SYMBOL INDEX (147 symbols across 20 files)

FILE: inits.py
  function uniform (line 5) | def uniform(shape, scale=0.05, name=None):
  function glorot (line 11) | def glorot(shape, name=None):
  function zeros (line 18) | def zeros(shape, name=None):
  function ones (line 24) | def ones(shape, name=None):

FILE: lanczos.py
  function lanczos (line 8) | def lanczos(A,k,q):
  function dense_RandomSVD (line 36) | def dense_RandomSVD(A,K):

FILE: layers.py
  function get_layer_uid (line 11) | def get_layer_uid(layer_name=''):
  function sparse_dropout (line 21) | def sparse_dropout(x, keep_prob, noise_shape):
  function dot (line 30) | def dot(x, y, sparse=False):
  class Layer (line 39) | class Layer(object):
    method __init__ (line 54) | def __init__(self, **kwargs):
    method _call (line 68) | def _call(self, inputs):
    method __call__ (line 71) | def __call__(self, inputs):
    method _log_vars (line 80) | def _log_vars(self):
  class Dense (line 85) | class Dense(Layer):
    method __init__ (line 87) | def __init__(self, input_dim, output_dim, placeholders, dropout=0., sp...
    method _call (line 113) | def _call(self, inputs):
  class GraphConvolution (line 133) | class GraphConvolution(Layer):
    method __init__ (line 135) | def __init__(self, input_dim, output_dim, placeholders, dropout=0.,
    method _call (line 167) | def _call(self, inputs):
  class SampledGraphConvolution (line 201) | class SampledGraphConvolution(Layer):
    method __init__ (line 203) | def __init__(self, input_dim, output_dim, placeholders, dropout=0., ra...
    method _call (line 236) | def _call(self, inputs):

FILE: metrics.py
  function masked_softmax_cross_entropy (line 5) | def masked_softmax_cross_entropy(preds, labels, mask):
  function masked_accuracy (line 14) | def masked_accuracy(preds, labels, mask):
  function softmax_cross_entropy (line 24) | def softmax_cross_entropy(preds, labels):
  function accuracy (line 28) | def accuracy(preds, labels):

FILE: models.py
  class Model (line 8) | class Model(object):
    method __init__ (line 9) | def __init__(self, **kwargs):
    method _build (line 35) | def _build(self):
    method build (line 38) | def build(self):
    method predict (line 60) | def predict(self):
    method _loss (line 63) | def _loss(self):
    method _accuracy (line 66) | def _accuracy(self):
    method save (line 69) | def save(self, sess=None):
    method load (line 76) | def load(self, sess=None):
  class MLP (line 85) | class MLP(Model):
    method __init__ (line 86) | def __init__(self, placeholders, input_dim, **kwargs):
    method _loss (line 99) | def _loss(self):
    method _accuracy (line 108) | def _accuracy(self):
    method _build (line 112) | def _build(self):
    method predict (line 128) | def predict(self):
  class GCN (line 134) | class GCN(Model):
    method __init__ (line 135) | def __init__(self, placeholders, input_dim, **kwargs):
    method _loss (line 148) | def _loss(self):
    method _accuracy (line 157) | def _accuracy(self):
    method _build (line 161) | def _build(self):
    method predict (line 178) | def predict(self):
  class GCN_APPRO (line 183) | class GCN_APPRO(Model):
    method __init__ (line 184) | def __init__(self, placeholders, input_dim, **kwargs):
    method _loss (line 197) | def _loss(self):
    method _accuracy (line 205) | def _accuracy(self):
    method _build (line 208) | def _build(self):
    method predict (line 227) | def predict(self):
  class GCN_APPRO_Mix (line 231) | class GCN_APPRO_Mix(Model): #mixture of dense and gcn
    method __init__ (line 232) | def __init__(self, placeholders, input_dim, **kwargs):
    method _loss (line 245) | def _loss(self):
    method _accuracy (line 254) | def _accuracy(self):
    method _build (line 257) | def _build(self):
    method predict (line 274) | def predict(self):
  class GCN_APPRO_Onelayer (line 279) | class GCN_APPRO_Onelayer(Model):
    method __init__ (line 280) | def __init__(self, placeholders, input_dim, **kwargs):
    method _loss (line 293) | def _loss(self):
    method _accuracy (line 302) | def _accuracy(self):
    method _build (line 306) | def _build(self):
    method predict (line 317) | def predict(self):

