SYMBOL INDEX (290 symbols across 49 files)

FILE: data/clevr/clevr_extract_feat.py
  function build_model (line 23) | def build_model(args):
  function batch_feat (line 44) | def batch_feat(cur_batch, model):
  function extract_feature (line 59) | def extract_feature(args, images_path, feats_npz_path):

FILE: data/gqa/gqa_feat_preproc.py
  function process_spatial_features (line 20) | def process_spatial_features(feat_path, out_path):
  function process_object_features (line 58) | def process_object_features(feat_path, out_path):

FILE: docs/_source/conf.py
  function setup (line 89) | def setup(app):

FILE: openvqa/core/base_cfgs.py
  class BaseCfgs (line 12) | class BaseCfgs(PATH):
    method __init__ (line 13) | def __init__(self):
    method str_to_bool (line 181) | def str_to_bool(self, args):
    method parse_to_dict (line 197) | def parse_to_dict(self, args):
    method add_args (line 207) | def add_args(self, args_dict):
    method proc (line 212) | def proc(self):
    method __str__ (line 319) | def __str__(self):

FILE: openvqa/core/base_dataset.py
  class BaseDataSet (line 12) | class BaseDataSet(Data.Dataset):
    method __init__ (line 13) | def __init__(self):
    method load_ques_ans (line 24) | def load_ques_ans(self, idx):
    method load_img_feats (line 28) | def load_img_feats(self, idx, iid):
    method __getitem__ (line 32) | def __getitem__(self, idx):
    method __len__ (line 46) | def __len__(self):
    method shuffle_list (line 49) | def shuffle_list(self, list):
  class BaseAdapter (line 53) | class BaseAdapter(nn.Module):
    method __init__ (line 54) | def __init__(self, __C):
    method vqa_init (line 71) | def vqa_init(self, __C):
    method gqa_init (line 74) | def gqa_init(self, __C):
    method clevr_init (line 77) | def clevr_init(self, __C):
    method forward (line 80) | def forward(self, frcn_feat, grid_feat, bbox_feat):
    method vqa_forward (line 95) | def vqa_forward(self, feat_dict):
    method gqa_forward (line 98) | def gqa_forward(self, feat_dict):
    method clevr_forward (line 101) | def clevr_forward(self, feat_dict):

FILE: openvqa/core/path_cfgs.py
  class PATH (line 8) | class PATH:
    method __init__ (line 9) | def __init__(self):
    method init_path (line 14) | def init_path(self):
    method check_path (line 116) | def check_path(self, dataset=None):

FILE: openvqa/datasets/clevr/clevr_loader.py
  class DataSet (line 12) | class DataSet(BaseDataSet):
    method __init__ (line 13) | def __init__(self, __C):
    method img_feat_path_load (line 79) | def img_feat_path_load(self, path_list):
    method tokenize (line 89) | def tokenize(self, stat_ques_list, use_glove):
    method ans_stat (line 126) | def ans_stat(self, stat_ans_list):
    method load_ques_ans (line 145) | def load_ques_ans(self, idx):
    method load_img_feats (line 162) | def load_img_feats(self, idx, iid):
    method proc_ques (line 174) | def proc_ques(self, ques, token_to_ix, max_token):
    method proc_ans (line 195) | def proc_ans(self, ans, ans_to_ix):

FILE: openvqa/datasets/clevr/eval/result_eval.py
  function eval (line 11) | def eval(__C, dataset, ans_ix_list, pred_list, result_eval_file, ensembl...

FILE: openvqa/datasets/dataset_loader.py
  class DatasetLoader (line 8) | class DatasetLoader:
    method __init__ (line 9) | def __init__(self, __C):
    method DataSet (line 16) | def DataSet(self):
  class EvalLoader (line 20) | class EvalLoader:
    method __init__ (line 21) | def __init__(self, __C):
    method eval (line 28) | def eval(self, __arg1, __arg2, __arg3, __arg4, __arg5, __arg6, __arg7):

FILE: openvqa/datasets/gqa/eval/gqa_eval.py
  class GQAEval (line 13) | class GQAEval:
    method __init__ (line 14) | def __init__(self, __C, result_eval_file, ques_file_path, choices_path...
    method get_str_result (line 195) | def get_str_result(self):
    method loadFile (line 198) | def loadFile(self, name):
    method toScore (line 215) | def toScore(self, b):
    method avg (line 219) | def avg(self, l):
    method wavg (line 224) | def wavg(self, l, w):
    method getWordsNum (line 233) | def getWordsNum(self, question):
    method getStepsNum (line 237) | def getStepsNum(self, question):
    method belongs (line 260) | def belongs(self, element, group, question):
    method updateConsistency (line 270) | def updateConsistency(self, questionId, question, questions):
    method chiSquare (line 289) | def chiSquare(self, goldDist, predictedDist):

FILE: openvqa/datasets/gqa/eval/result_eval.py
  function eval (line 11) | def eval(__C, dataset, ans_ix_list, pred_list, result_eval_file, ensembl...

