generator(mode):
  function generate (line 96) | def generate(train_name, eval_name, test_name, hparams):

FILE: data/dataset_maps.py
  function register (line 7) | def register(fn):
  function get_augmentation (line 13) | def get_augmentation(name, params, training):
  function cifar_augmentation (line 23) | def cifar_augmentation(image, label, training, params):
  function imagenet_augmentation (line 40) | def imagenet_augmentation(image, label, training, params):
  function load_images (line 55) | def load_images(example, training, params):
  function set_shapes (line 72) | def set_shapes(image, label, training, params):
  function transpose (line 76) | def transpose(image, label, training, params):

FILE: data/image_reader.py
  function image_reader (line 13) | def image_reader(data_sources, hparams, training):
  function mnist_simple (line 53) | def mnist_simple(data_source, params, training):
  function fashion (line 77) | def fashion(data_source, params, training):

FILE: data/imagenet_augs.py
  function _crop (line 10) | def _crop(image, offset_height, offset_width, crop_height, crop_width):
  function distorted_bounding_box_crop (line 48) | def distorted_bounding_box_crop(image,
  function _random_crop (line 104) | def _random_crop(image, size):
  function _flip (line 123) | def _flip(image):
  function _at_least_x_are_true (line 129) | def _at_least_x_are_true(a, b, x):
  function _do_scale (line 136) | def _do_scale(image, size):
  function _center_crop (line 147) | def _center_crop(image, size):
  function _normalize (line 158) | def _normalize(image):
  function preprocess_for_train (line 168) | def preprocess_for_train(image, image_size=224):
  function preprocess_for_eval (line 183) | def preprocess_for_eval(image, image_size=224):

FILE: data/registry.py
  function register (line 9) | def register(name, generator):
  function get_input_fns (line 21) | def get_input_fns(hparams, generate=True):
  function get_dataset (line 50) | def get_dataset(hparams):
  function maybe_generate (line 60) | def maybe_generate(check_path, hparams):

FILE: hparams/basic.py
  function mnist_basic_no_dropout (line 9) | def mnist_basic_no_dropout():
  function mnist_basic_trgtd_dropout (line 31) | def mnist_basic_trgtd_dropout():
  function mnist_basic_untrgtd_dropout (line 41) | def mnist_basic_untrgtd_dropout():
  function mnist_basic_trgtd_dropout_random (line 50) | def mnist_basic_trgtd_dropout_random():
  function mnist_basic_trgtd_unit_dropout (line 60) | def mnist_basic_trgtd_unit_dropout():
  function mnist_basic_smallify_dropout_1eneg4 (line 70) | def mnist_basic_smallify_dropout_1eneg4():
  function mnist_basic_smallify_dropout_1eneg3 (line 81) | def mnist_basic_smallify_dropout_1eneg3():
  function mnist_basic_smallify_weight_dropout_1eneg4 (line 89) | def mnist_basic_smallify_weight_dropout_1eneg4():
  function cifar10_basic_no_dropout (line 100) | def cifar10_basic_no_dropout():
  function cifar100_basic_no_dropout (line 123) | def cifar100_basic_no_dropout():
  function imagenet32_basic (line 131) | def imagenet32_basic():

FILE: hparams/defaults.py
  function default (line 8) | def default():
  function default_cifar10 (line 64) | def default_cifar10():
  function default_cifar100 (line 79) | def default_cifar100():
  function default_imagenet299 (line 89) | def default_imagenet299():
  function default_imagenet224 (line 104) | def default_imagenet224():
  function default_imagenet64 (line 112) | def default_imagenet64():
  function default_imagenet32 (line 120) | def default_imagenet32():

