SYMBOL INDEX (284 symbols across 35 files)

FILE: causal_began/CausalBEGAN.py
  class CausalBEGAN (line 18) | class CausalBEGAN(object):
    method __init__ (line 31) | def __init__(self,batch_size,config):
    method __call__ (line 89) | def __call__(self, real_inputs, fake_inputs):
    method build_train_op (line 248) | def build_train_op(self):
    method train_step (line 286) | def train_step(self,sess,counter):
    method build_summary_op (line 292) | def build_summary_op(self):

FILE: causal_began/config.py
  function str2bool (line 4) | def str2bool(v):
  function add_argument_group (line 11) | def add_argument_group(name):
  function gpu_logic (line 100) | def gpu_logic(config):
  function get_config (line 111) | def get_config():

FILE: causal_began/models.py
  function lrelu (line 6) | def lrelu(x,leak=0.2,name='lrelu'):
  function GeneratorCNN (line 12) | def GeneratorCNN( z, config, reuse=None):
  function DiscriminatorCNN (line 35) | def DiscriminatorCNN(image, config, reuse=None):
  function Discriminator_labeler (line 80) | def Discriminator_labeler(image, output_size, config, reuse=None):
  function next (line 107) | def next(loader):
  function to_nhwc (line 110) | def to_nhwc(image, data_format):
  function to_nchw_numpy (line 118) | def to_nchw_numpy(image):
  function norm_img (line 125) | def norm_img(image, data_format=None):
  function denorm_img (line 131) | def denorm_img(norm, data_format):
  function slerp (line 134) | def slerp(val, low, high):
  function int_shape (line 142) | def int_shape(tensor):
  function get_conv_shape (line 146) | def get_conv_shape(tensor, data_format):
  function nchw_to_nhwc (line 154) | def nchw_to_nhwc(x):
  function nhwc_to_nchw (line 157) | def nhwc_to_nchw(x):
  function reshape (line 160) | def reshape(x, h, w, c, data_format):
  function resize_nearest_neighbor (line 167) | def resize_nearest_neighbor(x, new_size, data_format):
  function upscale (line 176) | def upscale(x, scale, data_format):
  function average_gradients (line 183) | def average_gradients(tower_grads):

FILE: causal_began/utils.py
  function make_summary (line 16) | def make_summary(name, val):
  function summary_stats (line 19) | def summary_stats(name,tensor,collections=None,hist=False):
  function prepare_dirs_and_logger (line 29) | def prepare_dirs_and_logger(config):
  function get_time (line 70) | def get_time():
  function save_config (line 73) | def save_config(config):
  function get_available_gpus (line 82) | def get_available_gpus():
  function distribute_input_data (line 87) | def distribute_input_data(data_loader,num_gpu):
  function rank (line 114) | def rank(array):
  function make_grid (line 117) | def make_grid(tensor, nrow=8, padding=2,
  function save_image (line 137) | def save_image(tensor, filename, nrow=8, padding=2,

FILE: causal_controller/ArrayDict.py
  class ArrayDict (line 2) | class ArrayDict(object):
    method __init__ (line 12) | def __init__(self):
    method __len__ (line 14) | def __len__(self):
    method __repr__ (line 19) | def __repr__(self):
    method keys (line 21) | def keys(self):
    method items (line 23) | def items(self):
    method validate_dict (line 26) | def validate_dict(self,a_dict):
    method arr_dict (line 49) | def arr_dict(self,a_dict):
    method concat (line 56) | def concat(self,a_dict):
    method __getitem__ (line 63) | def __getitem__(self,at):