FILE: openvqa/datasets/gqa/gqa_loader.py
  class DataSet (line 12) | class DataSet(BaseDataSet):
    method __init__ (line 13) | def __init__(self, __C):
    method img_feat_path_load (line 97) | def img_feat_path_load(self, path_list):
    method tokenize (line 160) | def tokenize(self, json_file, use_glove):
    method ans_stat (line 175) | def ans_stat(self, json_file):
    method load_ques_ans (line 185) | def load_ques_ans(self, idx):
    method load_img_feats (line 202) | def load_img_feats(self, idx, iid):
    method proc_img_feat (line 225) | def proc_img_feat(self, img_feat, img_feat_pad_size):
    method proc_bbox_feat (line 239) | def proc_bbox_feat(self, bbox, img_shape):
    method proc_ques (line 250) | def proc_ques(self, ques, token_to_ix, max_token):
    method proc_ans (line 271) | def proc_ans(self, ans, ans_to_ix):

FILE: openvqa/datasets/vqa/eval/result_eval.py
  function eval (line 7) | def eval(__C, dataset, ans_ix_list, pred_list, result_eval_file, ensembl...

FILE: openvqa/datasets/vqa/eval/vqa.py
  class VQA (line 24) | class VQA:
    method __init__ (line 25) | def __init__(self, annotation_file=None, question_file=None):
    method createIndex (line 47) | def createIndex(self):
    method info (line 65) | def info(self):
    method getQuesIds (line 73) | def getQuesIds(self, imgIds=[], quesTypes=[], ansTypes=[]):
    method getImgIds (line 97) | def getImgIds(self, quesIds=[], quesTypes=[], ansTypes=[]):
    method loadQA (line 121) | def loadQA(self, ids=[]):
    method showQA (line 132) | def showQA(self, anns):
    method loadRes (line 146) | def loadRes(self, resFile, quesFile):

FILE: openvqa/datasets/vqa/eval/vqaEval.py
  class VQAEval (line 10) | class VQAEval:
    method __init__ (line 11) | def __init__(self, vqa, vqaRes, n=2):
    method evaluate (line 68) | def evaluate(self, quesIds=None):
    method processPunctuation (line 122) | def processPunctuation(self, inText):
    method processDigitArticle (line 134) | def processDigitArticle(self, inText):
    method setAccuracy (line 149) | def setAccuracy(self, accQA, accQuesType, accAnsType):
    method setEvalQA (line 154) | def setEvalQA(self, quesId, acc):
    method setEvalQuesType (line 157) | def setEvalQuesType(self, quesId, quesType, acc):
    method setEvalAnsType (line 162) | def setEvalAnsType(self, quesId, ansType, acc):
    method updateProgress (line 167) | def updateProgress(self, progress):

FILE: openvqa/datasets/vqa/vqa_loader.py
  class DataSet (line 11) | class DataSet(BaseDataSet):
    method __init__ (line 12) | def __init__(self, __C):
    method img_feat_path_load (line 82) | def img_feat_path_load(self, path_list):
    method ques_load (line 93) | def ques_load(self, ques_list):
    method tokenize (line 103) | def tokenize(self, stat_ques_list, use_glove):
    method ans_stat (line 159) | def ans_stat(self, json_file):
    method load_ques_ans (line 170) | def load_ques_ans(self, idx):
    method load_img_feats (line 193) | def load_img_feats(self, idx, iid):
    method proc_img_feat (line 215) | def proc_img_feat(self, img_feat, img_feat_pad_size):
    method proc_bbox_feat (line 229) | def proc_bbox_feat(self, bbox, img_shape):
    method proc_ques (line 243) | def proc_ques(self, ques, token_to_ix, max_token):
    method get_score (line 264) | def get_score(self, occur):
    method proc_ans (line 277) | def proc_ans(self, ans, ans_to_ix):

FILE: openvqa/models/ban/adapter.py
  class Adapter (line 12) | class Adapter(BaseAdapter):
    method __init__ (line 13) | def __init__(self, __C):
    method vqa_init (line 18) | def vqa_init(self, __C):
    method gqa_init (line 23) | def gqa_init(self, __C):
    method clevr_init (line 35) | def clevr_init(self, __C):
    method vqa_forward (line 39) | def vqa_forward(self, feat_dict):
    method gqa_forward (line 49) | def gqa_forward(self, feat_dict):
    method clevr_forward (line 64) | def clevr_forward(self, feat_dict):