FILE: pubmed-original_inductive_FastGCN.py
  function construct_feeddict_forMixlayers (line 31) | def construct_feeddict_forMixlayers(AXfeatures, support, labels, placeho...
  function iterate_minibatches_listinputs (line 39) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function main (line 53) | def main(rank1):

FILE: pubmed-original_transductive_FastGCN.py
  function construct_feeddict_forMixlayers (line 31) | def construct_feeddict_forMixlayers(AXfeatures, support, labels, placeho...
  function iterate_minibatches_listinputs (line 39) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function main (line 53) | def main(rank1):

FILE: pubmed_Mix.py
  function construct_feeddict_forMixlayers (line 31) | def construct_feeddict_forMixlayers(AXfeatures, support, labels, placeho...
  function iterate_minibatches_listinputs (line 39) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function main (line 53) | def main(rank1):

FILE: pubmed_Mix_sampleA.py
  function construct_feeddict_forMixlayers (line 31) | def construct_feeddict_forMixlayers(AXfeatures, support, labels, placeho...
  function iterate_minibatches_listinputs (line 39) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function main (line 53) | def main(rank1):

FILE: pubmed_Mix_uniform.py
  function construct_feeddict_forMixlayers (line 31) | def construct_feeddict_forMixlayers(AXfeatures, support, labels, placeho...
  function iterate_minibatches_listinputs (line 39) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function main (line 53) | def main(rank1):

FILE: pubmed_inductive_appr2layers.py
  function iterate_minibatches_listinputs (line 31) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function main (line 44) | def main(rank1, rank0):

FILE: train.py
  function evaluate (line 67) | def evaluate(features, support, labels, mask, placeholders):

FILE: train_batch_multiRank_inductive_newscheme.py
  function iterate_minibatches_listinputs (line 33) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function main (line 46) | def main(rank1, rank0):

FILE: train_batch_multiRank_inductive_reddit_Mixlayers_sampleA.py
  function iterate_minibatches_listinputs (line 35) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function loadRedditFromG (line 49) | def loadRedditFromG(dataset_dir, inputfile):
  function loadRedditFromNPZ (line 59) | def loadRedditFromNPZ(dataset_dir):
  function transferRedditDataFormat (line 67) | def transferRedditDataFormat(dataset_dir, output_file):
  function transferLabel2Onehot (line 99) | def transferLabel2Onehot(labels, N):
  function construct_feeddict_forMixlayers (line 106) | def construct_feeddict_forMixlayers(AXfeatures, support, labels, placeho...
  function main (line 114) | def main(rank1):
  function transferG2ADJ (line 271) | def transferG2ADJ():
  function test (line 286) | def test(rank1=None):

FILE: train_batch_multiRank_inductive_reddit_Mixlayers_sampleBatch.py
  function iterate_minibatches_listinputs (line 35) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function loadRedditFromG (line 49) | def loadRedditFromG(dataset_dir, inputfile):
  function loadRedditFromNPZ (line 59) | def loadRedditFromNPZ(dataset_dir):
  function transferRedditDataFormat (line 67) | def transferRedditDataFormat(dataset_dir, output_file):
  function transferLabel2Onehot (line 99) | def transferLabel2Onehot(labels, N):
  function construct_feeddict_forMixlayers (line 106) | def construct_feeddict_forMixlayers(AXfeatures, support, labels, placeho...
  function main (line 114) | def main(rank1):

