SYMBOL INDEX (1257 symbols across 80 files) FILE: DualGCN/data_utils.py function ParseData (line 19) | def ParseData(data_path): function build_tokenizer (line 59) | def build_tokenizer(fnames, max_length, data_file): class Vocab (line 70) | class Vocab(object): method __init__ (line 72) | def __init__(self, vocab_list, add_pad, add_unk): method word_to_id (line 92) | def word_to_id(self, word): method id_to_word (line 97) | def id_to_word(self, id_): method has_word (line 102) | def has_word(self, word): method __len__ (line 105) | def __len__(self): method load_vocab (line 109) | def load_vocab(vocab_path: str): method save_vocab (line 113) | def save_vocab(self, vocab_path): class Tokenizer (line 118) | class Tokenizer(object): method __init__ (line 120) | def __init__(self, vocab, max_length, lower, pos_char_to_int, pos_int_... method from_files (line 129) | def from_files(cls, fnames, max_length, parse, lower=True): method pad_sequence (line 141) | def pad_sequence(sequence, pad_id, maxlen, dtype='int64', padding='pos... method text_to_sequence (line 154) | def text_to_sequence(self, text, reverse=False, padding='post', trunca... method split_text (line 167) | def split_text(text): class SentenceDataset (line 173) | class SentenceDataset(Dataset): method __init__ (line 175) | def __init__(self, fname, tokenizer, opt, vocab_help): method __getitem__ (line 230) | def __getitem__(self, index): method __len__ (line 233) | def __len__(self): function _load_wordvec (line 236) | def _load_wordvec(data_path, embed_dim, vocab=None): function build_embedding_matrix (line 262) | def build_embedding_matrix(vocab, embed_dim, data_file): function softmax (line 279) | def softmax(x): class Tokenizer4BertGCN (line 297) | class Tokenizer4BertGCN: method __init__ (line 298) | def __init__(self, max_seq_len, pretrained_bert_name): method tokenize (line 303) | def tokenize(self, s): method convert_tokens_to_ids (line 305) | def convert_tokens_to_ids(self, tokens): class ABSAGCNData (line 309) | class ABSAGCNData(Dataset): method __init__ (line 310) | def __init__(self, fname, tokenizer, opt): method __len__ (line 405) | def __len__(self): method __getitem__ (line 408) | def __getitem__(self, idx): FILE: DualGCN/layers.py class DynamicLSTM (line 6) | class DynamicLSTM(nn.Module): method __init__ (line 10) | def __init__(self, input_size, hidden_size, num_layers=1, bias=True, b... method forward (line 33) | def forward(self, x, x_len): class SqueezeEmbedding (line 64) | class SqueezeEmbedding(nn.Module): method __init__ (line 68) | def __init__(self, batch_first=True): method forward (line 72) | def forward(self, x, x_len): class SoftAttention (line 91) | class SoftAttention(nn.Module): method __init__ (line 95) | def __init__(self, hidden_dim, embed_dim): method forward (line 105) | def forward(self, h, aspect): class Attention (line 116) | class Attention(nn.Module): method __init__ (line 117) | def __init__(self, embed_dim, hidden_dim=None, out_dim=None, n_head=1,... method reset_parameters (line 147) | def reset_parameters(self): method forward (line 152) | def forward(self, k, q): FILE: DualGCN/models/atae_lstm.py class ATAE_LSTM (line 13) | class ATAE_LSTM(nn.Module): method __init__ (line 15) | def __init__(self, embedding_matrix, opt): method forward (line 23) | def forward(self, inputs): FILE: DualGCN/models/dualgcn.py class DualGCNClassifier (line 17) | class DualGCNClassifier(nn.Module): method __init__ (line 18) | def __init__(self, embedding_matrix, opt): method forward (line 25) | def forward(self, inputs): class GCNAbsaModel (line 56) | class GCNAbsaModel(nn.Module): method __init__ (line 57) | def __init__(self, embedding_matrix, opt): method forward (line 68) | def forward(self, inputs): class GCN (line 92) | class GCN(nn.Module): method __init__ (line 93) | def __init__(self, opt, embeddings, mem_dim, num_layers): method encode_with_rnn (line 131) | def encode_with_rnn(self, rnn_inputs, seq_lens, batch_size): method forward (line 138) | def forward(self, adj, inputs): function rnn_zero_state (line 204) | def rnn_zero_state(batch_size, hidden_dim, num_layers, bidirectional=True): function attention (line 211) | def attention(query, key, mask=None, dropout=None): function clones (line 224) | def clones(module, N): class MultiHeadAttention (line 228) | class MultiHeadAttention(nn.Module): method __init__ (line 230) | def __init__(self, h, d_model, dropout=0.1): method forward (line 238) | def forward(self, query, key, mask=None): FILE: DualGCN/models/dualgcn_bert.py class LayerNorm (line 15) | class LayerNorm(nn.Module): method __init__ (line 18) | def __init__(self, features, eps=1e-6): method forward (line 24) | def forward(self, x): class DualGCNBertClassifier (line 30) | class DualGCNBertClassifier(nn.Module): method __init__ (line 31) | def __init__(self, bert, opt): method forward (line 37) | def forward(self, inputs): class GCNAbsaModel (line 68) | class GCNAbsaModel(nn.Module): method __init__ (line 69) | def __init__(self, bert, opt): method forward (line 74) | def forward(self, inputs): class GCNBert (line 86) | class GCNBert(nn.Module): method __init__ (line 87) | def __init__(self, bert, opt, num_layers): method forward (line 115) | def forward(self, adj, inputs): function attention (line 171) | def attention(query, key, mask=None, dropout=None): function clones (line 184) | def clones(module, N): class MultiHeadAttention (line 188) | class MultiHeadAttention(nn.Module): method __init__ (line 190) | def __init__(self, h, d_model, dropout=0.1): method forward (line 198) | def forward(self, query, key, mask=None): FILE: DualGCN/models/ian.py class IAN (line 13) | class IAN(nn.Module): method __init__ (line 14) | def __init__(self, embedding_matrix, opt): method forward (line 24) | def forward(self, inputs): FILE: DualGCN/models/semgcn.py class SemGCNClassifier (line 16) | class SemGCNClassifier(nn.Module): method __init__ (line 17) | def __init__(self, embedding_matrix, opt): method forward (line 24) | def forward(self, inputs): class GCNAbsaModel (line 30) | class GCNAbsaModel(nn.Module): method __init__ (line 31) | def __init__(self, embedding_matrix, opt): method forward (line 43) | def forward(self, inputs): class GCN (line 57) | class GCN(nn.Module): method __init__ (line 58) | def __init__(self, opt, embeddings, mem_dim, num_layers): method encode_with_rnn (line 94) | def encode_with_rnn(self, rnn_inputs, seq_lens, batch_size): method forward (line 101) | def forward(self, inputs): function rnn_zero_state (line 149) | def rnn_zero_state(batch_size, hidden_dim, num_layers, bidirectional=True): function attention (line 156) | def attention(query, key, mask=None, dropout=None): function clones (line 169) | def clones(module, N): class MultiHeadAttention (line 173) | class MultiHeadAttention(nn.Module): method __init__ (line 175) | def __init__(self, h, d_model, dropout=0.1): method forward (line 184) | def forward(self, query, key, mask=None): FILE: DualGCN/models/syngcn.py class SynGCNClassifier (line 15) | class SynGCNClassifier(nn.Module): method __init__ (line 16) | def __init__(self, embedding_matrix, opt): method forward (line 23) | def forward(self, inputs): class GCNAbsaModel (line 28) | class GCNAbsaModel(nn.Module): method __init__ (line 29) | def __init__(self, embedding_matrix, opt): method forward (line 42) | def forward(self, inputs): class GCN (line 66) | class GCN(nn.Module): method __init__ (line 67) | def __init__(self, opt, embeddings, mem_dim, num_layers): method encode_with_rnn (line 95) | def encode_with_rnn(self, rnn_inputs, seq_lens, batch_size): method forward (line 102) | def forward(self, adj, inputs): function rnn_zero_state (line 131) | def rnn_zero_state(batch_size, hidden_dim, num_layers, bidirectional=True): FILE: DualGCN/prepare_vocab.py class VocabHelp (line 11) | class VocabHelp(object): method __init__ (line 12) | def __init__(self, counter, specials=['', '']): method __eq__ (line 31) | def __eq__(self, other): method __len__ (line 38) | def __len__(self): method extend (line 41) | def extend(self, v): method load_vocab (line 50) | def load_vocab(vocab_path: str): method save_vocab (line 54) | def save_vocab(self, vocab_path): function parse_args (line 58) | def parse_args(): function main (line 66) | def main(): function load_tokens (line 120) | def load_tokens(filename): FILE: DualGCN/train.py function setup_seed (line 34) | def setup_seed(seed): class Instructor (line 42) | class Instructor: method __init__ (line 44) | def __init__(self, opt): method _print_args (line 86) | def _print_args(self): method _reset_params (line 101) | def _reset_params(self): method get_bert_optimizer (line 110) | def get_bert_optimizer(self, model): method _train (line 158) | def _train(self, criterion, optimizer, max_test_acc_overall=0): method _evaluate (line 201) | def _evaluate(self, show_results=False): method _test (line 227) | def _test(self): method run (line 237) | def run(self): function main (line 260) | def main(): FILE: DualGCN/tree.py class Tree (line 10) | class Tree(object): method __init__ (line 14) | def __init__(self): method add_child (line 19) | def add_child(self, child): method size (line 24) | def size(self): method depth (line 33) | def depth(self): method __iter__ (line 46) | def __iter__(self): function head_to_tree (line 52) | def head_to_tree(head, tokens, len_): function tree_to_adj (line 79) | def tree_to_adj(sent_len, tree, directed=False, self_loop=True): FILE: LAL-Parser/EVALB/evalb.c type s_terminal (line 80) | typedef struct ss_terminal { type s_term_ind (line 86) | typedef struct ss_term_ind { type s_bracket (line 94) | typedef struct ss_bracket { type s_equiv (line 104) | typedef struct ss_equiv { function main (line 306) | int function init_global (line 416) | void function print_head (line 437) | void function init (line 449) | void function read_parameter_file (line 500) | void function set_param (line 546) | void function narg (line 620) | int function read_line (line 646) | int function pushb (line 767) | void function popb (line 774) | int function stackempty (line 787) | int function calc_result (line 801) | void function fix_quote (line 977) | void function reinsert_term (line 1017) | void function massage_data (line 1071) | void function modify_label (line 1144) | void function individual_result (line 1162) | void function print_total (line 1236) | void function dsp_info (line 1325) | void function is_terminator (line 1381) | int function is_deletelabel (line 1392) | int function is_deletelabel_for_length (line 1407) | int function is_quote_term (line 1422) | int function word_comp (line 1443) | int function label_comp (line 1468) | int function Error (line 1494) | void function Fatal (line 1510) | void function Usage (line 1522) | void FILE: LAL-Parser/src_joint/KM_parser.py function from_numpy (line 15) | def from_numpy(ndarray): class BatchIndices (line 80) | class BatchIndices: method __init__ (line 84) | def __init__(self, batch_idxs_np): class FeatureDropoutFunction (line 97) | class FeatureDropoutFunction(torch.autograd.function.InplaceFunction): method forward (line 99) | def forward(cls, ctx, input, batch_idxs, p=0.5, train=False, inplace=F... method backward (line 126) | def backward(ctx, grad_output): class FeatureDropout (line 133) | class FeatureDropout(nn.Module): method __init__ (line 139) | def __init__(self, p=0.5, inplace=False): method forward (line 147) | def forward(self, input, batch_idxs): class LayerNormalization (line 151) | class LayerNormalization(nn.Module): method __init__ (line 152) | def __init__(self, d_hid, eps=1e-3, affine=True): method forward (line 161) | def forward(self, z): class