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setting_keywords.py
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setting_keywords.py
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class KeyWordSettings(object):
Doc_cID = "doc_cid"
Doc_URL = "doc_ciurl"
Doc_cLabel = "doc_clabel"
Doc_wImages = "doc_wimages"
Doc_wContent = "doc_wcontent"
Relevant_Score = "relevant_score"
Query_id = "qid"
Query_TweetID = "qtweetid"
Query_Images = "query_images"
Ranked_Docs = "ranked_docs"
Query_Content = "query_content"
Query_Adj = "query_adj"
Evd_Docs_Adj = "docs_adj"
GNN_Window = "gnn_window"
Query_lens = "query_lens"
Doc_lens = "docs_lens"
# for lstm keywords
QueryLensIndices = "query_lens_indices"
DocLensIndices = "doc_lens_indices"
QueryIDs = "query_ids"
DocIDs = "doc_ids"
UseVisual = "use_visual"
OutputRankingKey = "output_ranking"
QueryCountVal = [1116, 1000, 187, 1159]
QueryCountTest = [1001, 1164, 1118, 187, 156, 1160, 1500]
UseCuda = "use_cuda"
QuerySources = "query_sources"
DocSources = "doc_sources"
TempLabel = "fc_labels"
DocContentNoPaddingEvidence = "doc_content_without_padding_evidences" # to avoid empty sequences to lstm
QueryContentNoPaddingEvidence = "query_content_without_padding_evidences"
ClaimEmbeddings = "claim_embeddings"
EvidenceEmbeddings = "evidences_embeddings"
EvidenceCountPerQuery = "evd_cnt_each_query"
FIXED_NUM_EVIDENCES = "fixed_num_evidences"
LOSS_FUNCTIONS = ("cross_entropy")
ClaimCountVal = [433, 356]
ClaimCountTest = [782, 781, 391, 390, 644, 642, 323, 321]
AUC_metric = "auc"
F1_macro = "f1_macro"
F1_micro = "f1_micro"
F1 = "f1"
PrecisionTrueCls = "precision_true_cls"
RecallTrueCls = "recall_true_cls"
F1TrueCls = "f1_true_cls"
PrecisionFalseCls = "precision_false_cls"
RecallFalseCls = "recall_false_cls"
F1FalseCls = "f1_false_cls"
PrecisionMixedCls = "precision_mixed_cls"
RecallMixedCls = "recall_mixed_cls"
F1MixedCls = "f1_mixed_cls"
# for fact-checking error analysis
class FCClass:
DocAttentionScore = "doc_attention_score"
WordAttentionScore = "word_attention_score"
ClaimLabel = "claim_label"
PredictedProb = "predicted_prob"
AttentionWeightsInfo = "attention_weights_info"
CharSourceKey = "char_source"
QueryCharSource = "query_char_source" # characters of claims' source (i.e. chars of speakers' names)
DocCharSource = "doc_char_source"
CLS_METRICS = [AUC_metric,F1_macro, F1_micro, F1,
PrecisionTrueCls, RecallTrueCls, F1TrueCls,
PrecisionFalseCls, RecallFalseCls, F1FalseCls,]
OutputHandlerFactChecking = "output_handler_fact_checking"
OutputRepr = "ouput_repr"