FILE: openvqa/models/ban/ban.py
  class MLP (line 16) | class MLP(nn.Module):
    method __init__ (line 21) | def __init__(self, dims, act='ReLU', dropout_r=0.0):
    method forward (line 36) | def forward(self, x):
  class BC (line 43) | class BC(nn.Module):
    method __init__ (line 48) | def __init__(self, __C, atten=False):
    method forward (line 66) | def forward(self, v, q):
    method forward_with_weights (line 74) | def forward_with_weights(self, v, q, w):
  class BiAttention (line 87) | class BiAttention(nn.Module):
    method __init__ (line 88) | def __init__(self, __C):
    method forward (line 94) | def forward(self, v, q, v_mask=True, logit=False, mask_with=-float('in...
  class BAN (line 115) | class BAN(nn.Module):
    method __init__ (line 116) | def __init__(self, __C):
    method forward (line 130) | def forward(self, q, v):

FILE: openvqa/models/ban/model_cfgs.py
  class Cfgs (line 9) | class Cfgs(BaseCfgs):
    method __init__ (line 10) | def __init__(self):

FILE: openvqa/models/ban/net.py
  class Net (line 21) | class Net(nn.Module):
    method __init__ (line 22) | def __init__(self, __C, pretrained_emb, token_size, answer_size):
    method forward (line 56) | def forward(self, frcn_feat, grid_feat, bbox_feat, ques_ix):

FILE: openvqa/models/butd/adapter.py
  class Adapter (line 12) | class Adapter(BaseAdapter):
    method __init__ (line 13) | def __init__(self, __C):
    method vqa_init (line 18) | def vqa_init(self, __C):
    method gqa_init (line 22) | def gqa_init(self, __C):
    method clevr_init (line 33) | def clevr_init(self, __C):
    method vqa_forward (line 37) | def vqa_forward(self, feat_dict):
    method gqa_forward (line 47) | def gqa_forward(self, feat_dict):
    method clevr_forward (line 62) | def clevr_forward(self, feat_dict):

FILE: openvqa/models/butd/model_cfgs.py
  class Cfgs (line 9) | class Cfgs(BaseCfgs):
    method __init__ (line 10) | def __init__(self):

FILE: openvqa/models/butd/net.py
  class Net (line 20) | class Net(nn.Module):
    method __init__ (line 21) | def __init__(self, __C, pretrained_emb, token_size, answer_size):
    method forward (line 55) | def forward(self, frcn_feat, grid_feat, bbox_feat, ques_ix):

FILE: openvqa/models/butd/tda.py
  class MLP (line 19) | class MLP(nn.Module):
    method __init__ (line 24) | def __init__(self, dims, act='ELU', dropout_r=0.0):
    method forward (line 39) | def forward(self, x):
  class AttnMap (line 47) | class AttnMap(nn.Module):
    method __init__ (line 51) | def __init__(self, __C):
    method forward (line 62) | def forward(self, q, v):
    method logits (line 69) | def logits(self, q, v):
  class TDA (line 82) | class TDA(nn.Module):
    method __init__ (line 83) | def __init__(self, __C):
    method forward (line 91) | def forward(self, q, v):

FILE: openvqa/models/mcan/adapter.py
  class Adapter (line 12) | class Adapter(BaseAdapter):
    method __init__ (line 13) | def __init__(self, __C):
    method bbox_proc (line 17) | def bbox_proc(self, bbox):
    method vqa_init (line 21) | def vqa_init(self, __C):
    method gqa_init (line 29) | def gqa_init(self, __C):
    method clevr_init (line 40) | def clevr_init(self, __C):
    method vqa_forward (line 44) | def vqa_forward(self, feat_dict):
    method gqa_forward (line 59) | def gqa_forward(self, feat_dict):
    method clevr_forward (line 81) | def clevr_forward(self, feat_dict):

FILE: openvqa/models/mcan/mca.py
  class MHAtt (line 19) | class MHAtt(nn.Module):
    method __init__ (line 20) | def __init__(self, __C):
    method forward (line 31) | def forward(self, v, k, q, mask):
    method att (line 66) | def att(self, value, key, query, mask):
  class FFN (line 86) | class FFN(nn.Module):
    method __init__ (line 87) | def __init__(self, __C):
    method forward (line 98) | def forward(self, x):
  class SA (line 106) | class SA(nn.Module):
    method __init__ (line 107) | def __init__(self, __C):
    method forward (line 119) | def forward(self, y, y_mask):
  class SGA (line 135) | class SGA(nn.Module):
    method __init__ (line 136) | def __init__(self, __C):
    method forward (line 152) | def forward(self, x, y, x_mask, y_mask):
  class MCA_ED (line 172) | class MCA_ED(nn.Module):
    method __init__ (line 173) | def __init__(self, __C):
    method forward (line 179) | def forward(self, y, x, y_mask, x_mask):