FILE: hparams/lenet.py
  function cifar_lenet (line 10) | def cifar_lenet():
  function cifar_lenet_no_dropout (line 39) | def cifar_lenet_no_dropout():
  function cifar_lenet_weight (line 45) | def cifar_lenet_weight():
  function cifar_lenet_trgtd_weight (line 53) | def cifar_lenet_trgtd_weight():
  function cifar_lenet_unit (line 62) | def cifar_lenet_unit():
  function cifar_lenet_trgtd_unit (line 70) | def cifar_lenet_trgtd_unit():
  function cifar_lenet_l1 (line 79) | def cifar_lenet_l1():
  function cifar_lenet_trgtd_weight_l1 (line 86) | def cifar_lenet_trgtd_weight_l1():
  function cifar_lenet_trgtd_unit_l1 (line 96) | def cifar_lenet_trgtd_unit_l1():
  function cifar_lenet_trgtd_unit_botk75_33 (line 106) | def cifar_lenet_trgtd_unit_botk75_33():
  function cifar_lenet_trgtd_unit_botk75_66 (line 115) | def cifar_lenet_trgtd_unit_botk75_66():
  function cifar_lenet_trgtd_weight_botk75_33 (line 124) | def cifar_lenet_trgtd_weight_botk75_33():
  function cifar_lenet_trgtd_weight_botk75_66 (line 133) | def cifar_lenet_trgtd_weight_botk75_66():
  function cifar_lenet_louizos_weight_1en3 (line 142) | def cifar_lenet_louizos_weight_1en3():
  function cifar_lenet_louizos_weight_1en1 (line 154) | def cifar_lenet_louizos_weight_1en1():
  function cifar_lenet_louizos_weight_1en2 (line 166) | def cifar_lenet_louizos_weight_1en2():
  function cifar_lenet_louizos_weight_5en3 (line 178) | def cifar_lenet_louizos_weight_5en3():
  function cifar_lenet_louizos_weight_1en4 (line 190) | def cifar_lenet_louizos_weight_1en4():
  function cifar_lenet_louizos_unit_1en3 (line 202) | def cifar_lenet_louizos_unit_1en3():
  function cifar_lenet_louizos_unit_1en1 (line 214) | def cifar_lenet_louizos_unit_1en1():
  function cifar_lenet_louizos_unit_1en2 (line 226) | def cifar_lenet_louizos_unit_1en2():
  function cifar_lenet_louizos_unit_5en3 (line 238) | def cifar_lenet_louizos_unit_5en3():
  function cifar_lenet_louizos_unit_1en4 (line 250) | def cifar_lenet_louizos_unit_1en4():
  function cifar_lenet_variational (line 262) | def cifar_lenet_variational():
  function cifar_lenet_variational_unscaled (line 272) | def cifar_lenet_variational_unscaled():
  function cifar_lenet_variational_unit (line 281) | def cifar_lenet_variational_unit():
  function cifar_lenet_variational_unit_unscaled (line 291) | def cifar_lenet_variational_unit_unscaled():
  function cifar_lenet_smallify_neg4 (line 300) | def cifar_lenet_smallify_neg4():

FILE: hparams/registry.py
  function register (line 6) | def register(fn):
  function get_hparams (line 12) | def get_hparams(hparams_list):