ScaledAttention (line 174) | class ScaledAttention(nn.Module): method __init__ (line 175) | def __init__(self, hparams, attention_dropout=0.1): method forward (line 182) | def forward(self, q, k, v, attn_mask=None): class ScaledDotProductAttention (line 206) | class ScaledDotProductAttention(nn.Module): method __init__ (line 207) | def __init__(self, d_model, attention_dropout=0.1): method forward (line 213) | def forward(self, q, k, v, attn_mask=None): class MultiHeadAttention (line 244) | class MultiHeadAttention(nn.Module): method __init__ (line 249) | def __init__(self, hparams, n_head, d_model, d_k, d_v, residual_dropou... method split_qkv_packed (line 303) | def split_qkv_packed(self, inp, qk_inp=None): method pad_and_rearrange (line 329) | def pad_and_rearrange(self, q_s, k_s, v_s, batch_idxs): method combine_v (line 357) | def combine_v(self, outputs): method forward (line 381) | def forward(self, inp, batch_idxs, qk_inp=None): class PositionwiseFeedForward (line 407) | class PositionwiseFeedForward(nn.Module): method __init__ (line 415) | def __init__(self, d_hid, d_ff, relu_dropout=0.1, residual_dropout=0.1): method forward (line 426) | def forward(self, x, batch_idxs): class PartitionedPositionwiseFeedForward (line 437) | class PartitionedPositionwiseFeedForward(nn.Module): method __init__ (line 438) | def __init__(self, d_hid, d_ff, d_positional, relu_dropout=0.1, residu... method forward (line 450) | def forward(self, x, batch_idxs): class MultiLevelEmbedding (line 469) | class MultiLevelEmbedding(nn.Module): method __init__ (line 470) | def __init__(self, method forward (line 548) | def forward(self, xs, pre_words_idxs, batch_idxs, extra_content_annota... class CharacterLSTM (line 596) | class CharacterLSTM(nn.Module): method __init__ (line 597) | def __init__(self, num_embeddings, d_embedding, d_out, method forward (line 617) | def forward(self, chars_padded_np, word_lens_np, batch_idxs): function get_elmo_class (line 642) | def get_elmo_class(): function get_xlnet (line 692) | def get_xlnet(xlnet_model, xlnet_do_lower_case): function get_roberta (line 704) | def get_roberta(roberta_model, roberta_do_lower_case): function get_bert (line 716) | def get_bert(bert_model, bert_do_lower_case): class BiLinear (line 737) | class BiLinear(nn.Module): method __init__ (line 741) | def __init__(self, left_features, right_features, out_features, bias=T... method reset_parameters (line 767) | def reset_parameters(self): method forward (line 773) | def forward(self, input_left, input_right): class BiAAttention (line 795) | class BiAAttention(nn.Module): method __init__ (line 800) | def __init__(self, hparams): method forward (line 807) | def forward(self, input_d, input_e, input_s = None): class Dep_score (line 818) | class Dep_score(nn.Module): method __init__ (line 819) | def __init__(self, hparams, num_labels): method forward (line 834) | def forward(self, outputs, outpute): class LabelAttention (line 868) | class LabelAttention(nn.Module): method __init__ (line 873) | def __init__(self, hparams, d_model, d_k, d_v, d_l, d_proj, use_resdro... method split_qkv_packed (line 952) | def split_qkv_packed(self, inp, k_inp=None): method pad_and_rearrange (line 988) | def pad_and_rearrange(self, q_s, k_s, v_s, batch_idxs): method combine_v (line 1028) | def combine_v(self, outputs): method forward (line 1058) | def forward(self, inp, batch_idxs, k_inp=None): class Encoder (line 1105) | class Encoder(nn.Module): method __init__ (line 1106) | def __init__(self, hparams, embedding, method forward (line 1165) | def forward(self, xs, pre_words_idxs, batch_idxs, extra_content_annota... class ChartParser (line 1176) | class ChartParser(nn.Module): method __init__ (line 1177) | def __init__( method model (line 1407) | def model(self): method from_spec (line 1411) | def from_spec(cls, spec, model): method split_batch (line 1465) | def split_batch(self, sentences, golds, subbatch_max_tokens=3000): method parse_batch (line 1482) | def parse_batch(self, sentences, golds=None): method label_scores_from_annotations (line 1869) | def label_scores_from_annotations(self, fencepost_annotations_start, f... method parse_from_annotations (line 1896) | def parse_from_annotations(self, fencepost_annotations_start, fencepos... method decode_from_chart_batch (line 1931) | def decode_from_chart_batch(self, sentences, charts_np, golds=None): method decode_from_chart (line 1942) | def decode_from_chart(self, sentence, label_scores_chart_np, arc_dc_np... FILE: LAL-Parser/src_joint/absa_parser.py function torch_load (line 13) | def torch_load(load_path): class Config (line 20) | class Config(object): class ParseHead (line 25) | class ParseHead(object): method __init__ (line 26) | def __init__(self, config) -> None: method parse_heads (line 36) | def parse_heads(self, sentence): FILE: LAL-Parser/src_joint/dep_eval.py function is_uni_punctuation (line 6) | def is_uni_punctuation(word): function is_punctuation (line 11) | def is_punctuation(word, pos, punct_set=None): function eval (line 18) | def eval(batch_size, words, postags, heads_pred, types_pred, heads, type... FILE: LAL-Parser/src_joint/dep_reader.py class Sentence (line 6) | class Sentence(object): method __init__ (line 7) | def __init__(self, words, postags): method length (line 11) | def length(self): class DependencyInstance (line 15) | class DependencyInstance(object): method __init__ (line 16) | def __init__(self, sentence, postags, heads, types): method length (line 22) | def length(self): class CoNLLXReader (line 26) | class CoNLLXReader(object): method __init__ (line 27) | def __init__(self, file_path, type_vocab = None): method close (line 31) | def close(self): method getNext (line 34) | def getNext(self): FILE: LAL-Parser/src_joint/evaluate.py class FScore (line 9) | class FScore(object): method __init__ (line 10) | def __init__(self, recall, precision, fscore): method __str__ (line 15) | def __str__(self): function evalb (line 19) | def evalb(evalb_dir, gold_trees, predicted_trees, ref_gold_path=None): FILE: LAL-Parser/src_joint/main.py function torch_load (line 38) | def torch_load(load_path): function format_elapsed (line 44) | def format_elapsed(start_time): function make_hparams (line 54) | def make_hparams(): function count_wh (line 134) | def count_wh(str, data, heads, types): function run_train (line 146) | def run_train(args, hparams): function run_test (line 544) | def run_test(args): function run_parse (line 650) | def run_parse(args): function run_parse_head (line 736) | def run_parse_head(args): function main (line 794) | def main(): FILE: LAL-Parser/src_joint/makehp.py class HParams (line 1) | class HParams(): method __init__ (line 3) | def __init__(self, **kwargs): method __getitem__ (line 7) | def __getitem__(self, item): method __setitem__ (line 10) | def __setitem__(self, item, value): method to_dict (line 15) | def to_dict(self): method populate_arguments (line 23) | def populate_arguments(self, parser): method set_from_args (line 37) | def set_from_args(self, args): method print (line 46) | def print(self): FILE: LAL-Parser/src_joint/pretrained_bert/__main__.py function main (line 2) | def main(): FILE: LAL-Parser/src_joint/pretrained_bert/convert_tf_checkpoint_to_pytorch.py function convert_tf_checkpoint_to_pytorch (line 30) | def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, bert_config_fil... FILE: LAL-Parser/src_joint/pretrained_bert/file_utils.py function url_to_filename (line 30) | def url_to_filename(url: str, etag: str = None) -> str: function filename_to_url (line 48) | def filename_to_url(filename: str, cache_dir: Union[str, Path] = None) -... function cached_path (line 74) | def cached_path(url_or_filename: Union[str, Path], cache_dir: Union[str,... function split_s3_path (line 104) | def split_s3_path(url: str) -> Tuple[str, str]: function s3_request (line 117) | def s3_request(func: Callable): function s3_etag (line 137) | def s3_etag(url: str) -> Optional[str]: function s3_get (line 146) | def s3_get(url: str, temp_file: IO) -> None: function http_get (line 153) | def http_get(url: str, temp_file: IO) -> None: function get_from_cache (line 165) | def get_from_cache(url: str, cache_dir: Union[str, Path] = None) -> str: function read_set_from_file (line 224) | def read_set_from_file(filename: str) -> Set[str]: function get_file_extension (line 236) | def get_file_extension(path: str, dot=True, lower: bool = True): FILE: LAL-Parser/src_joint/pretrained_bert/modeling.py function gelu (line 51) | def gelu(x): function swish (line 59) | def swish(x): class BertConfig (line 66) | class BertConfig(object): method __init__ (line 69) | def __init__(self, method from_dict (line 127) | def from_dict(cls, json_object): method from_json_file (line 135) | def from_json_file(cls, json_file): method __repr__ (line 141) | def __repr__(self): method to_dict (line 144) | def to_dict(self): method to_json_string (line 149) | def to_json_string(self): class BertLayerNorm (line 157) | class BertLayerNorm(nn.Module): method __init__ (line 158) | def __init__(self, hidden_size, eps=1e-12): method forward (line 166) | def forward(self, x): class BertEmbeddings (line 172) | class BertEmbeddings(nn.Module): method __init__ (line 175) | def __init__(self, config): method forward (line 186) | def forward(self, input_ids, token_type_ids=None): class BertSelfAttention (line 203) | class BertSelfAttention(nn.Module): method __init__ (line 204) | def __init__(self, config): method transpose_for_scores (line 220) | def transpose_for_scores(self, x): method forward (line 225) | def forward(self, hidden_states, attention_mask): class BertSelfOutput (line 254) | class BertSelfOutput(nn.Module): method __init__ (line 255) | def __init__(self, config): method forward (line 261) | def forward(self, hidden_states, input_tensor): class BertAttention (line 268) | class BertAttention(nn.Module): method __init__ (line 269) | def __init__(self, config): method forward (line 274) | def forward(self, input_tensor, attention_mask): class BertIntermediate (line 280) | class BertIntermediate(nn.Module): method __init__ (line 281) | def __init__(self, config): method forward (line 287) | def forward(self, hidden_states): class BertOutput (line 293) | class BertOutput(nn.Module): method __init__ (line 294) | def __init__(self, config): method forward (line 300) | def forward(self, hidden_states, input_tensor): class BertLayer (line 307) | class BertLayer(nn.Module): method __init__ (line 308) | def __init__(self, config): method forward (line 314) | def forward(self, hidden_states, attention_mask): class BertEncoder (line 321) | class BertEncoder(nn.Module): method __init__ (line 322) | def __init__(self, config): method forward (line 327) | def forward(self, hidden_states, attention_mask, output_all_encoded_la... class BertPooler (line 338) | class BertPooler(nn.Module): method __init__ (line 339) | def __init__(self, config): method forward (line 344) | def forward(self, hidden_states): class BertPredictionHeadTransform (line 353) | class BertPredictionHeadTransform(nn.Module): method __init__ (line 354) | def __init__(self, config): method forward (line 361) | def forward(self, hidden_states): class BertLMPredictionHead (line 368) | class BertLMPredictionHead(nn.Module): method __init__ (line 369) | def __init__(self, config, bert_model_embedding_weights): method forward (line 381) | def forward(self, hidden_states): class BertOnlyMLMHead (line 387) | class BertOnlyMLMHead(nn.Module): method __init__ (line 388) | def __init__(self, config, bert_model_embedding_weights): method forward (line 392) | def forward(self, sequence_output): class BertOnlyNSPHead (line 397) | class BertOnlyNSPHead(nn.Module): method __init__ (line 398) | def __init__(self, config): method forward (line 402) | def forward(self, pooled_output): class BertPreTrainingHeads (line 407) | class BertPreTrainingHeads(nn.Module): method __init__ (line 408) | def __init__(self, config, bert_model_embedding_weights): method forward (line 413) | def forward(self, sequence_output, pooled_output): class PreTrainedBertModel (line 419) | class PreTrainedBertModel(nn.Module): method __init__ (line 423) | def __init__(self, config, *inputs, **kwargs): method init_bert_weights (line 434) | def init_bert_weights(self, module): method from_pretrained (line 448) | def from_pretrained(cls, pretrained_model_name, state_dict=None, cache... class BertModel (line 554) | class BertModel(PreTrainedBertModel): method __init__ (line 598) | def __init__(self, config): method forward (line 605) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForPreTraining (line 637) | class BertForPreTraining(PreTrainedBertModel): method __init__ (line 687) | def __init__(self, config): method forward (line 693) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForMaskedLM (line 708) | class BertForMaskedLM(PreTrainedBertModel): method __init__ (line 750) | def __init__(self, config): method forward (line 756) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForNextSentencePrediction (line 769) | class BertForNextSentencePrediction(PreTrainedBertModel): method __init__ (line 812) | def __init__(self, config): method forward (line 818) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForSequenceClassification (line 831) | class BertForSequenceClassification(PreTrainedBertModel): method __init__ (line 876) | def __init__(self, config, num_labels=2): method forward (line 884) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForMultipleChoice (line 897) | class BertForMultipleChoice(PreTrainedBertModel): method __init__ (line 941) | def __init__(self, config, num_choices=2): method forward (line 949) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForTokenClassification (line 966) | class BertForTokenClassification(PreTrainedBertModel): method __init__ (line 1011) | def __init__(self, config, num_labels=2): method forward (line 1019) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForQuestionAnswering (line 1032) | class BertForQuestionAnswering(PreTrainedBertModel): method __init__ (line 1087) | def __init__(self, config): method forward (line 1095) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... FILE: LAL-Parser/src_joint/pretrained_bert/optimization.py function warmup_cosine (line 23) | def warmup_cosine(x, warmup=0.002): function warmup_constant (line 28) | def warmup_constant(x, warmup=0.002): function warmup_linear (line 33) | def warmup_linear(x, warmup=0.002): class BertAdam (line 45) | class BertAdam(Optimizer): method __init__ (line 59) | def __init__(self, params, lr=required, warmup=-1, t_total=-1, schedul... method get_lr (line 79) | def get_lr(self): method step (line 94) | def step(self, closure=None): FILE: LAL-Parser/src_joint/pretrained_bert/tokenization.py function load_vocab (line 51) | def load_vocab(vocab_file): function whitespace_tokenize (line 66) | def whitespace_tokenize(text): class BertTokenizer (line 75) | class BertTokenizer(object): method __init__ (line 78) | def __init__(self, vocab_file, do_lower_case=True, max_len=None): method tokenize (line 90) | def tokenize(self, text): method convert_tokens_to_ids (line 97) | def convert_tokens_to_ids(self, tokens): method convert_ids_to_tokens (line 110) | def convert_ids_to_tokens(self, ids): method from_pretrained (line 118) | def from_pretrained(cls, pretrained_model_name, cache_dir=None, *input... class BasicTokenizer (line 156) | class BasicTokenizer(object): method __init__ (line 159) | def __init__(self, do_lower_case=True): method tokenize (line 167) | def tokenize(self, text): method _run_strip_accents (line 188) | def _run_strip_accents(self, text): method _run_split_on_punc (line 199) | def _run_split_on_punc(self, text): method _tokenize_chinese_chars (line 219) | def _tokenize_chinese_chars(self, text): method _is_chinese_char (line 232) | def _is_chinese_char(self, cp): method _clean_text (line 254) | def _clean_text(self, text): class WordpieceTokenizer (line 268) | class WordpieceTokenizer(object): method __init__ (line 271) | def __init__(self, vocab, unk_token="[UNK]", max_input_chars_per_word=... method tokenize (line 276) | def tokenize(self, text): function _is_whitespace (line 328) | def _is_whitespace(char): function _is_control (line 340) | def _is_control(char): function _is_punctuation (line 352) | def _is_punctuation(char): FILE: LAL-Parser/src_joint/pytorch_transformers/__main__.py function main (line 2) | def main(): FILE: LAL-Parser/src_joint/pytorch_transformers/convert_gpt2_checkpoint_to_pytorch.py function convert_gpt2_checkpoint_to_pytorch (line 33) | def convert_gpt2_checkpoint_to_pytorch(gpt2_checkpoint_path, gpt2_config... FILE: LAL-Parser/src_joint/pytorch_transformers/convert_openai_checkpoint_to_pytorch.py function convert_openai_checkpoint_to_pytorch (line 33) | def convert_openai_checkpoint_to_pytorch(openai_checkpoint_folder_path, ... FILE: LAL-Parser/src_joint/pytorch_transformers/convert_pytorch_checkpoint_to_tf.py function convert_pytorch_checkpoint_to_tf (line 26) | def convert_pytorch_checkpoint_to_tf(model:BertModel, ckpt_dir:str, mode... function main (line 95) | def main(raw_args=None): FILE: LAL-Parser/src_joint/pytorch_transformers/convert_roberta_checkpoint_to_pytorch.py function convert_roberta_checkpoint_to_pytorch (line 42) | def convert_roberta_checkpoint_to_pytorch(roberta_checkpoint_path, pytor... FILE: LAL-Parser/src_joint/pytorch_transformers/convert_tf_checkpoint_to_pytorch.py function convert_tf_checkpoint_to_pytorch (line 29) | def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, bert_config_fil... FILE: LAL-Parser/src_joint/pytorch_transformers/convert_transfo_xl_checkpoint_to_pytorch.py function convert_transfo_xl_checkpoint_to_pytorch (line 48) | def convert_transfo_xl_checkpoint_to_pytorch(tf_checkpoint_path, FILE: LAL-Parser/src_joint/pytorch_transformers/convert_xlm_checkpoint_to_pytorch.py function convert_xlm_checkpoint_to_pytorch (line 32) | def convert_xlm_checkpoint_to_pytorch(xlm_checkpoint_path, pytorch_dump_... FILE: LAL-Parser/src_joint/pytorch_transformers/convert_xlnet_checkpoint_to_pytorch.py function convert_xlnet_checkpoint_to_pytorch (line 46) | def convert_xlnet_checkpoint_to_pytorch(tf_checkpoint_path, bert_config_... FILE: LAL-Parser/src_joint/pytorch_transformers/file_utils.py function url_to_filename (line 52) | def url_to_filename(url, etag=None): function filename_to_url (line 70) | def filename_to_url(filename, cache_dir=None): function cached_path (line 96) | def cached_path(url_or_filename, cache_dir=None): function split_s3_path (line 126) | def split_s3_path(url): function s3_request (line 139) | def s3_request(func): function s3_etag (line 159) | def s3_etag(url): function s3_get (line 168) | def s3_get(url, temp_file): function http_get (line 175) | def http_get(url, temp_file): function get_from_cache (line 187) | def get_from_cache(url, cache_dir=None): FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_auto.py class AutoConfig (line 38) | class AutoConfig(object): method __init__ (line 59) | def __init__(self): method from_pretrained (line 64) | def from_pretrained(cls, pretrained_model_name_or_path, **kwargs): class AutoModel (line 133) | class AutoModel(object): method __init__ (line 155) | def __init__(self): method from_pretrained (line 160) | def from_pretrained(cls, pretrained_model_name_or_path, *model_args, *... FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_bert.py function load_tf_weights_in_bert (line 69) | def load_tf_weights_in_bert(model, config, tf_checkpoint_path): function gelu (line 136) | def gelu(x): function swish (line 145) | def swish(x): class BertConfig (line 152) | class BertConfig(PretrainedConfig): method __init__ (line 183) | def __init__(self, class BertLayerNorm (line 227) | class BertLayerNorm(nn.Module): method __init__ (line 228) | def __init__(self, hidden_size, eps=1e-12): method forward (line 236) | def forward(self, x): class BertEmbeddings (line 242) | class BertEmbeddings(nn.Module): method __init__ (line 245) | def __init__(self, config): method forward (line 256) | def forward(self, input_ids, token_type_ids=None, position_ids=None): class BertSelfAttention (line 274) | class BertSelfAttention(nn.Module): method __init__ (line 275) | def __init__(self, config): method transpose_for_scores (line 293) | def transpose_for_scores(self, x): method forward (line 298) | def forward(self, hidden_states, attention_mask, head_mask=None): class BertSelfOutput (line 334) | class BertSelfOutput(nn.Module): method __init__ (line 335) | def __init__(self, config): method forward (line 341) | def forward(self, hidden_states, input_tensor): class BertAttention (line 348) | class BertAttention(nn.Module): method __init__ (line 349) | def __init__(self, config): method prune_heads (line 354) | def prune_heads(self, heads): method forward (line 371) | def forward(self, input_tensor, attention_mask, head_mask=None): class BertIntermediate (line 378) | class BertIntermediate(nn.Module): method __init__ (line 379) | def __init__(self, config): method forward (line 387) | def forward(self, hidden_states): class BertOutput (line 393) | class BertOutput(nn.Module): method __init__ (line 394) | def __init__(self, config): method forward (line 400) | def forward(self, hidden_states, input_tensor): class BertLayer (line 407) | class BertLayer(nn.Module): method __init__ (line 408) | def __init__(self, config): method forward (line 414) | def forward(self, hidden_states, attention_mask, head_mask=None): class BertEncoder (line 423) | class BertEncoder(nn.Module): method __init__ (line 424) | def __init__(self, config): method forward (line 430) | def forward(self, hidden_states, attention_mask, head_mask=None): class BertPooler (line 455) | class BertPooler(nn.Module): method __init__ (line 456) | def __init__(self, config): method forward (line 461) | def forward(self, hidden_states): class BertPredictionHeadTransform (line 470) | class BertPredictionHeadTransform(nn.Module): method __init__ (line 471) | def __init__(self, config): method forward (line 480) | def forward(self, hidden_states): class BertLMPredictionHead (line 487) | class BertLMPredictionHead(nn.Module): method __init__ (line 488) | def __init__(self, config): method forward (line 500) | def forward(self, hidden_states): class BertOnlyMLMHead (line 506) | class BertOnlyMLMHead(nn.Module): method __init__ (line 507) | def __init__(self, config): method forward (line 511) | def forward(self, sequence_output): class BertOnlyNSPHead (line 516) | class BertOnlyNSPHead(nn.Module): method __init__ (line 517) | def __init__(self, config): method forward (line 521) | def forward(self, pooled_output): class BertPreTrainingHeads (line 526) | class BertPreTrainingHeads(nn.Module): method __init__ (line 527) | def __init__(self, config): method forward (line 532) | def forward(self, sequence_output, pooled_output): class BertPreTrainedModel (line 538) | class BertPreTrainedModel(PreTrainedModel): method __init__ (line 547) | def __init__(self, *inputs, **kwargs): method init_weights (line 550) | def init_weights(self, module): class BertModel (line 624) | class BertModel(BertPreTrainedModel): method __init__ (line 653) | def __init__(self, config): method _resize_token_embeddings (line 662) | def _resize_token_embeddings(self, new_num_tokens): method _prune_heads (line 668) | def _prune_heads(self, heads_to_prune): method forward (line 676) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForPreTraining (line 726) | class BertForPreTraining(BertPreTrainedModel): method __init__ (line 763) | def __init__(self, config): method tie_weights (line 772) | def tie_weights(self): method forward (line 779) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForMaskedLM (line 801) | class BertForMaskedLM(BertPreTrainedModel): method __init__ (line 831) | def __init__(self, config): method tie_weights (line 840) | def tie_weights(self): method forward (line 847) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForNextSentencePrediction (line 866) | class BertForNextSentencePrediction(BertPreTrainedModel): method __init__ (line 896) | def __init__(self, config): method forward (line 904) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForSequenceClassification (line 924) | class BertForSequenceClassification(BertPreTrainedModel): method __init__ (line 955) | def __init__(self, config): method forward (line 965) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForMultipleChoice (line 992) | class BertForMultipleChoice(BertPreTrainedModel): method __init__ (line 1060) | def __init__(self, config): method forward (line 1069) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForTokenClassification (line 1098) | class BertForTokenClassification(BertPreTrainedModel): method __init__ (line 1127) | def __init__(self, config): method forward (line 1137) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class BertForQuestionAnswering (line 1165) | class BertForQuestionAnswering(BertPreTrainedModel): method __init__ (line 1202) | def __init__(self, config): method forward (line 1211) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_gpt2.py function load_tf_weights_in_gpt2 (line 45) | def load_tf_weights_in_gpt2(model, config, gpt2_checkpoint_path): function gelu (line 99) | def gelu(x): class GPT2Config (line 103) | class GPT2Config(PretrainedConfig): method __init__ (line 125) | def __init__( method max_position_embeddings (line 200) | def max_position_embeddings(self): method hidden_size (line 204) | def hidden_size(self): method num_attention_heads (line 208) | def num_attention_heads(self): method num_hidden_layers (line 212) | def num_hidden_layers(self): class Attention (line 217) | class Attention(nn.Module): method __init__ (line 218) | def __init__(self, nx, n_ctx, config, scale=False): method prune_heads (line 235) | def prune_heads(self, heads): method _attn (line 251) | def _attn(self, q, k, v, head_mask=None): method merge_heads (line 271) | def merge_heads(self, x): method split_heads (line 276) | def split_heads(self, x, k=False): method forward (line 284) | def forward(self, x, layer_past=None, head_mask=None): class MLP (line 307) | class MLP(nn.Module): method __init__ (line 308) | def __init__(self, n_state, config): # in MLP: n_state=3072 (4 * n_embd) method forward (line 316) | def forward(self, x): class Block (line 322) | class Block(nn.Module): method __init__ (line 323) | def __init__(self, n_ctx, config, scale=False): method forward (line 331) | def forward(self, x, layer_past=None, head_mask=None): class GPT2PreTrainedModel (line 343) | class GPT2PreTrainedModel(PreTrainedModel): method __init__ (line 352) | def __init__(self, *inputs, **kwargs): method init_weights (line 355) | def init_weights(self, module): class GPT2Model (line 417) | class GPT2Model(GPT2PreTrainedModel): method __init__ (line 443) | def __init__(self, config): method _resize_token_embeddings (line 456) | def _resize_token_embeddings(self, new_num_tokens): method _prune_heads (line 460) | def _prune_heads(self, heads_to_prune): method forward (line 467) | def forward(self, input_ids, position_ids=None, token_type_ids=None, p... class GPT2LMHeadModel (line 541) | class GPT2LMHeadModel(GPT2PreTrainedModel): method __init__ (line 576) | def __init__(self, config): method tie_weights (line 584) | def tie_weights(self): method forward (line 591) | def forward(self, input_ids, position_ids=None, token_type_ids=None, l... class GPT2DoubleHeadsModel (line 617) | class GPT2DoubleHeadsModel(GPT2PreTrainedModel): method __init__ (line 694) | def __init__(self, config): method tie_weights (line 702) | def tie_weights(self): method forward (line 709) | def forward(self, input_ids, mc_token_ids=None, lm_labels=None, mc_lab... FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_openai.py function load_tf_weights_in_openai_gpt (line 44) | def load_tf_weights_in_openai_gpt(model, config, openai_checkpoint_folde... function gelu (line 119) | def gelu(x): function swish (line 123) | def swish(x): class OpenAIGPTConfig (line 130) | class OpenAIGPTConfig(PretrainedConfig): method __init__ (line 157) | def __init__( method max_position_embeddings (line 219) | def max_position_embeddings(self): method hidden_size (line 223) | def hidden_size(self): method num_attention_heads (line 227) | def num_attention_heads(self): method num_hidden_layers (line 231) | def num_hidden_layers(self): class Attention (line 235) | class Attention(nn.Module): method __init__ (line 236) | def __init__(self, nx, n_ctx, config, scale=False): method prune_heads (line 253) | def prune_heads(self, heads): method _attn (line 269) | def _attn(self, q, k, v, head_mask=None): method merge_heads (line 290) | def merge_heads(self, x): method split_heads (line 295) | def split_heads(self, x, k=False): method forward (line 303) | def forward(self, x, head_mask=None): class MLP (line 321) | class MLP(nn.Module): method __init__ (line 322) | def __init__(self, n_state, config): # in MLP: n_state=3072 (4 * n_embd) method forward (line 330) | def forward(self, x): class Block (line 336) | class Block(nn.Module): method __init__ (line 337) | def __init__(self, n_ctx, config, scale=False): method forward (line 345) | def forward(self, x, head_mask=None): class OpenAIGPTPreTrainedModel (line 357) | class OpenAIGPTPreTrainedModel(PreTrainedModel): method __init__ (line 366) | def __init__(self, *inputs, **kwargs): method init_weights (line 369) | def init_weights(self, module): class OpenAIGPTModel (line 427) | class OpenAIGPTModel(OpenAIGPTPreTrainedModel): method __init__ (line 449) | def __init__(self, config): method _resize_token_embeddings (line 461) | def _resize_token_embeddings(self, new_num_tokens): method _prune_heads (line 465) | def _prune_heads(self, heads_to_prune): method forward (line 472) | def forward(self, input_ids, position_ids=None, token_type_ids=None, h... class OpenAIGPTLMHeadModel (line 536) | class OpenAIGPTLMHeadModel(OpenAIGPTPreTrainedModel): method __init__ (line 567) | def __init__(self, config): method tie_weights (line 575) | def tie_weights(self): method forward (line 582) | def forward(self, input_ids, position_ids=None, token_type_ids=None, l... class OpenAIGPTDoubleHeadsModel (line 607) | class OpenAIGPTDoubleHeadsModel(OpenAIGPTPreTrainedModel): method __init__ (line 676) | def __init__(self, config): method tie_weights (line 686) | def tie_weights(self): method forward (line 693) | def forward(self, input_ids, mc_token_ids=None, lm_labels=None, mc_lab... FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_roberta.py class RobertaEmbeddings (line 49) | class RobertaEmbeddings(BertEmbeddings): method __init__ (line 53) | def __init__(self, config): method forward (line 57) | def forward(self, input_ids, token_type_ids=None, position_ids=None): class RobertaConfig (line 67) | class RobertaConfig(BertConfig): class RobertaModel (line 129) | class RobertaModel(BertModel): method __init__ (line 162) | def __init__(self, config): method forward (line 168) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class RobertaForMaskedLM (line 178) | class RobertaForMaskedLM(BertPreTrainedModel): method __init__ (line 212) | def __init__(self, config): method tie_weights (line 221) | def tie_weights(self): method forward (line 227) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class RobertaLMHead (line 244) | class RobertaLMHead(nn.Module): method __init__ (line 247) | def __init__(self, config): method forward (line 255) | def forward(self, features, **kwargs): class RobertaForSequenceClassification (line 269) | class RobertaForSequenceClassification(BertPreTrainedModel): method __init__ (line 304) | def __init__(self, config): method forward (line 311) | def forward(self, input_ids, token_type_ids=None, attention_mask=None,... class RobertaClassificationHead (line 333) | class RobertaClassificationHead(nn.Module): method __init__ (line 336) | def __init__(self, config): method forward (line 342) | def forward(self, features, **kwargs): FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_transfo_xl.py function build_tf_to_pytorch_map (line 50) | def build_tf_to_pytorch_map(model, config): function load_tf_weights_in_transfo_xl (line 122) | def load_tf_weights_in_transfo_xl(model, config, tf_path): class TransfoXLConfig (line 178) | class TransfoXLConfig(PretrainedConfig): method __init__ (line 215) | def __init__(self, method max_position_embeddings (line 291) | def max_position_embeddings(self): method vocab_size (line 295) | def vocab_size(self): method vocab_size (line 299) | def vocab_size(self, value): method hidden_size (line 303) | def hidden_size(self): method num_attention_heads (line 307) | def num_attention_heads(self): method num_hidden_layers (line 311) | def num_hidden_layers(self): class PositionalEmbedding (line 315) | class PositionalEmbedding(nn.Module): method __init__ (line 316) | def __init__(self, demb): method forward (line 324) | def forward(self, pos_seq, bsz=None): class PositionwiseFF (line 335) | class PositionwiseFF(nn.Module): method __init__ (line 336) | def __init__(self, d_model, d_inner, dropout, pre_lnorm=False): method forward (line 354) | def forward(self, inp): class MultiHeadAttn (line 372) | class MultiHeadAttn(nn.Module): method __init__ (line 373) | def __init__(self, n_head, d_model, d_head, dropout, dropatt=0, method forward (line 403) | def forward(self, h, attn_mask=None, mems=None, head_mask=None): class RelMultiHeadAttn (line 461) | class RelMultiHeadAttn(nn.Module): method __init__ (line 462) | def __init__(self, n_head, d_model, d_head, dropout, dropatt=0, method _parallelogram_mask (line 492) | def _parallelogram_mask(self, h, w, left=False): method _shift (line 503) | def _shift(self, x, qlen, klen, mask, left=False): method _rel_shift (line 521) | def _rel_shift(self, x, zero_triu=False): method forward (line 537) | def forward(self, w, r, attn_mask=None, mems=None): class RelPartialLearnableMultiHeadAttn (line 540) | class RelPartialLearnableMultiHeadAttn(RelMultiHeadAttn): method __init__ (line 541) | def __init__(self, *args, **kwargs): method forward (line 546) | def forward(self, w, r, attn_mask=None, mems=None, head_mask=None): class RelLearnableMultiHeadAttn (line 628) | class RelLearnableMultiHeadAttn(RelMultiHeadAttn): method __init__ (line 629) | def __init__(self, *args, **kwargs): method forward (line 632) | def forward(self, w, r_emb, r_w_bias, r_bias, attn_mask=None, mems=Non... class DecoderLayer (line 721) | class DecoderLayer(nn.Module): method __init__ (line 722) | def __init__(self, n_head, d_model, d_head, d_inner, dropout, **kwargs): method forward (line 729) | def forward(self, dec_inp, dec_attn_mask=None, mems=None, head_mask=No... class RelLearnableDecoderLayer (line 739) | class RelLearnableDecoderLayer(nn.Module): method __init__ (line 740) | def __init__(self, n_head, d_model, d_head, d_inner, dropout, method forward (line 749) | def