FILE: causal_controller/CausalController.py
  class CausalController (line 14) | class CausalController(object):
    method summary_scalar (line 17) | def summary_scalar(self,name,ten):
    method summary_stats (line 19) | def summary_stats(self,name,ten,hist=False):
    method load (line 22) | def load(self,sess,path):
    method __init__ (line 35) | def __init__(self,batch_size,config):
    method build_pretrain (line 140) | def build_pretrain(self,label_loader):
    method dcc_var (line 212) | def dcc_var(self):
    method critic_update (line 222) | def critic_update(self,sess):
    method __len__ (line 228) | def __len__(self):
    method list_placeholders (line 232) | def list_placeholders(self):
    method list_labels (line 234) | def list_labels(self):
    method list_label_logits (line 236) | def list_label_logits(self):
    method do2feed (line 239) | def do2feed(self,do_dict):
    method sample_label (line 248) | def sample_label(self, sess, cond_dict=None,do_dict=None,N=None,verbos...
  class CausalNode (line 328) | class CausalNode(object):
    method summary_scalar (line 352) | def summary_scalar(self,name,ten):
    method summary_stats (line 354) | def summary_stats(self,name,ten,hist=False):
    method __init__ (line 357) | def __init__(self,name,config):
    method setup_tensor (line 370) | def setup_tensor(self):
    method var (line 396) | def var(self):
    method train_var (line 401) | def train_var(self):
    method label_logit (line 406) | def label_logit(self):
    method label (line 415) | def label(self):
    method setup_pretrain (line 423) | def setup_pretrain(self,config,label_loader,DCC):

FILE: causal_controller/config.py
  function str2bool (line 11) | def str2bool(v):
  function add_argument_group (line 18) | def add_argument_group(name):
  function get_config (line 111) | def get_config():

FILE: causal_controller/models.py
  function lrelu (line 6) | def lrelu(x,leak=0.2,name='lrelu'):
  function DiscriminatorW (line 14) | def DiscriminatorW(labels,batch_size, n_hidden, config, reuse=None):
  function Grad_Penalty (line 35) | def Grad_Penalty(real_data,fake_data,Discriminator,config):

FILE: causal_controller/utils.py
  function summary_stats (line 5) | def summary_stats(name,tensor,collections=None,hist=False):
  function did_succeed (line 14) | def did_succeed( output_dict, cond_dict ):

FILE: causal_dcgan/CausalGAN.py
  function norm_img (line 25) | def norm_img(image):
  function denorm_img (line 28) | def denorm_img(norm):
  function tf_truncexpon (line 31) | def tf_truncexpon(batch_size,rate,right):
  function add_texp_noise (line 50) | def add_texp_noise(batch_size,labels01):
  class CausalGAN (line 64) | class CausalGAN(object):
    method __init__ (line 67) | def __init__(self,batch_size,config):
    method __call__ (line 101) | def __call__(self, real_inputs, fake_inputs):
    method build_train_op (line 281) | def build_train_op(self):
    method build_summary_op (line 303) | def build_summary_op(self):
    method train_step (line 306) | def train_step(self,sess,counter):

FILE: causal_dcgan/config.py
  function str2bool (line 4) | def str2bool(v):
  function add_argument_group (line 10) | def add_argument_group(name):
  function get_config (line 154) | def get_config():

FILE: causal_dcgan/models.py
  function conv_out_size_same (line 11) | def conv_out_size_same(size, stride):
  function GeneratorCNN (line 14) | def GeneratorCNN( z, config, reuse=None):
  function DiscriminatorCNN (line 65) | def DiscriminatorCNN(image, config, reuse=None):
  function discriminator_labeler (line 125) | def discriminator_labeler(image, output_dim, config, reuse=None):
  function discriminator_gen_labeler (line 143) | def discriminator_gen_labeler(image, output_dim, config, reuse=None):
  function discriminator_on_z (line 161) | def discriminator_on_z(image, config, reuse=None):

FILE: causal_dcgan/ops.py
  class batch_norm (line 11) | class batch_norm(object):
    method __init__ (line 12) | def __init__(self, epsilon=1e-5, momentum = 0.9, name="batch_norm"):
    method __call__ (line 18) | def __call__(self, x, train=True):
  function conv_cond_concat (line 27) | def conv_cond_concat(x, y):
  function conv2d (line 49) | def conv2d(input_, output_dim,
  function deconv2d (line 63) | def deconv2d(input_, output_shape,
  function lrelu (line 84) | def lrelu(x,leak=0.2,name='lrelu'):
  function linear (line 94) | def linear(input_, output_size, scope=None, stddev=0.02, bias_start=0.0,...
  function add_minibatch_features (line 115) | def add_minibatch_features(image,df_dim):