FILE: hparams/resnet.py
  function resnet_default (line 9) | def resnet_default():
  function resnet102_imagenet224 (line 24) | def resnet102_imagenet224():
  function resnet102_imagenet64 (line 44) | def resnet102_imagenet64():
  function resnet50_imagenet224 (line 51) | def resnet50_imagenet224():
  function resnet34_imagenet224 (line 58) | def resnet34_imagenet224():
  function resnet_cifar100 (line 65) | def resnet_cifar100():
  function cifar10_resnet32 (line 72) | def cifar10_resnet32():
  function cifar10_resnet32_no_dropout (line 79) | def cifar10_resnet32_no_dropout():
  function cifar10_resnet32_trgtd_weight (line 87) | def cifar10_resnet32_trgtd_weight():
  function cifar10_resnet32_weight (line 97) | def cifar10_resnet32_weight():
  function cifar10_resnet32_weight_50 (line 106) | def cifar10_resnet32_weight_50():
  function cifar10_resnet32_trgtd_unit (line 114) | def cifar10_resnet32_trgtd_unit():
  function cifar10_resnet32_trgtd_ard (line 124) | def cifar10_resnet32_trgtd_ard():
  function cifar10_resnet32_unit (line 134) | def cifar10_resnet32_unit():
  function cifar10_resnet32_unit_50 (line 143) | def cifar10_resnet32_unit_50():
  function cifar10_resnet32_l1_1eneg3 (line 151) | def cifar10_resnet32_l1_1eneg3():
  function cifar10_resnet32_l1_1eneg2 (line 159) | def cifar10_resnet32_l1_1eneg2():
  function cifar10_resnet32_l1_1eneg1 (line 167) | def cifar10_resnet32_l1_1eneg1():
  function cifar10_resnet32_trgted_weight_l1 (line 175) | def cifar10_resnet32_trgted_weight_l1():
  function cifar10_resnet32_targeted_unit_l1 (line 186) | def cifar10_resnet32_targeted_unit_l1():
  function cifar10_resnet32_trgtd_unit_botk75_33 (line 197) | def cifar10_resnet32_trgtd_unit_botk75_33():
  function cifar10_resnet32_trgtd_unit_botk75_66 (line 207) | def cifar10_resnet32_trgtd_unit_botk75_66():
  function cifar10_resnet32_trgtd_weight_botk75_33 (line 217) | def cifar10_resnet32_trgtd_weight_botk75_33():
  function cifar10_resnet32_trgtd_weight_botk75_66 (line 227) | def cifar10_resnet32_trgtd_weight_botk75_66():
  function cifar10_resnet32_trgtd_unit_ramping_botk90_99 (line 237) | def cifar10_resnet32_trgtd_unit_ramping_botk90_99():
  function cifar10_resnet32_trgtd_weight_ramping_botk99_99 (line 247) | def cifar10_resnet32_trgtd_weight_ramping_botk99_99():
  function cifar10_resnet32_louizos_weight_1en3 (line 258) | def cifar10_resnet32_louizos_weight_1en3():
  function cifar10_resnet32_louizos_weight_1en1 (line 271) | def cifar10_resnet32_louizos_weight_1en1():
  function cifar10_resnet32_louizos_weight_1en2 (line 280) | def cifar10_resnet32_louizos_weight_1en2():
  function cifar10_resnet32_louizos_weight_5en3 (line 288) | def cifar10_resnet32_louizos_weight_5en3():
  function cifar10_resnet32_louizos_weight_1en4 (line 296) | def cifar10_resnet32_louizos_weight_1en4():
  function cifar10_resnet32_louizos_unit_1en3 (line 304) | def cifar10_resnet32_louizos_unit_1en3():
  function cifar10_resnet32_louizos_unit_1en1 (line 317) | def cifar10_resnet32_louizos_unit_1en1():
  function cifar10_resnet32_louizos_unit_1en2 (line 325) | def cifar10_resnet32_louizos_unit_1en2():
  function cifar10_resnet32_louizos_unit_5en3 (line 333) | def cifar10_resnet32_louizos_unit_5en3():
  function cifar10_resnet32_louizos_unit_1en4 (line 341) | def cifar10_resnet32_louizos_unit_1en4():
  function cifar10_resnet32_louizos_unit_1en5 (line 349) | def cifar10_resnet32_louizos_unit_1en5():
  function cifar10_resnet32_louizos_unit_1en6 (line 357) | def cifar10_resnet32_louizos_unit_1en6():
  function cifar10_resnet32_variational_weight (line 365) | def cifar10_resnet32_variational_weight():
  function cifar10_resnet32_variational_weight_unscaled (line 377) | def cifar10_resnet32_variational_weight_unscaled():
  function cifar10_resnet32_variational_unit (line 389) | def cifar10_resnet32_variational_unit():
  function cifar10_resnet32_variational_unit_unscaled (line 401) | def cifar10_resnet32_variational_unit_unscaled():
  function cifar10_resnet32_smallify_1eneg4 (line 413) | def cifar10_resnet32_smallify_1eneg4():
  function cifar10_resnet32_smallify_1eneg3 (line 424) | def cifar10_resnet32_smallify_1eneg3():
  function cifar10_resnet32_smallify_1eneg5 (line 432) | def cifar10_resnet32_smallify_1eneg5():
  function cifar10_resnet32_smallify_1eneg6 (line 440) | def cifar10_resnet32_smallify_1eneg6():
  function cifar10_resnet32_smallify_weight_1eneg4 (line 448) | def cifar10_resnet32_smallify_weight_1eneg4():
  function cifar10_resnet32_smallify_weight_1eneg3 (line 459) | def cifar10_resnet32_smallify_weight_1eneg3():
  function cifar10_resnet32_smallify_weight_1eneg5 (line 467) | def cifar10_resnet32_smallify_weight_1eneg5():
  function cifar10_resnet32_smallify_weight_1eneg6 (line 475) | def cifar10_resnet32_smallify_weight_1eneg6():