FILE: openvqa/models/mcan/model_cfgs.py
  class Cfgs (line 9) | class Cfgs(BaseCfgs):
    method __init__ (line 10) | def __init__(self):

FILE: openvqa/models/mcan/net.py
  class AttFlat (line 21) | class AttFlat(nn.Module):
    method __init__ (line 22) | def __init__(self, __C):
    method forward (line 39) | def forward(self, x, x_mask):
  class Net (line 63) | class Net(nn.Module):
    method __init__ (line 64) | def __init__(self, __C, pretrained_emb, token_size, answer_size):
    method forward (line 97) | def forward(self, frcn_feat, grid_feat, bbox_feat, ques_ix):

FILE: openvqa/models/mfb/adapter.py
  class Adapter (line 13) | class Adapter(BaseAdapter):
    method __init__ (line 14) | def __init__(self, __C):
    method vqa_init (line 19) | def vqa_init(self, __C):
    method gqa_init (line 23) | def gqa_init(self, __C):
    method clevr_init (line 32) | def clevr_init(self, __C):
    method vqa_forward (line 36) | def vqa_forward(self, feat_dict):
    method gqa_forward (line 46) | def gqa_forward(self, feat_dict):
    method clevr_forward (line 61) | def clevr_forward(self, feat_dict):

FILE: openvqa/models/mfb/mfb.py
  class MFB (line 18) | class MFB(nn.Module):
    method __init__ (line 19) | def __init__(self, __C, img_feat_size, ques_feat_size, is_first):
    method forward (line 28) | def forward(self, img_feat, ques_feat, exp_in=1):
  class QAtt (line 48) | class QAtt(nn.Module):
    method __init__ (line 49) | def __init__(self, __C):
    method forward (line 60) | def forward(self, ques_feat):
  class IAtt (line 79) | class IAtt(nn.Module):
    method __init__ (line 80) | def __init__(self, __C, img_feat_size, ques_att_feat_size):
    method forward (line 93) | def forward(self, img_feat, ques_att_feat):
  class CoAtt (line 117) | class CoAtt(nn.Module):
    method __init__ (line 118) | def __init__(self, __C):
    method forward (line 135) | def forward(self, img_feat, ques_feat):

FILE: openvqa/models/mfb/model_cfgs.py
  class Cfgs (line 9) | class Cfgs(BaseCfgs):
    method __init__ (line 10) | def __init__(self):

FILE: openvqa/models/mfb/net.py
  class Net (line 18) | class Net(nn.Module):
    method __init__ (line 19) | def __init__(self, __C, pretrained_emb, token_size, answer_size):
    method forward (line 48) | def forward(self, frcn_feat, grid_feat, bbox_feat, ques_ix):

FILE: openvqa/models/mmnasnet/adapter.py
  class Adapter (line 12) | class Adapter(BaseAdapter):
    method __init__ (line 13) | def __init__(self, __C):
    method relation_embedding (line 18) | def relation_embedding(self, f_g):
    method vqa_init (line 47) | def vqa_init(self, __C):
    method gqa_init (line 55) | def gqa_init(self, __C):
    method clevr_init (line 66) | def clevr_init(self, __C):
    method vqa_forward (line 70) | def vqa_forward(self, feat_dict):
    method gqa_forward (line 86) | def gqa_forward(self, feat_dict):
    method clevr_forward (line 109) | def clevr_forward(self, feat_dict):

FILE: openvqa/models/mmnasnet/model_cfgs.py
  class Cfgs (line 9) | class Cfgs(BaseCfgs):
    method __init__ (line 10) | def __init__(self):

