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Functions334 in github.com/castorini/castor

⨍ Functions 334◇ Types & classes 79 ↳ Endpoints 3

conv_rnn/train.py:25

(self, dirname, fmt="stsa.fine.{}", word2vec_file="word2vec.sst-1")

conv_rnn/data.py:14

(self, sentences)

conv_rnn/data.py:39

(self, id_dict, weights, unknown_vocab=[], static=True, padding_idx=0)

conv_rnn/model.py:74

(self, id_dict, weights, unknown_vocab=[])

conv_rnn/model.py:104

(self, label, value_flag_map)

idf_baseline/experimental_settings.py:10

(self, qa_dataset)

idf_baseline/experimental_settings.py:28

(self, model, embedding, train_loader, trainer_config, train_evaluator, test_evaluator, dev_evaluator)

common/trainers/sst_trainer.py:13

(self, model, embedding, train_loader, trainer_config, train_evaluator, test_evaluator, dev_evaluator=None)

common/trainers/trainer.py:7

(self, dataset_cls, model, embedding, data_loader, batch_size, device, keep_results=False)

common/evaluators/evaluator.py:6

Create a SNLI dataset instance

datasets/snli.py:34

Create a MSRVID dataset instance

datasets/msrvid.py:41

Create a PIT2015 dataset instance

datasets/pit2015.py:26

Create a WIKIQA dataset instance

datasets/wikiqa.py:26

Create a Castor dataset involving pairs of texts

datasets/castor_dataset.py:27

Create a SICK dataset instance

datasets/sick.py:41

Create a Quora dataset instance

datasets/quora.py:34

Create a TRECQA dataset instance

datasets/trecqa.py:26

Create a STS2014 dataset instance

datasets/sts2014.py:42

Create the model based on MLP networks. :param num_units: size of the networks :param num_classes: number of classes in the

decatt/model.py:14

(self, n_word_dim, n_holistic_filters, n_per_dim_filters, filter_widths, hidden_layer_units, num_classes, drop

mp_cnn/lite_model.py:11

(self, n_word_dim, n_holistic_filters, n_per_dim_filters, filter_widths, hidden_layer_units, num_classes, drop

mp_cnn/model.py:9

(self, h_size=[512, 1024, 2048], d=300, mlp_d=1600, dropout_r=0.1, max_l=60, num_classes=3)

sse/model.py:11

Constructor for the CallRetrieveSentences class. Parameters ---------- args : argparse.Namespace Argumen

anserini_dependency/RetrieveSentences.py:19

conv_rnn/train.py:18

conv_rnn/train.py:40

vdpwi/data.py:56

conv_rnn/data.py:43

conv_rnn/train.py:45

Method_add_layers

mp_cnn/lite_model.py:15

Method_get_n_feats

mp_cnn/lite_model.py:31

Method_transformation_input

(self,embed_sent, x1_mask)

esim/model.py:194

anserini_dependency/api.py:22

Methodattention_softmax3d

(self,raw_attentions)

esim/model.py:189

Functionauto_rnn_bilstm

(lstm: nn.LSTM, seqs, lengths)

utils/torch_util.py:9

Methodbuild_mask

vdpwi/model.py:138

FunctioncancelAnalyserUpdates

anserini_dependency/js/speech.js:79

Functionclean_str_sst

Tokenization/string cleaning for the SST dataset

datasets/sst.py:10

Functioncompute_overlap_idx

(questions, answers, stoplist, q_max_sent_length, a_max_sent_length)

sm_cnn/overlap_features.py:62

Functioncompute_overlap_idx

(questions, answers, stoplist, q_max_sent_length, a_max_sent_length)

nce/nce_pairwise_sm/overlap_features.py:62

Methodcompute_prism

vdpwi/model.py:111

Methodcompute_sim

(prism1, prism2)

vdpwi/model.py:101

Methodconvert_dataset

(self, dataset)

conv_rnn/model.py:35

Methodcosine_interaction

:param tensor1: #step1 * dim :param tensor2: #step2 * dim :return: #step1 * #step2

esim/model.py:221

Functiondiscrete_tnorm

(a, b, tgt_loc, sigma=1, n_steps=100)

vdpwi/utils/preprocess.py:19

sse/model.py:35

FunctiondoneEncoding

anserini_dependency/js/speech.js:45

vdpwi/model.py:29

vdpwi/model.py:60

(self, sent1, sent2, ext_feats=None, word_to_doc_count=None, raw_sent1=None, raw_sent2=None)