FILE: hparams/utils.py
  class HParams (line 4) | class HParams(tf.contrib.training.HParams):
    method __setattr__ (line 13) | def __setattr__(self, name, value):

FILE: hparams/vgg.py
  function vgg16_default (line 9) | def vgg16_default():
  function cifar10_vgg16 (line 27) | def cifar10_vgg16():
  function cifar100_vgg16_no_dropout (line 34) | def cifar100_vgg16_no_dropout():
  function cifar10_vgg16_no_dropout (line 47) | def cifar10_vgg16_no_dropout():
  function cifar100_vgg16_targeted_dropout (line 60) | def cifar100_vgg16_targeted_dropout():
  function cifar100_vgg16_untargeted_dropout (line 69) | def cifar100_vgg16_untargeted_dropout():
  function cifar100_vgg16_untargeted_unit_dropout (line 77) | def cifar100_vgg16_untargeted_unit_dropout():
  function cifar100_vgg16_targeted_unit_dropout (line 85) | def cifar100_vgg16_targeted_unit_dropout():
  function cifar100_vgg16_targeted_unit_dropout_botk75_66 (line 94) | def cifar100_vgg16_targeted_unit_dropout_botk75_66():
  function cifar100_vgg16_louizos_unit (line 102) | def cifar100_vgg16_louizos_unit():
  function cifar100_vgg16_louizos_weight (line 115) | def cifar100_vgg16_louizos_weight():
  function cifar100_vgg16_variational_unscaled (line 123) | def cifar100_vgg16_variational_unscaled():
  function cifar100_vgg16_variational (line 135) | def cifar100_vgg16_variational():
  function cifar100_vgg16_variational_unit_unscaled (line 143) | def cifar100_vgg16_variational_unit_unscaled():
  function cifar100_vgg16_variational_unit (line 151) | def cifar100_vgg16_variational_unit():
  function cifar100_vgg16_smallify_1eneg4 (line 159) | def cifar100_vgg16_smallify_1eneg4():
  function cifar100_vgg16_smallify_weight_1eneg5 (line 170) | def cifar100_vgg16_smallify_weight_1eneg5():

FILE: models/basic/basic.py
  function get_basic (line 12) | def get_basic(params, lr):

FILE: models/lenet/lenet.py
  function get_lenet (line 13) | def get_lenet(hparams, lr):

FILE: models/registry.py
  function register (line 8) | def register(name):
  function get_model (line 18) | def get_model(hparams):

FILE: models/resnet/resnet.py
  function get_resnet (line 15) | def get_resnet(hparams, lr):

FILE: models/utils/activations.py
  function register (line 6) | def register(name):
  function get_activation (line 16) | def get_activation(params):
  function relu (line 21) | def relu(params):
  function brelu (line 26) | def brelu(params):
  function selu (line 42) | def selu(params):
  function elu (line 47) | def elu(params):
  function sigmoid (line 52) | def sigmoid(params):
  function swish (line 57) | def swish(params):
  function tanh (line 62) | def tanh(params):