forward(self, dec_inp, r_emb, r_w_bias, r_bias, dec_attn_mask=None... class RelPartialLearnableDecoderLayer (line 760) | class RelPartialLearnableDecoderLayer(nn.Module): method __init__ (line 761) | def __init__(self, n_head, d_model, d_head, d_inner, dropout, method forward (line 770) | def forward(self, dec_inp, r, dec_attn_mask=None, mems=None, head_mask... class AdaptiveEmbedding (line 783) | class AdaptiveEmbedding(nn.Module): method __init__ (line 784) | def __init__(self, n_token, d_embed, d_proj, cutoffs, div_val=1, method forward (line 814) | def forward(self, inp): class TransfoXLPreTrainedModel (line 847) | class TransfoXLPreTrainedModel(PreTrainedModel): method __init__ (line 856) | def __init__(self, *inputs, **kwargs): method _init_weight (line 859) | def _init_weight(self, weight): method _init_bias (line 865) | def _init_bias(self, bias): method init_weights (line 868) | def init_weights(self, m): method set_num_special_tokens (line 909) | def set_num_special_tokens(self, num_special_tokens): class TransfoXLModel (line 952) | class TransfoXLModel(TransfoXLPreTrainedModel): method __init__ (line 978) | def __init__(self, config): method _resize_token_embeddings (line 1060) | def _resize_token_embeddings(self, new_num_tokens): method backward_compatible (line 1063) | def backward_compatible(self): method reset_length (line 1066) | def reset_length(self, tgt_len, ext_len, mem_len): method _prune_heads (line 1071) | def _prune_heads(self, heads): method init_mems (line 1075) | def init_mems(self, data): method _update_mems (line 1088) | def _update_mems(self, hids, mems, qlen, mlen): method _forward (line 1111) | def _forward(self, dec_inp, mems=None, head_mask=None): method forward (line 1242) | def forward(self, input_ids, mems=None, head_mask=None): class TransfoXLLMHeadModel (line 1257) | class TransfoXLLMHeadModel(TransfoXLPreTrainedModel): method __init__ (line 1293) | def __init__(self, config): method tie_weights (line 1308) | def tie_weights(self): method reset_length (line 1335) | def reset_length(self, tgt_len, ext_len, mem_len): method init_mems (line 1338) | def init_mems(self, data): method forward (line 1341) | def forward(self, input_ids, labels=None, mems=None, head_mask=None): FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_transfo_xl_utilities.py class ProjectedAdaptiveLogSoftmax (line 31) | class ProjectedAdaptiveLogSoftmax(nn.Module): method __init__ (line 32) | def __init__(self, n_token, d_embed, d_proj, cutoffs, div_val=1, method _compute_logit (line 78) | def _compute_logit(self, hidden, weight, bias, proj): method forward (line 92) | def forward(self, hidden, labels=None, keep_order=False): method log_prob (line 198) | def log_prob(self, hidden): class LogUniformSampler (line 260) | class LogUniformSampler(object): method __init__ (line 261) | def __init__(self, range_max, n_sample): method sample (line 280) | def sample(self, labels): function sample_logits (line 301) | def sample_logits(embedding, bias, labels, inputs, sampler): FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_utils.py class Identity (line 46) | class Identity(nn.Module): method __init__ (line 49) | def __init__(self, *args, **kwargs): method forward (line 52) | def forward(self, input): function add_start_docstrings (line 57) | def add_start_docstrings(*docstr): function add_start_docstrings (line 64) | def add_start_docstrings(*docstr): class PretrainedConfig (line 70) | class PretrainedConfig(object): method __init__ (line 86) | def __init__(self, **kwargs): method save_pretrained (line 93) | def save_pretrained(self, save_directory): method from_pretrained (line 105) | def from_pretrained(cls, pretrained_model_name_or_path, **kwargs): method from_dict (line 195) | def from_dict(cls, json_object): method from_json_file (line 203) | def from_json_file(cls, json_file): method __eq__ (line 209) | def __eq__(self, other): method __repr__ (line 212) | def __repr__(self): method to_dict (line 215) | def to_dict(self): method to_json_string (line 220) | def to_json_string(self): method to_json_file (line 224) | def to_json_file(self, json_file_path): class PreTrainedModel (line 230) | class PreTrainedModel(nn.Module): method __init__ (line 252) | def __init__(self, config, *inputs, **kwargs): method _get_resized_embeddings (line 264) | def _get_resized_embeddings(self, old_embeddings, new_num_tokens=None): method _tie_or_clone_weights (line 298) | def _tie_or_clone_weights(self, first_module, second_module): method resize_token_embeddings (line 306) | def resize_token_embeddings(self, new_num_tokens=None): method prune_heads (line 334) | def prune_heads(self, heads_to_prune): method save_pretrained (line 344) | def save_pretrained(self, save_directory): method from_pretrained (line 362) | def from_pretrained(cls, pretrained_model_name_or_path, *model_args, *... class Conv1D (line 547) | class Conv1D(nn.Module): method __init__ (line 548) | def __init__(self, nf, nx): method forward (line 559) | def forward(self, x): class PoolerStartLogits (line 566) | class PoolerStartLogits(nn.Module): method __init__ (line 568) | def __init__(self, config): method forward (line 572) | def forward(self, hidden_states, p_mask=None): class PoolerEndLogits (line 586) | class PoolerEndLogits(nn.Module): method __init__ (line 589) | def __init__(self, config): method forward (line 596) | def forward(self, hidden_states, start_states=None, start_positions=No... class PoolerAnswerClass (line 627) | class PoolerAnswerClass(nn.Module): method __init__ (line 629) | def __init__(self, config): method forward (line 635) | def forward(self, hidden_states, start_states=None, start_positions=No... class SQuADHead (line 671) | class SQuADHead(nn.Module): method __init__ (line 711) | def __init__(self, config): method forward (line 720) | def forward(self, hidden_states, start_positions=None, end_positions=N... class SequenceSummary (line 780) | class SequenceSummary(nn.Module): method __init__ (line 795) | def __init__(self, config): method forward (line 825) | def forward(self, hidden_states, cls_index=None): function prune_linear_layer (line 857) | def prune_linear_layer(layer, index, dim=0): function prune_conv1d_layer (line 882) | def prune_conv1d_layer(layer, index, dim=1): function prune_layer (line 906) | def prune_layer(layer, index, dim=None): FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_xlm.py class XLMConfig (line 60) | class XLMConfig(PretrainedConfig): method __init__ (line 105) | def __init__(self, method vocab_size (line 184) | def vocab_size(self): method vocab_size (line 188) | def vocab_size(self, value): method hidden_size (line 192) | def hidden_size(self): method num_attention_heads (line 196) | def num_attention_heads(self): method num_hidden_layers (line 200) | def num_hidden_layers(self): function create_sinusoidal_embeddings (line 204) | def create_sinusoidal_embeddings(n_pos, dim, out): function gelu (line 215) | def gelu(x): function get_masks (line 226) | def get_masks(slen, lengths, causal, padding_mask=None): class MultiHeadAttention (line 251) | class MultiHeadAttention(nn.Module): method __init__ (line 255) | def __init__(self, n_heads, dim, config): method prune_heads (line 269) | def prune_heads(self, heads): method forward (line 287) | def forward(self, input, mask, kv=None, cache=None, head_mask=None): class TransformerFFN (line 351) | class TransformerFFN(nn.Module): method __init__ (line 353) | def __init__(self, in_dim, dim_hidden, out_dim, config): method forward (line 360) | def forward(self, input): class XLMPreTrainedModel (line 368) | class XLMPreTrainedModel(PreTrainedModel): method __init__ (line 377) | def __init__(self, *inputs, **kwargs): method init_weights (line 380) | def init_weights(self, module): class XLMModel (line 460) | class XLMModel(XLMPreTrainedModel): method __init__ (line 487) | def __init__(self, config): #, dico, is_encoder, with_output): method _resize_token_embeddings (line 549) | def _resize_token_embeddings(self, new_num_tokens): method _prune_heads (line 553) | def _prune_heads(self, heads_to_prune): method forward (line 561) | def forward(self, input_ids, lengths=None, position_ids=None, langs=None, class XLMPredLayer (line 678) | class XLMPredLayer(nn.Module): method __init__ (line 682) | def __init__(self, config): method forward (line 700) | def forward(self, x, y=None): class XLMWithLMHeadModel (line 723) | class XLMWithLMHeadModel(XLMPreTrainedModel): method __init__ (line 754) | def __init__(self, config): method tie_weights (line 762) | def tie_weights(self): method forward (line 767) | def forward(self, input_ids, lengths=None, position_ids=None, langs=No... class XLMForSequenceClassification (line 783) | class XLMForSequenceClassification(XLMPreTrainedModel): method __init__ (line 814) | def __init__(self, config): method forward (line 823) | def forward(self, input_ids, lengths=None, position_ids=None, langs=No... class XLMForQuestionAnswering (line 850) | class XLMForQuestionAnswering(XLMPreTrainedModel): method __init__ (line 893) | def __init__(self, config): method forward (line 901) | def forward(self, input_ids, lengths=None, position_ids=None, langs=No... FILE: LAL-Parser/src_joint/pytorch_transformers/modeling_xlnet.py function build_tf_xlnet_to_pytorch_map (line 49) | def build_tf_xlnet_to_pytorch_map(model, config, tf_weights=None): function load_tf_weights_in_xlnet (line 119) | def load_tf_weights_in_xlnet(model, config, tf_path): function gelu (line 179) | def gelu(x): function swish (line 188) | def swish(x): class XLNetConfig (line 195) | class XLNetConfig(PretrainedConfig): method __init__ (line 238) | def __init__(self, method max_position_embeddings (line 312) | def max_position_embeddings(self): method vocab_size (line 316) | def vocab_size(self): method vocab_size (line 320) | def vocab_size(self, value): method hidden_size (line 324) | def hidden_size(self): method num_attention_heads (line 328) | def num_attention_heads(self): method num_hidden_layers (line 332) | def num_hidden_layers(self): class XLNetLayerNorm (line 340) | class XLNetLayerNorm(nn.Module): method __init__ (line 341) | def __init__(self, d_model, eps=1e-12): method forward (line 349) | def forward(self, x): class XLNetRelativeAttention (line 355) | class XLNetRelativeAttention(nn.Module): method __init__ (line 356) | def __init__(self, config): method prune_heads (line 384) | def prune_heads(self, heads): method rel_shift (line 388) | def rel_shift(x, klen=-1): method rel_attn_core (line 400) | def rel_attn_core(self, q_head, k_head_h, v_head_h, k_head_r, seg_mat=... method post_attention (line 439) | def post_attention(self, h, attn_vec, residual=True): method forward (line 451) | def forward(self, h, g, class XLNetFeedForward (line 544) | class XLNetFeedForward(nn.Module): method __init__ (line 545) | def __init__(self, config): method forward (line 557) | def forward(self, inp): class XLNetLayer (line 567) | class XLNetLayer(nn.Module): method __init__ (line 568) | def __init__(self, config): method forward (line 574) | def forward(self, output_h, output_g, class XLNetPreTrainedModel (line 590) | class XLNetPreTrainedModel(PreTrainedModel): method __init__ (line 599) | def __init__(self, *inputs, **kwargs): method init_weights (line 602) | def init_weights(self, module): class XLNetModel (line 696) | class XLNetModel(XLNetPreTrainedModel): method __init__ (line 722) | def __init__(self, config): method _resize_token_embeddings (line 743) | def _resize_token_embeddings(self, new_num_tokens): method _prune_heads (line 747) | def _prune_heads(self, heads_to_prune): method create_mask (line 750) | def create_mask(self, qlen, mlen): method