FILE: openvqa/models/mmnasnet/nasnet.py
  class RelMHAtt (line 19) | class RelMHAtt(nn.Module):
    method __init__ (line 20) | def __init__(self, __C):
    method forward (line 35) | def forward(self, v, k, q, mask=None, rel_embed=None):
  class MHAtt (line 63) | class MHAtt(nn.Module):
    method __init__ (line 64) | def __init__(self, __C):
    method forward (line 75) | def forward(self, v, k, q, mask):
    method att (line 110) | def att(self, value, key, query, mask):
  class FFN (line 126) | class FFN(nn.Module):
    method __init__ (line 127) | def __init__(self, __C):
    method forward (line 141) | def forward(self, x, arg1, arg2, arg3, arg4):
  class SA (line 148) | class SA(nn.Module):
    method __init__ (line 149) | def __init__(self, __C, size=1024):
    method forward (line 157) | def forward(self, y, arg1, y_mask, arg2, arg3):
  class RSA (line 165) | class RSA(nn.Module):
    method __init__ (line 166) | def __init__(self, __C, size=1024):
    method forward (line 174) | def forward(self, x, arg1, x_mask, arg2, rela):
  class GA (line 182) | class GA(nn.Module):
    method __init__ (line 183) | def __init__(self, __C):
    method forward (line 191) | def forward(self, x, y, x_mask, y_mask, rela):
  class NAS_ED (line 203) | class NAS_ED(nn.Module):
    method __init__ (line 204) | def __init__(self, __C):
    method forward (line 211) | def forward(self, y, x, y_mask, x_mask, rela):

FILE: openvqa/models/mmnasnet/net.py
  class AttFlat (line 21) | class AttFlat(nn.Module):
    method __init__ (line 22) | def __init__(self, __C):
    method forward (line 39) | def forward(self, x, x_mask):
  class Net (line 63) | class Net(nn.Module):
    method __init__ (line 64) | def __init__(self, __C, pretrained_emb, token_size, answer_size):
    method forward (line 101) | def forward(self, frcn_feat, grid_feat, bbox_feat, ques_ix):

FILE: openvqa/models/model_loader.py
  class ModelLoader (line 9) | class ModelLoader:
    method __init__ (line 10) | def __init__(self, __C):
    method Net (line 16) | def Net(self, __arg1, __arg2, __arg3, __arg4):
  class CfgLoader (line 20) | class CfgLoader:
    method __init__ (line 21) | def __init__(self, model_use):
    method load (line 26) | def load(self):

FILE: openvqa/ops/fc.py
  class FC (line 10) | class FC(nn.Module):
    method __init__ (line 11) | def __init__(self, in_size, out_size, dropout_r=0., use_relu=True):
    method forward (line 24) | def forward(self, x):
  class MLP (line 36) | class MLP(nn.Module):
    method __init__ (line 37) | def __init__(self, in_size, mid_size, out_size, dropout_r=0., use_relu...
    method forward (line 43) | def forward(self, x):

FILE: openvqa/ops/layer_norm.py
  class LayerNorm (line 9) | class LayerNorm(nn.Module):
    method __init__ (line 10) | def __init__(self, size, eps=1e-6):
    method forward (line 17) | def forward(self, x):

FILE: openvqa/utils/ans_punct.py
  function process_punctuation (line 74) | def process_punctuation(inText):
  function process_digit_article (line 86) | def process_digit_article(inText):
  function prep_ans (line 102) | def prep_ans(answer):

FILE: openvqa/utils/feat_filter.py
  function feat_filter (line 7) | def feat_filter(dataset, frcn_feat, grid_feat, bbox_feat):

FILE: openvqa/utils/make_mask.py
  function make_mask (line 10) | def make_mask(feature):

FILE: openvqa/utils/optim.py
  class WarmupOptimizer (line 9) | class WarmupOptimizer(object):
    method __init__ (line 10) | def __init__(self, lr_base, optimizer, data_size, batch_size, warmup_e...
    method step (line 20) | def step(self):
    method zero_grad (line 31) | def zero_grad(self):
    method rate (line 35) | def rate(self, step=None):
  function get_optim (line 51) | def get_optim(__C, model, data_size, lr_base=None):
  function adjust_lr (line 72) | def adjust_lr(optim, decay_r):

FILE: run.py
  function parse_args (line 11) | def parse_args():

FILE: utils/exec.py
  class Execution (line 11) | class Execution:
    method __init__ (line 12) | def __init__(self, __C):
    method run (line 29) | def run(self, run_mode):
    method empty_log (line 45) | def empty_log(self, version):

FILE: utils/proc_dict_gqa.py
  function tokenize (line 38) | def tokenize(stat_ques_dict):
  function ans_stat (line 64) | def ans_stat(stat_ans_dict):

FILE: utils/proc_dict_vqa.py
  function ans_stat (line 21) | def ans_stat(stat_ans_list):

FILE: utils/test_engine.py
  function test_engine (line 16) | def test_engine(__C, dataset, state_dict=None, validation=False):
  function ckpt_proc (line 151) | def ckpt_proc(state_dict):

FILE: utils/train_engine.py
  function train_engine (line 16) | def train_engine(__C, dataset, dataset_eval=None):