FILE: causal_dcgan/utils.py
  function get_image (line 20) | def get_image(image_path, input_height, input_width,
  function save_images (line 27) | def save_images(images, size, image_path):
  function imread (line 30) | def imread(path, is_grayscale = False):
  function merge_images (line 36) | def merge_images(images, size):
  function merge (line 39) | def merge(images, size):
  function imsave (line 48) | def imsave(images, size, path):
  function center_crop (line 51) | def center_crop(x, crop_h, crop_w,
  function transform (line 61) | def transform(image, input_height, input_width,
  function inverse_transform (line 71) | def inverse_transform(images):
  function to_json (line 74) | def to_json(output_path, *layers):
  function make_gif (line 137) | def make_gif(images, fname, duration=2, true_image=False):

FILE: causal_graph.py
  function get_causal_graph (line 325) | def get_causal_graph(causal_model=None,*args,**kwargs):

FILE: config.py
  function str2bool (line 4) | def str2bool(v):
  function add_argument_group (line 11) | def add_argument_group(name):
  function gpu_logic (line 113) | def gpu_logic(config):
  function get_config (line 125) | def get_config():

FILE: data_loader.py
  function logodds (line 12) | def logodds(p):
  class DataLoader (line 15) | class DataLoader(object):
    method __init__ (line 24) | def __init__(self,label_names,config):
    method get_label_queue (line 56) | def get_label_queue(self,batch_size):
    method get_data_queue (line 80) | def get_data_queue(self,batch_size):

FILE: download.py
  function download_file_from_google_drive (line 13) | def download_file_from_google_drive(id, destination):
  function get_confirm_token (line 26) | def get_confirm_token(response):
  function save_response_content (line 32) | def save_response_content(response, destination, chunk_size=32*1024):
  function unzip (line 40) | def unzip(filepath):
  function download_celeb_a (line 47) | def download_celeb_a(base_path):
  function download_attr_file (line 74) | def download_attr_file(data_path):
  function prepare_data_dir (line 81) | def prepare_data_dir(path = './data'):
  function check_link (line 86) | def check_link(in_dir, basename, out_dir):
  function add_splits (line 93) | def add_splits(base_path):
  function delete_top_line (line 121) | def delete_top_line(txt_fname):

FILE: figure_scripts/distributions.py
  function get_pdf (line 16) | def get_pdf(model, do_dict=None,cond_dict=None,name='',N=6400,return_dis...
  function get_interv_table (line 45) | def get_interv_table(model,intrv=True):
  function record_interventional (line 71) | def record_interventional(model,step=''):

FILE: figure_scripts/encode.py
  function var_like_z (line 18) | def var_like_z(z_ten,name):
  function noise_like_z (line 21) | def noise_like_z(z_ten,name):
  class Encoder (line 27) | class Encoder:
    method __init__ (line 37) | def __init__(self,model,image,image_name=None,max_tr_steps=50000,load_...
    method init (line 187) | def init(self):
    method save (line 201) | def save(self, step=None):
    method train (line 212) | def train(self, n_step=None):

FILE: figure_scripts/high_level.py
  function fig1 (line 28) | def fig1(model, output_folder):

FILE: figure_scripts/pairwise.py
  function calc_tvd (line 17) | def calc_tvd(label_dict,attr):
  function crosstab (line 53) | def crosstab(model,result_dir=None,report_tvd=True,no_save=False,N=500000):

FILE: figure_scripts/sample.py
  function find_logit_percentile (line 23) | def find_logit_percentile(model, key, per):
  function fixed_label_diversity (line 33) | def fixed_label_diversity(model, config,step=''):
  function get_joint (line 58) | def get_joint(model, int_do_dict=None,int_cond_dict=None, N=6400,return_...
  function take_product (line 176) | def take_product(do_dict):
  function chunks (line 195) | def chunks(input_dict, chunk_size):
  function do2feed (line 218) | def do2feed( do_dict, model, on_logits=True):
  function cond2fetch (line 254) | def cond2fetch( cond_dict=None, model=None, on_logits=True):
  function interpret_dict (line 289) | def interpret_dict( a_dict, model,n_times=1, on_logits=True):
  function slice_dict (line 326) | def slice_dict(feed_dict, rows):
  function did_succeed (line 339) | def did_succeed( output_dict, cond_dict ):
  function sample (line 368) | def sample(model, cond_dict=None, do_dict=None, fetch_dict=None,N=None,
  function condition2d (line 614) | def condition2d( model, cond_dict,cond_dict_name,step='', on_logits=True):
  function intervention2d (line 753) | def intervention2d(model, fetch=None, do_dict=None, do_dict_name=None, o...