cache_mem (line 780) | def cache_mem(self, curr_out, prev_mem): method positional_embedding (line 796) | def positional_embedding(pos_seq, inv_freq, bsz=None): method relative_positional_encoding (line 806) | def relative_positional_encoding(self, qlen, klen, bsz=None): method forward (line 845) | def forward(self, input_ids, token_type_ids=None, input_mask=None, att... class XLNetLMHeadModel (line 993) | class XLNetLMHeadModel(XLNetPreTrainedModel): method __init__ (line 1033) | def __init__(self, config): method tie_weights (line 1044) | def tie_weights(self): method forward (line 1049) | def forward(self, input_ids, token_type_ids=None, input_mask=None, att... class XLNetForSequenceClassification (line 1074) | class XLNetForSequenceClassification(XLNetPreTrainedModel): method __init__ (line 1109) | def __init__(self, config): method forward (line 1119) | def forward(self, input_ids, token_type_ids=None, input_mask=None, att... class XLNetForQuestionAnswering (line 1149) | class XLNetForQuestionAnswering(XLNetPreTrainedModel): method __init__ (line 1208) | def __init__(self, config): method forward (line 1220) | def forward(self, input_ids, token_type_ids=None, input_mask=None, att... FILE: LAL-Parser/src_joint/pytorch_transformers/optimization.py class ConstantLRSchedule (line 26) | class ConstantLRSchedule(LambdaLR): method __init__ (line 29) | def __init__(self, optimizer, last_epoch=-1): class WarmupConstantSchedule (line 33) | class WarmupConstantSchedule(LambdaLR): method __init__ (line 38) | def __init__(self, optimizer, warmup_steps, last_epoch=-1): method lr_lambda (line 42) | def lr_lambda(self, step): class WarmupLinearSchedule (line 48) | class WarmupLinearSchedule(LambdaLR): method __init__ (line 53) | def __init__(self, optimizer, warmup_steps, t_total, last_epoch=-1): method lr_lambda (line 58) | def lr_lambda(self, step): class WarmupCosineSchedule (line 64) | class WarmupCosineSchedule(LambdaLR): method __init__ (line 70) | def __init__(self, optimizer, warmup_steps, t_total, cycles=.5, last_e... method lr_lambda (line 76) | def lr_lambda(self, step): class WarmupCosineWithHardRestartsSchedule (line 84) | class WarmupCosineWithHardRestartsSchedule(LambdaLR): method __init__ (line 90) | def __init__(self, optimizer, warmup_steps, t_total, cycles=1., last_e... method lr_lambda (line 96) | def lr_lambda(self, step): class AdamW (line 107) | class AdamW(Optimizer): method __init__ (line 117) | def __init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-6, weig... method step (line 130) | def step(self, closure=None): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/conftest.py function pytest_addoption (line 6) | def pytest_addoption(parser): function pytest_collection_modifyitems (line 12) | def pytest_collection_modifyitems(config, items): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_auto_test.py class AutoModelTest (line 30) | class AutoModelTest(unittest.TestCase): method test_model_from_pretrained (line 31) | def test_model_from_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_bert_test.py class BertModelTest (line 32) | class BertModelTest(CommonTestCases.CommonModelTester): class BertModelTester (line 38) | class BertModelTester(object): method __init__ (line 40) | def __init__(self, method prepare_config_and_inputs (line 87) | def prepare_config_and_inputs(self): method check_loss_output (line 121) | def check_loss_output(self, result): method create_and_check_bert_model (line 126) | def create_and_check_bert_model(self, config, input_ids, token_type_... method create_and_check_bert_for_masked_lm (line 143) | def create_and_check_bert_for_masked_lm(self, config, input_ids, tok... method create_and_check_bert_for_next_sequence_prediction (line 156) | def create_and_check_bert_for_next_sequence_prediction(self, config,... method create_and_check_bert_for_pretraining (line 170) | def create_and_check_bert_for_pretraining(self, config, input_ids, t... method create_and_check_bert_for_question_answering (line 188) | def create_and_check_bert_for_question_answering(self, config, input... method create_and_check_bert_for_sequence_classification (line 206) | def create_and_check_bert_for_sequence_classification(self, config, ... method create_and_check_bert_for_token_classification (line 221) | def create_and_check_bert_for_token_classification(self, config, inp... method create_and_check_bert_for_multiple_choice (line 236) | def create_and_check_bert_for_multiple_choice(self, config, input_id... method prepare_config_and_inputs_for_common (line 257) | def prepare_config_and_inputs_for_common(self): method setUp (line 264) | def setUp(self): method test_config (line 268) | def test_config(self): method test_bert_model (line 271) | def test_bert_model(self): method test_for_masked_lm (line 275) | def test_for_masked_lm(self): method test_for_multiple_choice (line 279) | def test_for_multiple_choice(self): method test_for_next_sequence_prediction (line 283) | def test_for_next_sequence_prediction(self): method test_for_pretraining (line 287) | def test_for_pretraining(self): method test_for_question_answering (line 291) | def test_for_question_answering(self): method test_for_sequence_classification (line 295) | def test_for_sequence_classification(self): method test_for_token_classification (line 299) | def test_for_token_classification(self): method test_model_from_pretrained (line 304) | def test_model_from_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_common_test.py function _config_zero_init (line 35) | def _config_zero_init(config): class CommonTestCases (line 42) | class CommonTestCases: class CommonModelTester (line 44) | class CommonModelTester(unittest.TestCase): method test_initialization (line 52) | def test_initialization(self): method test_attention_outputs (line 63) | def test_attention_outputs(self): method test_torchscript (line 101) | def test_torchscript(self): method test_torchscript_output_attentions (line 106) | def test_torchscript_output_attentions(self): method test_torchscript_output_hidden_state (line 112) | def test_torchscript_output_hidden_state(self): method _create_and_check_torchscript (line 118) | def _create_and_check_torchscript(self, config, inputs_dict): method test_headmasking (line 160) | def test_headmasking(self): method test_head_pruning (line 206) | def test_head_pruning(self): method test_hidden_states_output (line 232) | def test_hidden_states_output(self): method test_resize_tokens_embeddings (line 249) | def test_resize_tokens_embeddings(self): method test_tie_model_weights (line 283) | def test_tie_model_weights(self): class GPTModelTester (line 334) | class GPTModelTester(CommonModelTester): method __init__ (line 336) | def __init__(self, method prepare_config_and_inputs (line 382) | def prepare_config_and_inputs(self): method create_and_check_base_model (line 414) | def create_and_check_base_model(self, config, input_ids, token_type_... method create_and_check_lm_head (line 429) | def create_and_check_lm_head(self, config, input_ids, token_type_ids... method create_and_check_presents (line 444) | def create_and_check_presents(self, config, input_ids, token_type_id... method create_and_check_double_heads (line 457) | def create_and_check_double_heads(self, config, input_ids, token_typ... method create_and_check_model_from_pretrained (line 477) | def create_and_check_model_from_pretrained(self): method prepare_config_and_inputs_for_common (line 484) | def prepare_config_and_inputs_for_common(self): method run_common_tests (line 491) | def run_common_tests(self, test_presents=False): method run_slow_tests (line 505) | def run_slow_tests(self): class ConfigTester (line 509) | class ConfigTester(object): method __init__ (line 510) | def __init__(self, parent, config_class=None, **kwargs): method create_and_test_config_common_properties (line 515) | def create_and_test_config_common_properties(self): method create_and_test_config_to_json_string (line 522) | def create_and_test_config_to_json_string(self): method create_and_test_config_to_json_file (line 528) | def create_and_test_config_to_json_file(self): method run_common_tests (line 536) | def run_common_tests(self): function ids_tensor (line 544) | def ids_tensor(shape, vocab_size, rng=None, name=None): class ModelUtilsTest (line 560) | class ModelUtilsTest(unittest.TestCase): method test_model_from_pretrained (line 561) | def test_model_from_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_gpt2_test.py class GPT2ModelTest (line 28) | class GPT2ModelTest(unittest.TestCase): method test_config (line 30) | def test_config(self): method test_model (line 34) | def test_model(self): method test_pretrained (line 41) | def test_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_openai_test.py class OpenAIModelTest (line 28) | class OpenAIModelTest(unittest.TestCase): method test_config (line 30) | def test_config(self): method test_model (line 34) | def test_model(self): method test_pretrained (line 41) | def test_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_roberta_test.py class RobertaModelTest (line 30) | class RobertaModelTest(CommonTestCases.CommonModelTester): class RobertaModelTester (line 34) | class RobertaModelTester(object): method __init__ (line 36) | def __init__(self, method prepare_config_and_inputs (line 83) | def prepare_config_and_inputs(self): method check_loss_output (line 117) | def check_loss_output(self, result): method create_and_check_roberta_model (line 122) | def create_and_check_roberta_model(self, config, input_ids, token_ty... method create_and_check_roberta_for_masked_lm (line 139) | def create_and_check_roberta_for_masked_lm(self, config, input_ids, ... method prepare_config_and_inputs_for_common (line 153) | def prepare_config_and_inputs_for_common(self): method setUp (line 160) | def setUp(self): method test_config (line 164) | def test_config(self): method test_roberta_model (line 167) | def test_roberta_model(self): method test_for_masked_lm (line 171) | def test_for_masked_lm(self): method test_model_from_pretrained (line 176) | def test_model_from_pretrained(self): class RobertaModelIntegrationTest (line 185) | class RobertaModelIntegrationTest(unittest.TestCase): method test_inference_masked_lm (line 188) | def test_inference_masked_lm(self): method test_inference_no_head (line 209) | def test_inference_no_head(self): method test_inference_classification_head (line 225) | def test_inference_classification_head(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_transfo_xl_test.py class TransfoXLModelTest (line 33) | class TransfoXLModelTest(CommonTestCases.CommonModelTester): class TransfoXLModelTester (line 40) | class TransfoXLModelTester(object): method __init__ (line 42) | def __init__(self, method prepare_config_and_inputs (line 82) | def prepare_config_and_inputs(self): method set_seed (line 105) | def set_seed(self): method create_transfo_xl_model (line 109) | def create_transfo_xl_model(self, config, input_ids_1, input_ids_2, ... method check_transfo_xl_model_output (line 123) | def check_transfo_xl_model_output(self, result): method create_transfo_xl_lm_head (line 138) | def create_transfo_xl_lm_head(self, config, input_ids_1, input_ids_2... method check_transfo_xl_lm_head_output (line 157) | def check_transfo_xl_lm_head_output(self, result): method prepare_config_and_inputs_for_common (line 178) | def prepare_config_and_inputs_for_common(self): method setUp (line 185) | def setUp(self): method test_config (line 189) | def test_config(self): method test_transfo_xl_model (line 192) | def test_transfo_xl_model(self): method test_transfo_xl_lm_head (line 198) | def test_transfo_xl_lm_head(self): method