FILE: models/utils/dropouts.py
  function register (line 7) | def register(name):
  function get_dropout (line 17) | def get_dropout(name):
  function targeted_weight_dropout (line 23) | def targeted_weight_dropout(w, params, is_training):
  function targeted_weight_random (line 47) | def targeted_weight_random(w, params, is_training):
  function ramping_targeted_weight_random (line 75) | def ramping_targeted_weight_random(w, params, is_training):
  function targeted_weight_piecewise_dropout (line 109) | def targeted_weight_piecewise_dropout(w, params, is_training):
  function targeted_unit_piecewise (line 142) | def targeted_unit_piecewise(w, params, is_training):
  function delayed_targeted_weight (line 176) | def delayed_targeted_weight(w, params, is_training):
  function delayed_targeted_unit (line 193) | def delayed_targeted_unit(x, params, is_training):
  function untargeted_weight (line 210) | def untargeted_weight(w, params, is_training):
  function targeted_unit_dropout (line 217) | def targeted_unit_dropout(x, params, is_training):
  function targeted_unit_random (line 241) | def targeted_unit_random(w, params, is_training):
  function targeted_ard_dropout (line 269) | def targeted_ard_dropout(w, x, params, is_training):
  function unit_dropout (line 291) | def unit_dropout(w, params, is_training):
  function louizos_weight_dropout (line 303) | def louizos_weight_dropout(w, params, is_training):
  function louizos_unit_dropout (line 327) | def louizos_unit_dropout(w, params, is_training):
  function log_sigma2_variable (line 352) | def log_sigma2_variable(shape, ard_init=-10.):
  function get_log_alpha (line 358) | def get_log_alpha(log_sigma2, w):
  function paranoid_log (line 364) | def paranoid_log(x, eps=1e-8):
  function clip (line 370) | def clip(x):
  function dkl_qp (line 374) | def dkl_qp(log_alpha):
  function variational_dropout (line 383) | def variational_dropout(w, _, is_training):
  function variational_unit_dropout (line 396) | def variational_unit_dropout(w, _, is_training):
  function smallify_dropout (line 411) | def smallify_dropout(x, hparams, is_training):
  function smallify_weight_dropout (line 453) | def smallify_weight_dropout(x, hparams, is_training):

FILE: models/utils/initializations.py
  function register (line 6) | def register(name):
  function get_init (line 16) | def get_init(params):
  function normal (line 21) | def normal(params):
  function constant (line 26) | def constant(params):
  function uniform_unit_scaling (line 31) | def uniform_unit_scaling(params):
  function glorot_normal_initializer (line 36) | def glorot_normal_initializer(params):
  function glorot_uniform_initializer (line 41) | def glorot_uniform_initializer(params):
  function variance_scaling_initializer (line 46) | def variance_scaling_initializer(params):
  class RandomUnitScaling (line 50) | class RandomUnitScaling(tf.keras.initializers.Initializer):
    method __call__ (line 52) | def __call__(self, shape, dtype=None, partition_info=None):
  class RandomHadamardConstant (line 63) | class RandomHadamardConstant(tf.keras.initializers.Initializer):
    method __call__ (line 65) | def __call__(self, shape, dtype=None, partition_info=None):
  class RandomHadamardUnscaled (line 73) | class RandomHadamardUnscaled(tf.keras.initializers.Initializer):
    method __call__ (line 75) | def __call__(self, shape, dtype=None, partition_info=None):
  class RandomWarpedUniform (line 79) | class RandomWarpedUniform(tf.keras.initializers.Initializer):
    method __init__ (line 81) | def __init__(self, k=2):
    method __call__ (line 84) | def __call__(self, shape, dtype=None, partition_info=None):
  function warped_unif (line 100) | def warped_unif(params):
  function unit_scaling (line 105) | def unit_scaling(params):
  function hadamard_constant (line 110) | def hadamard_constant(params):
  function hadamard_unscaled (line 115) | def hadamard_unscaled(params):

FILE: models/utils/model_utils.py
  class ModeKeys (line 12) | class ModeKeys(object):
  function collect_vars (line 20) | def collect_vars(fn):
  function dense (line 38) | def dense(x, units, hparams, is_training, dropout=True):
  function conv (line 54) | def conv(x,
  function weight_decay_and_noise (line 123) | def weight_decay_and_noise(loss, hparams, learning_rate, var_list=None):
  function weight_noise (line 136) | def weight_noise(hparams, learning_rate):
  function weight_decay (line 156) | def weight_decay(hparams):
  function axis_aligned_cost (line 177) | def axis_aligned_cost(logits, hparams):
  function ard_cost (line 199) | def ard_cost():
  function shape_list (line 214) | def shape_list(x):
  function standardize_images (line 233) | def standardize_images(x):
  function batch_norm (line 247) | def batch_norm(inputs, hparams, training):
  function louizos_complexity_cost (line 267) | def louizos_complexity_cost(params):
  function switch_loss (line 302) | def switch_loss():
  function nonzero_count (line 313) | def nonzero_count():
  function percent_sparsity (line 324) | def percent_sparsity():
  function convert (line 337) | def convert(num, base, length=None):
  function equal_mult (line 357) | def equal_mult(size, num_branches):
  function uniform (line 364) | def uniform(size, num_branches):
  function bernoulli (line 371) | def bernoulli(size, num_branches):
  function combine (line 379) | def combine(rand_uniform, rand_bernoulli, num_branches):
  function model_top (line 386) | def model_top(labels, preds, cost, lr, mode, hparams):