vdpwi/model.py:157

(self, x_question, x_answer, x_ext)

sm_cnn/model.py:46

nce/nce_pairwise_sm/model.py:19

nce/nce_pairwise_sm/model.py:65

(self, input, h, c)

esim/model.py:65

:param x: #step x #sample x dim_emb :param x_mask: #step x #sample :param x_left_mask: #step x #sample x #step :param

esim/model.py:84

(self, sent1, sent2, ext_feats=None, word_to_doc_count=None, raw_sent1=None, raw_sent2=None, visualize=False)

esim/model.py:251

(self, x, lengths)

conv_rnn/model.py:54

conv_rnn/model.py:95

(self, sent1, sent2, ext_feats=None, word_to_doc_count=None, raw_sent1=None, raw_sent2=None)

decatt/model.py:158

(self, sent1, sent2, ext_feats=None, word_to_doc_count=None, raw_sent1=None, raw_sent2=None)

mp_cnn/lite_model.py:100

(self, sent1, sent2, ext_feats=None, word_to_doc_count=None, raw_sent1=None, raw_sent2=None)

mp_cnn/model.py:219

(self, sent1, sent2, ext_feats=None, word_to_doc_count=None, raw_sent1=None, raw_sent2=None)

sse/model.py:39

Methodget_choice

(self, setting)

idf_baseline/experimental_settings.py:17

Functionget_class_probs

Convert a single label into class probabilities.

datasets/snli.py:11

Functionget_class_probs

Convert a single label into class probabilities.

datasets/msrvid.py:13

Functionget_class_probs

Convert a single label into class probabilities.

datasets/sick.py:13

Functionget_class_probs

Convert a single label into class probabilities.

datasets/quora.py:11

Functionget_class_probs

Convert a single label into class probabilities.

datasets/sts2014.py:13

Methodget_final_prediction_and_label

(self, batch_predictions, batch_labels)

common/evaluators/sick_evaluator.py:45

Methodget_final_prediction_and_label

(self, batch_predictions, batch_labels)

common/evaluators/sts2014_evaluator.py:45

Methodget_final_prediction_and_label

(self, batch_predictions, batch_labels)

common/evaluators/qa_evaluator.py:38

Methodget_final_prediction_and_label

(self, batch_predictions, batch_labels)

common/evaluators/msrvid_evaluator.py:41

Methodget_scores

common/evaluators/snli_evaluator.py:9

Methodget_scores

common/evaluators/sick_evaluator.py:10

Methodget_scores

common/evaluators/quora_evaluator.py:9

Methodget_scores

common/evaluators/sts2014_evaluator.py:10

Methodget_scores

common/evaluators/sst_evaluator.py:9

Methodget_scores

common/evaluators/pit2015_evaluator.py:79

Methodget_scores

common/evaluators/qa_evaluator.py:9

Methodget_scores

common/evaluators/msrvid_evaluator.py:10

Methodget_settings

idf_baseline/experimental_settings.py:14

FunctiongotBuffers

anserini_dependency/js/speech.js:40

FunctiongotStream

anserini_dependency/js/speech.js:136

anserini_dependency/api.py:18

FunctioninitAudio

anserini_dependency/js/speech.js:157

Methodinitialize_lstm

esim/model.py:165

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param vectors_dir: d

datasets/snli.py:45

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param vectors_cache:

datasets/msrvid.py:52

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param vectors_dir: d

datasets/pit2015.py:37

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param vectors_dir: d

datasets/wikiqa.py:37

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param ve

datasets/sst.py:82

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param vectors_cache:

datasets/sick.py:52

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param vectors_dir: d

datasets/quora.py:45

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param vectors_dir: d

datasets/trecqa.py:37

:param path: directory containing train, test, dev files :param vectors_name: name of word vectors file :param vectors_cache:

datasets/sts2014.py:53

Functionload_dataset

vdpwi/data.py:105

Functionload_sick

vdpwi/data.py:60

Methodlog_dev_metrics

(self, pearsonr, spearmanr)

vdpwi/utils/log.py:20

Methodlog_hyperparams

vdpwi/utils/log.py:13

Methodlog_train_loss

vdpwi/utils/log.py:16

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