FILE: figure_scripts/utils.py
  function nhwc_to_nchw (line 28) | def nhwc_to_nchw(x):
  function to_nchw_numpy (line 30) | def to_nchw_numpy(image):
  function norm_img (line 37) | def norm_img(image, data_format=None):
  function nchw_to_nhwc (line 50) | def nchw_to_nhwc(x):
  function to_nhwc (line 52) | def to_nhwc(image, data_format):
  function denorm_img (line 58) | def denorm_img(norm, data_format):
  function read_prepared_uint8_image (line 62) | def read_prepared_uint8_image(img_path):
  function make_encode_dir (line 73) | def make_encode_dir(model,image_name):
  function make_sample_dir (line 85) | def make_sample_dir(model):
  function guess_model_step (line 98) | def guess_model_step(model):
  function infer_grid_image_shape (line 108) | def infer_grid_image_shape(N):
  function save_figure_images (line 116) | def save_figure_images(model_type, tensor, filename, size, padding=2, no...
  function make_grid (line 132) | def make_grid(tensor, nrow=8, padding=2,
  function began_save_image (line 152) | def began_save_image(tensor, filename, nrow=8, padding=2,
  function get_image (line 164) | def get_image(image_path, input_height, input_width,
  function dcgan_save_images (line 171) | def dcgan_save_images(images, size, image_path):
  function imread (line 174) | def imread(path, is_grayscale = False):
  function merge_images (line 180) | def merge_images(images, size):
  function merge (line 183) | def merge(images, size):
  function imsave (line 192) | def imsave(images, size, path):
  function center_crop (line 195) | def center_crop(x, crop_h, crop_w,
  function transform (line 205) | def transform(image, input_height, input_width,
  function inverse_transform (line 215) | def inverse_transform(images):

FILE: main.py
  function get_trainer (line 23) | def get_trainer():
  function main (line 77) | def main(trainer):

FILE: synthetic/collect_stats.py
  function makeplots (line 11) | def makeplots(x_iter,tvd_datastore,show=False,save=False,save_name=None):
  function make_individual_plots (line 69) | def make_individual_plots(x_iter,tvd_datastore,smooth=True,show=False,sa...

FILE: synthetic/config.py
  function str2bool (line 3) | def str2bool(v):
  function add_argument_group (line 12) | def add_argument_group(name):
  function get_config (line 59) | def get_config():

FILE: synthetic/main.py
  function get_trainer (line 18) | def get_trainer(config):
  function main (line 34) | def main(trainer,config):
  function get_model (line 41) | def get_model(config=None):

FILE: synthetic/models.py
  function sxe (line 7) | def sxe(logits,labels):
  function linear (line 15) | def linear(input_, output_dim, scope=None, stddev=.7):
  class Arrows (line 26) | class Arrows:
    method __init__ (line 30) | def __init__(self,N):
    method build (line 40) | def build(self):
    method normalize_output (line 43) | def normalize_output(self,X):
  class Generator (line 54) | class Generator:
    method __init__ (line 56) | def __init__(self, N, hidden_size=10,z_dim=10):
    method build (line 65) | def build(self):
    method smallNN (line 67) | def smallNN(self,inputs,name='smallNN'):
  function poly (line 82) | def poly(cause,cause2=None,cause3=None,name='poly1d',reuse=None):
  class CompleteArrows (line 147) | class CompleteArrows(Arrows): # Data generated from the causal graph X1-...
    method build (line 149) | def build(self):
  class CompleteGenerator (line 159) | class CompleteGenerator(Generator):
    method build (line 161) | def build(self):
  class ColliderArrows (line 171) | class ColliderArrows(Arrows):
    method build (line 173) | def build(self):
  class ColliderGenerator (line 181) | class ColliderGenerator(Generator):
    method build (line 183) | def build(self):
  class LinearArrows (line 192) | class LinearArrows(Arrows):
    method build (line 194) | def build(self):
  class LinearGenerator (line 203) | class LinearGenerator(Generator):
    method build (line 205) | def build(self):
  class NetworkArrows (line 214) | class NetworkArrows(Arrows):
    method build (line 216) | def build(self):
  class FC3_Generator (line 226) | class FC3_Generator(Generator):
    method build (line 228) | def build(self):
  class FC5_Generator (line 236) | class FC5_Generator(Generator):
    method build (line 238) | def build(self):
  class FC10_Generator (line 248) | class FC10_Generator(Generator):
    method build (line 250) | def build(self):
  function minibatch (line 266) | def minibatch(input_, num_kernels=5, kernel_dim=3):
  function Discriminator (line 275) | def Discriminator(input_, hidden_size,minibatch_layer=True,alpha=0.5,reu...