FILE: models/utils/optimizers.py
  function register (line 6) | def register(name):
  function get_optimizer (line 16) | def get_optimizer(lr, params):
  function sgd (line 24) | def sgd(lr, params):
  function adam (line 29) | def adam(lr, params):
  function adagrad (line 34) | def adagrad(lr, params):
  function momentum (line 39) | def momentum(lr, params):

FILE: models/vgg/vgg.py
  function metric_fn (line 17) | def metric_fn(labels, predictions):
  function get_vgg (line 27) | def get_vgg(hparams, lr):

FILE: scripts/prune/eval.py
  function init_flags (line 12) | def init_flags():
  function eval_model (line 39) | def eval_model(FLAGS, hparam_name):
  function _run (line 105) | def _run(FLAGS):

FILE: scripts/prune/prune.py
  function register (line 9) | def register(fn):
  function get_prune_fn (line 15) | def get_prune_fn(name):
  function weight (line 20) | def weight(mode, k=0.5):
  function unit (line 75) | def unit(mode, k=0.5):
  function ard (line 108) | def ard(k=0.5):
  function prune_weights (line 126) | def prune_weights(prune_fn,
  function get_louizos_masks (line 171) | def get_louizos_masks(sess, weights):
  function get_smallify_masks (line 183) | def get_smallify_masks(sess, weights):
  function is_prunable_weight (line 199) | def is_prunable_weight(weight):
  function get_current_weights (line 215) | def get_current_weights(sess):
  function prune_sess_weights (line 235) | def prune_sess_weights(sess, prune_percent, FLAGS, hparams):

FILE: train.py
  function init_flags (line 21) | def init_flags():
  function init_random_seeds (line 57) | def init_random_seeds():
  function init_model (line 63) | def init_model(hparams_name):
  function construct_estimator (line 88) | def construct_estimator(model_fn, hparams, tpu=None):
  function _run (line 124) | def _run(hparams_name):
  function main (line 182) | def main(_):

FILE: training/envs.py
  function register (line 4) | def register(cls):
  function get_env (line 10) | def get_env(name):
  class GCP (line 15) | class GCP(object):
  class TPU (line 21) | class TPU(object):
  class Local (line 27) | class Local(object):

FILE: training/flags.py
  function validate_flags (line 10) | def validate_flags(FLAGS):
  function update_hparams (line 23) | def update_hparams(FLAGS, hparams, hparams_name):

FILE: training/lr_schemes.py
  function register (line 6) | def register(name):
  function get_lr (line 16) | def get_lr(params):
  function constant (line 22) | def constant(gs, params):
  function exponential_decay (line 27) | def exponential_decay(gs, params, delay=0):
  function linear_decay (line 38) | def linear_decay(gs, params, delay=0):
  function delayed_exponential_decay (line 46) | def delayed_exponential_decay(gs, params):
  function delayed_linear_decay (line 54) | def delayed_linear_decay(gs, params):
  function warmup_resnet (line 62) | def warmup_resnet(gs, params):
  function resnet (line 79) | def resnet(gs, params):
  function lenet (line 93) | def lenet(gs, _):
  function stepped_lr (line 100) | def stepped_lr(gs, params):
  function warmup_linear_decay (line 108) | def warmup_linear_decay(gs, params):
  function warmup_constant (line 120) | def warmup_constant(gs, params):
  function warmup_exponential_decay (line 131) | def warmup_exponential_decay(gs, params):
  function warmup_cosine (line 144) | def warmup_cosine(gs, params):
  function cosine_annealing (line 163) | def cosine_annealing(gs, params):

FILE: training/tpu.py
  function remove_summaries (line 7) | def remove_summaries():
  function create_host_call (line 15) | def create_host_call(model_dir):