FILE: train_batch_multiRank_inductive_reddit_Mixlayers_uniform.py
  function iterate_minibatches_listinputs (line 35) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function loadRedditFromG (line 49) | def loadRedditFromG(dataset_dir, inputfile):
  function loadRedditFromNPZ (line 59) | def loadRedditFromNPZ(dataset_dir):
  function transferRedditDataFormat (line 67) | def transferRedditDataFormat(dataset_dir, output_file):
  function transferLabel2Onehot (line 99) | def transferLabel2Onehot(labels, N):
  function construct_feeddict_forMixlayers (line 106) | def construct_feeddict_forMixlayers(AXfeatures, support, labels, placeho...
  function main (line 114) | def main(rank1):
  function transferG2ADJ (line 256) | def transferG2ADJ():

FILE: train_batch_multiRank_inductive_reddit_appr2layers.py
  function iterate_minibatches_listinputs (line 35) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function loadRedditFromG (line 49) | def loadRedditFromG(dataset_dir, inputfile):
  function loadRedditFromNPZ (line 59) | def loadRedditFromNPZ(dataset_dir):
  function transferRedditDataFormat (line 67) | def transferRedditDataFormat(dataset_dir, output_file):
  function transferLabel2Onehot (line 99) | def transferLabel2Onehot(labels, N):
  function main (line 106) | def main(rank1, rank0):
  function transferG2ADJ (line 264) | def transferG2ADJ():

FILE: train_batch_multiRank_inductive_reddit_onelayer.py
  function iterate_minibatches_listinputs (line 35) | def iterate_minibatches_listinputs(inputs, batchsize, shuffle=False):
  function loadRedditFromG (line 49) | def loadRedditFromG(dataset_dir, inputfile):
  function loadRedditFromNPZ (line 59) | def loadRedditFromNPZ(dataset_dir):
  function transferRedditDataFormat (line 67) | def transferRedditDataFormat(dataset_dir, output_file):
  function transferLabel2Onehot (line 99) | def transferLabel2Onehot(labels, N):
  function run_regression (line 108) | def run_regression(train_embeds, train_labels, test_embeds, test_labels):
  function main (line 124) | def main(rank1):
  function transferG2ADJ (line 260) | def transferG2ADJ():
  function original (line 275) | def original():

FILE: transformRedditGraph2NPZ.py
  function loadRedditFromG (line 12) | def loadRedditFromG(dataset_dir, inputfile):
  function loadRedditFromNPZ (line 22) | def loadRedditFromNPZ(dataset_dir):
  function transferRedditData2AdjNPZ (line 29) | def transferRedditData2AdjNPZ(dataset_dir):
  function transferRedditDataFormat (line 42) | def transferRedditDataFormat(dataset_dir, output_file):

FILE: utils.py
  function parse_index_file (line 12) | def parse_index_file(filename):
  function sample_mask (line 20) | def sample_mask(idx, l):
  function load_data (line 86) | def load_data(dataset_str):
  function load_data_original (line 136) | def load_data_original(dataset_str):
  function sparse_to_tuple (line 187) | def sparse_to_tuple(sparse_mx):
  function nontuple_preprocess_features (line 206) | def nontuple_preprocess_features(features):
  function preprocess_features (line 216) | def preprocess_features(features):
  function normalize_adj (line 226) | def normalize_adj(adj):
  function nontuple_preprocess_adj (line 235) | def nontuple_preprocess_adj(adj):
  function column_prop (line 240) | def column_prop(adj):
  function mix_prop (line 246) | def mix_prop(adj, features, sparseinputs=False):
  function preprocess_adj (line 258) | def preprocess_adj(adj):
  function dense_lanczos (line 280) | def dense_lanczos(A,K):
  function sparse_lanczos (line 286) | def sparse_lanczos(A,k):
  function dense_RandomSVD (line 316) | def dense_RandomSVD(A,K):
  function construct_feed_dict (line 324) | def construct_feed_dict(features, support, labels, labels_mask, placehol...
  function chebyshev_polynomials (line 335) | def chebyshev_polynomials(adj, k):