FILE: synthetic/tboard.py
  function file2number (line 6) | def file2number(fname):

FILE: synthetic/trainer.py
  class GAN (line 20) | class GAN(object):
    method __init__ (line 21) | def __init__(self,config,gan_type,data,parent_dir):
    method build_model (line 36) | def build_model(self):
    method build_summaries (line 62) | def build_summaries(self):
    method record_losses (line 72) | def record_losses(self,sess):
    method record_tvd (line 78) | def record_tvd(self,sess):
    method record_scatter (line 86) | def record_scatter(self,sess):
    method prepare_model_dir (line 129) | def prepare_model_dir(self):
    method prepare_logger (line 134) | def prepare_logger(self):
    method log_tvd (line 141) | def log_tvd(self,step,tvd,mvd):
  class Trainer (line 146) | class Trainer(object):
    method __init__ (line 147) | def __init__(self,config,data_type):
    method data_scatterplot (line 201) | def data_scatterplot(self):
    method build_model (line 210) | def build_model(self):
    method train (line 224) | def train(self):
    method prepare_model_dir (line 270) | def prepare_model_dir(self):

FILE: synthetic/utils.py
  function make_summary (line 19) | def make_summary(name, val):
  function summary_losses (line 22) | def summary_losses(sess,model,N=1000):
  function calc_tvd (line 28) | def calc_tvd(sess,Generator,Data,N=50000,nbins=10):
  function summary_stats (line 48) | def summary_stats(name,tensor,hist=False):
  function summary_scatterplots (line 56) | def summary_scatterplots(X1,X2,X3):
  function summary_scatter2d (line 66) | def summary_scatter2d(x,y,title='2dscatterplot',xlabel=None,ylabel=None):
  function scatter2d (line 80) | def scatter2d(x,y,title='2dscatterplot',xlabel=None,ylabel=None):
  function prepare_dirs_and_logger (line 101) | def prepare_dirs_and_logger(config):
  function get_time (line 142) | def get_time():
  function save_config (line 145) | def save_config(config):
  class Timer (line 156) | class Timer(object):
    method __init__ (line 157) | def __init__(self):
    method on (line 160) | def on(self):
    method off (line 162) | def off(self):
    method __str__ (line 165) | def __str__(self):

FILE: tboard.py
  function file2number (line 6) | def file2number(fname):

FILE: trainer.py
  class Trainer (line 15) | class Trainer(object):
    method __init__ (line 17) | def __init__(self, config, cc_config, model_config=None):
    method pretrain_loop (line 157) | def pretrain_loop(self,num_iter=None):
    method train_loop (line 238) | def train_loop(self,num_iter=None):
    method sample_label (line 270) | def sample_label(self, cond_dict=None, do_dict=None,N=None):
    method label_interpolation (line 275) | def label_interpolation(self,inputs=None,save_dir=None,ext='.pdf'):
    method causal_sampling (line 311) | def causal_sampling(self, img_shape ,ext='.pdf'):
    method sample_diversity (line 399) | def sample_diversity(self,save_dir=None,ext='.pdf'):

FILE: utils.py
  function make_summary (line 20) | def make_summary(name, val):
  function summary_stats (line 23) | def summary_stats(name,tensor,collections=None,hist=False):
  function prepare_dirs_and_logger (line 33) | def prepare_dirs_and_logger(config):
  function ignore_except (line 81) | def ignore_except(src,contents,allowed_dirs):
  function get_time (line 88) | def get_time():
  function save_configs (line 91) | def save_configs(config,cc_config,dcgan_config,began_config):
  function save_config (line 100) | def save_config(config,name="params.json",where=None):
  function get_available_gpus (line 109) | def get_available_gpus():
  function distribute_input_data (line 114) | def distribute_input_data(data_loader,num_gpu):
  function rank (line 140) | def rank(array):
  function make_grid (line 143) | def make_grid(tensor, nrow=8, padding=2,
  function save_image (line 164) | def save_image(tensor, filename, nrow=8, padding=2,