test_model_from_pretrained (line 205) | def test_model_from_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_xlm_test.py class XLMModelTest (line 29) | class XLMModelTest(CommonTestCases.CommonModelTester): class XLMModelTester (line 35) | class XLMModelTester(object): method __init__ (line 37) | def __init__(self, method prepare_config_and_inputs (line 97) | def prepare_config_and_inputs(self): method check_loss_output (line 137) | def check_loss_output(self, result): method create_and_check_xlm_model (line 142) | def create_and_check_xlm_model(self, config, input_ids, token_type_i... method create_and_check_xlm_lm_head (line 157) | def create_and_check_xlm_lm_head(self, config, input_ids, token_type... method create_and_check_xlm_qa (line 176) | def create_and_check_xlm_qa(self, config, input_ids, token_type_ids,... method create_and_check_xlm_sequence_classif (line 230) | def create_and_check_xlm_sequence_classif(self, config, input_ids, t... method prepare_config_and_inputs_for_common (line 250) | def prepare_config_and_inputs_for_common(self): method setUp (line 257) | def setUp(self): method test_config (line 261) | def test_config(self): method test_xlm_model (line 264) | def test_xlm_model(self): method test_model_from_pretrained (line 284) | def test_model_from_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/modeling_xlnet_test.py class XLNetModelTest (line 33) | class XLNetModelTest(CommonTestCases.CommonModelTester): class XLNetModelTester (line 39) | class XLNetModelTester(object): method __init__ (line 41) | def __init__(self, method prepare_config_and_inputs (line 89) | def prepare_config_and_inputs(self): method set_seed (line 128) | def set_seed(self): method create_and_check_xlnet_base_model (line 132) | def create_and_check_xlnet_base_model(self, config, input_ids_1, inp... method create_and_check_xlnet_lm_head (line 154) | def create_and_check_xlnet_lm_head(self, config, input_ids_1, input_... method create_and_check_xlnet_qa (line 194) | def create_and_check_xlnet_qa(self, config, input_ids_1, input_ids_2... method create_and_check_xlnet_sequence_classif (line 252) | def create_and_check_xlnet_sequence_classif(self, config, input_ids_... method prepare_config_and_inputs_for_common (line 276) | def prepare_config_and_inputs_for_common(self): method setUp (line 285) | def setUp(self): method test_config (line 289) | def test_config(self): method test_xlnet_base_model (line 292) | def test_xlnet_base_model(self): method test_xlnet_lm_head (line 297) | def test_xlnet_lm_head(self): method test_xlnet_sequence_classif (line 302) | def test_xlnet_sequence_classif(self): method test_xlnet_qa (line 307) | def test_xlnet_qa(self): method test_model_from_pretrained (line 313) | def test_model_from_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/optimization_test.py function unwrap_schedule (line 30) | def unwrap_schedule(scheduler, num_steps=10): function unwrap_and_save_reload_schedule (line 37) | def unwrap_and_save_reload_schedule(scheduler, num_steps=10): class OptimizationTest (line 51) | class OptimizationTest(unittest.TestCase): method assertListAlmostEqual (line 53) | def assertListAlmostEqual(self, list1, list2, tol): method test_adam_w (line 58) | def test_adam_w(self): class ScheduleInitTest (line 73) | class ScheduleInitTest(unittest.TestCase): method assertListAlmostEqual (line 78) | def assertListAlmostEqual(self, list1, list2, tol): method test_constant_scheduler (line 83) | def test_constant_scheduler(self): method test_warmup_constant_scheduler (line 94) | def test_warmup_constant_scheduler(self): method test_warmup_linear_scheduler (line 105) | def test_warmup_linear_scheduler(self): method test_warmup_cosine_scheduler (line 116) | def test_warmup_cosine_scheduler(self): method test_warmup_cosine_hard_restart_scheduler (line 127) | def test_warmup_cosine_hard_restart_scheduler(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_auto_test.py class AutoTokenizerTest (line 29) | class AutoTokenizerTest(unittest.TestCase): method test_tokenizer_from_pretrained (line 30) | def test_tokenizer_from_pretrained(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_bert_test.py class BertTokenizationTest (line 29) | class BertTokenizationTest(CommonTestCases.CommonTokenizerTester): method setUp (line 33) | def setUp(self): method get_tokenizer (line 44) | def get_tokenizer(self): method get_input_output_texts (line 47) | def get_input_output_texts(self): method test_full_tokenizer (line 52) | def test_full_tokenizer(self): method test_chinese (line 59) | def test_chinese(self): method test_basic_tokenizer_lower (line 66) | def test_basic_tokenizer_lower(self): method test_basic_tokenizer_no_lower (line 74) | def test_basic_tokenizer_no_lower(self): method test_wordpiece_tokenizer (line 81) | def test_wordpiece_tokenizer(self): method test_is_whitespace (line 101) | def test_is_whitespace(self): method test_is_control (line 111) | def test_is_control(self): method test_is_punctuation (line 119) | def test_is_punctuation(self): method test_sequence_builders (line 128) | def test_sequence_builders(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_gpt2_test.py class GPT2TokenizationTest (line 25) | class GPT2TokenizationTest(CommonTestCases.CommonTokenizerTester): method setUp (line 29) | def setUp(self): method get_tokenizer (line 47) | def get_tokenizer(self): method get_input_output_texts (line 50) | def get_input_output_texts(self): method test_full_tokenizer (line 55) | def test_full_tokenizer(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_openai_test.py class OpenAIGPTTokenizationTest (line 26) | class OpenAIGPTTokenizationTest(CommonTestCases.CommonTokenizerTester): method setUp (line 30) | def setUp(self): method get_tokenizer (line 48) | def get_tokenizer(self): method get_input_output_texts (line 51) | def get_input_output_texts(self): method test_full_tokenizer (line 57) | def test_full_tokenizer(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_roberta_test.py class RobertaTokenizationTest (line 25) | class RobertaTokenizationTest(CommonTestCases.CommonTokenizerTester): method setUp (line 28) | def setUp(self): method get_tokenizer (line 46) | def get_tokenizer(self): method get_input_output_texts (line 49) | def get_input_output_texts(self): method test_full_tokenizer (line 54) | def test_full_tokenizer(self): method roberta_dict_integration_testing (line 66) | def roberta_dict_integration_testing(self): method test_sequence_builders (line 78) | def test_sequence_builders(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_tests_commons.py class TemporaryDirectory (line 27) | class TemporaryDirectory(object): method __enter__ (line 29) | def __enter__(self): method __exit__ (line 32) | def __exit__(self, exc_type, exc_value, traceback): class CommonTestCases (line 40) | class CommonTestCases: class CommonTokenizerTester (line 42) | class CommonTokenizerTester(unittest.TestCase): method setUp (line 46) | def setUp(self): method tearDown (line 49) | def tearDown(self): method get_tokenizer (line 52) | def get_tokenizer(self): method get_input_output_texts (line 55) | def get_input_output_texts(self): method test_save_and_load_tokenizer (line 58) | def test_save_and_load_tokenizer(self): method test_pickle_tokenizer (line 70) | def test_pickle_tokenizer(self): method test_add_tokens_tokenizer (line 89) | def test_add_tokens_tokenizer(self): method test_required_methods_tokenizer (line 135) | def test_required_methods_tokenizer(self): method test_pretrained_model_lists (line 153) | def test_pretrained_model_lists(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_transfo_xl_test.py class TransfoXLTokenizationTest (line 25) | class TransfoXLTokenizationTest(CommonTestCases.CommonTokenizerTester): method setUp (line 29) | def setUp(self): method get_tokenizer (line 40) | def get_tokenizer(self): method get_input_output_texts (line 43) | def get_input_output_texts(self): method test_full_tokenizer (line 48) | def test_full_tokenizer(self): method test_full_tokenizer_lower (line 57) | def test_full_tokenizer_lower(self): method test_full_tokenizer_no_lower (line 64) | def test_full_tokenizer_no_lower(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_utils_test.py class TokenizerUtilsTest (line 25) | class TokenizerUtilsTest(unittest.TestCase): method check_tokenizer_from_pretrained (line 26) | def check_tokenizer_from_pretrained(self, tokenizer_class): method test_pretrained_tokenizers (line 42) | def test_pretrained_tokenizers(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_xlm_test.py class XLMTokenizationTest (line 25) | class XLMTokenizationTest(CommonTestCases.CommonTokenizerTester): method setUp (line 29) | def setUp(self): method get_tokenizer (line 47) | def get_tokenizer(self): method get_input_output_texts (line 50) | def get_input_output_texts(self): method test_full_tokenizer (line 55) | def test_full_tokenizer(self): method test_sequence_builders (line 69) | def test_sequence_builders(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tests/tokenization_xlnet_test.py class XLNetTokenizationTest (line 27) | class XLNetTokenizationTest(CommonTestCases.CommonTokenizerTester): method setUp (line 31) | def setUp(self): method get_tokenizer (line 38) | def get_tokenizer(self): method get_input_output_texts (line 41) | def get_input_output_texts(self): method test_full_tokenizer (line 47) | def test_full_tokenizer(self): method test_tokenizer_lower (line 75) | def test_tokenizer_lower(self): method test_tokenizer_no_lower (line 84) | def test_tokenizer_no_lower(self): method test_sequence_builders (line 92) | def test_sequence_builders(self): FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_auto.py class AutoTokenizer (line 31) | class AutoTokenizer(object): method __init__ (line 52) | def __init__(self): method from_pretrained (line 57) | def from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwa... FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_bert.py function load_vocab (line 66) | def load_vocab(vocab_file): function whitespace_tokenize (line 77) | def whitespace_tokenize(text): class BertTokenizer (line 86) | class BertTokenizer(PreTrainedTokenizer): method __init__ (line 105) | def __init__(self, vocab_file, do_lower_case=True, do_basic_tokenize=T... method vocab_size (line 143) | def vocab_size(self): method _tokenize (line 146) | def _tokenize(self, text): method _convert_token_to_id (line 156) | def _convert_token_to_id(self, token): method _convert_id_to_token (line 160) | def _convert_id_to_token(self, index): method convert_tokens_to_string (line 164) | def convert_tokens_to_string(self, tokens): method add_special_tokens_single_sentence (line 169) | def add_special_tokens_single_sentence(self, token_ids): method add_special_tokens_sentences_pair (line 176) | def add_special_tokens_sentences_pair(self, token_ids_0, token_ids_1): method save_vocabulary (line 185) | def save_vocabulary(self, vocab_path): method from_pretrained (line 201) | def from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwa... class BasicTokenizer (line 219) | class BasicTokenizer(object): method __init__ (line 222) | def __init__(self, do_lower_case=True, never_split=None, tokenize_chin... method tokenize (line 242) | def tokenize(self, text, never_split=None): method _run_strip_accents (line 273) | def _run_strip_accents(self, text): method _run_split_on_punc (line 284) | def _run_split_on_punc(self, text, never_split=None): method _tokenize_chinese_chars (line 306) | def _tokenize_chinese_chars(self, text): method _is_chinese_char (line 319) | def _is_chinese_char(self, cp): method _clean_text (line 341) | def _clean_text(self, text): class WordpieceTokenizer (line 355) | class WordpieceTokenizer(object): method __init__ (line 358) | def __init__(self, vocab, unk_token, max_input_chars_per_word=100): method tokenize (line 363) | def tokenize(self, text): function _is_whitespace (line 415) | def _is_whitespace(char): function _is_control (line 427) | def _is_control(char): function _is_punctuation (line 439) | def _is_punctuation(char): FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_gpt2.py function lru_cache (line 31) | def lru_cache(): function bytes_to_unicode (line 62) | def bytes_to_unicode(): function get_pairs (line 84) | def get_pairs(word): class GPT2Tokenizer (line 96) | class GPT2Tokenizer(PreTrainedTokenizer): method __init__ (line 105) | def __init__(self, vocab_file, merges_file, errors='replace', unk_toke... method vocab_size (line 123) | def vocab_size(self): method bpe (line 126) | def bpe(self, token): method _tokenize (line 167) | def _tokenize(self, text): method _convert_token_to_id (line 178) | def _convert_token_to_id(self, token): method _convert_id_to_token (line 182) | def _convert_id_to_token(self, index): method convert_tokens_to_string (line 186) | def convert_tokens_to_string(self, tokens): method save_vocabulary (line 192) | def save_vocabulary(self, save_directory): FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_openai.py function get_pairs (line 50) | def get_pairs(word): function text_standardize (line 62) | def text_standardize(text): class OpenAIGPTTokenizer (line 77) | class OpenAIGPTTokenizer(PreTrainedTokenizer): method __init__ (line 87) | def __init__(self, vocab_file, merges_file, unk_token="", **kwargs): method vocab_size (line 108) | def vocab_size(self): method bpe (line 111) | def bpe(self, token): method _tokenize (line 154) | def _tokenize(self, text): method _convert_token_to_id (line 169) | def _convert_token_to_id(self, token): method _convert_id_to_token (line 173) | def _convert_id_to_token(self, index): method convert_tokens_to_string (line 177) | def convert_tokens_to_string(self, tokens): method save_vocabulary (line 182) | def save_vocabulary(self, save_directory): FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_roberta.py function lru_cache (line 34) | def lru_cache(): class RobertaTokenizer (line 66) | class RobertaTokenizer(PreTrainedTokenizer): method __init__ (line 74) | def __init__(self, vocab_file, merges_file, errors='replace', bos_toke... method vocab_size (line 94) | def vocab_size(self): method bpe (line 97) | def bpe(self, token): method _tokenize (line 138) | def _tokenize(self, text): method _convert_token_to_id (line 149) | def _convert_token_to_id(self, token): method _convert_id_to_token (line 153) | def _convert_id_to_token(self, index): method convert_tokens_to_string (line 157) | def convert_tokens_to_string(self, tokens): method add_special_tokens_single_sentence (line 163) | def add_special_tokens_single_sentence(self, token_ids): method add_special_tokens_sentences_pair (line 170) | def add_special_tokens_sentences_pair(self, token_ids_0, token_ids_1): method save_vocabulary (line 179) | def save_vocabulary(self, save_directory): FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_transfo_xl.py class TransfoXLTokenizer (line 61) | class TransfoXLTokenizer(PreTrainedTokenizer): method __init__ (line 69) | def __init__(self, special=None, min_freq=0, max_size=None, lower_case... method count_file (line 99) | def count_file(self, path, verbose=False, add_eos=False): method count_sents (line 114) | def count_sents(self, sents, verbose=False): method _build_from_file (line 124) | def _build_from_file(self, vocab_file): method save_vocabulary (line 139) | def save_vocabulary(self, vocab_path): method build_vocab (line 146) | def build_vocab(self): method encode_file (line 167) | def encode_file(self, path, ordered=False, verbose=False, add_eos=True, method encode_sents (line 185) | def encode_sents(self, sents, ordered=False, verbose=False): method add_special (line 198) | def add_special(self, sym): method add_symbol (line 204) | def add_symbol(self, sym): method _convert_id_to_token (line 209) | def _convert_id_to_token(self, idx): method _convert_token_to_id (line 214) | def _convert_token_to_id(self, sym): method convert_tokens_to_string (line 231) | def convert_tokens_to_string(self, tokens): method convert_to_tensor (line 236) | def convert_to_tensor(self, symbols): method vocab_size (line 240) | def vocab_size(self): method _tokenize (line 243) | def _tokenize(self, line, add_eos=False, add_double_eos=False): class LMOrderedIterator (line 263) | class LMOrderedIterator(object): method __init__ (line 264) | def __init__(self, data, bsz, bptt, device='cpu', ext_len=None): method get_batch (line 286) | def get_batch(self, i, bptt=None): method get_fixlen_iter (line 301) | def get_fixlen_iter(self, start=0): method get_varlen_iter (line 305) | def get_varlen_iter(self, start=0, std=5, min_len=5, max_deviation=3): method __iter__ (line 317) | def __iter__(self): class LMShuffledIterator (line 321) | class LMShuffledIterator(object): method __init__ (line 322) | def __init__(self, data, bsz, bptt, device='cpu', ext_len=None, shuffl... method get_sent_stream (line 335) | def get_sent_stream(self): method stream_iterator (line 344) | def stream_iterator(self, sent_stream): method __iter__ (line 393) | def __iter__(self): class LMMultiFileIterator (line 401) | class LMMultiFileIterator(LMShuffledIterator): method __init__ (line 402) | def __init__(self, paths, vocab, bsz, bptt, device='cpu', ext_len=None, method get_sent_stream (line 415) | def get_sent_stream(self, path): method __iter__ (line 423) | def __iter__(self): class TransfoXLCorpus (line 434) | class TransfoXLCorpus(object): method from_pretrained (line 436) | def from_pretrained(cls, pretrained_model_name_or_path, cache_dir=None... method __init__ (line 478) | def __init__(self, *args, **kwargs): method build_corpus (line 485) | def build_corpus(self, path, dataset): method get_iterator (line 524) | def get_iterator(self, split, *args, **kwargs): function get_lm_corpus (line 541) | def get_lm_corpus(datadir, dataset): FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_utils.py class PreTrainedTokenizer (line 32) | class PreTrainedTokenizer(object): method bos_token (line 71) | def bos_token(self): method eos_token (line 78) | def eos_token(self): method unk_token (line 85) | def unk_token(self): method sep_token (line 92) | def sep_token(self): method pad_token (line 99) | def pad_token(self): method cls_token (line 106) | def cls_token(self): method mask_token (line 113) | def mask_token(self): method additional_special_tokens (line 120) | def additional_special_tokens(self): method bos_token (line 127) | def bos_token(self, value): method eos_token (line 131) | def eos_token(self, value): method unk_token (line 135) | def unk_token(self, value): method sep_token (line 139) | def sep_token(self, value): method pad_token (line 143) | def pad_token(self, value): method cls_token (line 147) | def cls_token(self, value): method mask_token (line 151) | def mask_token(self, value): method additional_special_tokens (line 155) | def additional_special_tokens(self, value): method __init__ (line 158) | def __init__(self, max_len=None, **kwargs): method from_pretrained (line 182) | def from_pretrained(cls, *inputs, **kwargs): method _from_pretrained (line 224) | def _from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kw... method save_pretrained (line 339) | def save_pretrained(self, save_directory): method save_vocabulary (line 367) | def save_vocabulary(self, save_directory): method vocab_size (line 376) | def vocab_size(self): method __len__ (line 381) | def __len__(self): method add_tokens (line 386) | def add_tokens(self, new_tokens): method add_special_tokens (line 426) | def add_special_tokens(self, special_tokens_dict): method tokenize (line 473) | def tokenize(self, text, **kwargs): method _tokenize (line 494) | def _tokenize(self, text, **kwargs): method convert_tokens_to_ids (line 503) | def convert_tokens_to_ids(self, tokens): method _convert_token_to_id_with_added_voc (line 519) | def _convert_token_to_id_with_added_voc(self, token): method _convert_token_to_id (line 524) | def _convert_token_to_id(self, token): method encode (line 527) | def encode(self, text, text_pair=None, add_special_tokens=False): method add_special_tokens_single_sentence (line 553) | def add_special_tokens_single_sentence(self, token_ids): method add_special_tokens_sentences_pair (line 556) | def add_special_tokens_sentences_pair(self, token_ids_0, token_ids_1): method convert_ids_to_tokens (line 559) | def convert_ids_to_tokens(self, ids, skip_special_tokens=False): method _convert_id_to_token (line 581) | def _convert_id_to_token(self, index): method convert_tokens_to_string (line 584) | def convert_tokens_to_string(self, tokens): method decode (line 591) | def decode(self, token_ids, skip_special_tokens=False, clean_up_tokeni... method special_tokens_map (line 616) | def special_tokens_map(self): method all_special_tokens (line 628) | def all_special_tokens(self): method all_special_ids (line 640) | def all_special_ids(self): method clean_up_tokenization (line 649) | def clean_up_tokenization(out_string): FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_xlm.py function get_pairs (line 71) | def get_pairs(word): function text_standardize (line 83) | def text_standardize(text): class XLMTokenizer (line 98) | class XLMTokenizer(PreTrainedTokenizer): method __init__ (line 115) | def __init__(self, vocab_file, merges_file, unk_token="", bos_tok... method vocab_size (line 143) | def vocab_size(self): method bpe (line 146) | def bpe(self, token): method _tokenize (line 189) | def _tokenize(self, text): method _convert_token_to_id (line 204) | def _convert_token_to_id(self, token): method _convert_id_to_token (line 208) | def _convert_id_to_token(self, index): method convert_tokens_to_string (line 212) | def convert_tokens_to_string(self, tokens): method add_special_tokens_single_sentence (line 217) | def add_special_tokens_single_sentence(self, token_ids): method add_special_tokens_sentences_pair (line 224) | def add_special_tokens_sentences_pair(self, token_ids_0, token_ids_1): method save_vocabulary (line 233) | def save_vocabulary(self, save_directory): FILE: LAL-Parser/src_joint/pytorch_transformers/tokenization_xlnet.py class XLNetTokenizer (line 54) | class XLNetTokenizer(PreTrainedTokenizer): method __init__ (line 64) | def __init__(self, vocab_file, max_len=None, method vocab_size (line 89) | def vocab_size(self): method __getstate__ (line 92) | def __getstate__(self): method __setstate__ (line 97) | def __setstate__(self, d): method preprocess_text (line 107) | def preprocess_text(self, inputs): method _tokenize (line 125) | def _tokenize(self, text, return_unicode=True, sample=False): method _convert_token_to_id (line 164) | def _convert_token_to_id(self, token): method _convert_id_to_token (line 168) | def _convert_id_to_token(self, index, return_unicode=True): method convert_tokens_to_string (line 175) | def convert_tokens_to_string(self, tokens): method add_special_tokens_single_sentence (line 180) | def add_special_tokens_single_sentence(self, token_ids): method add_special_tokens_sentences_pair (line 189) | def add_special_tokens_sentences_pair(self, token_ids_0, token_ids_1): method save_vocabulary (line 198) | def save_vocabulary(self, save_directory): FILE: LAL-Parser/src_joint/transliterate.py function arabic (line 129) | def arabic(inp): function hebrew (line 142) | def hebrew(inp): FILE: LAL-Parser/src_joint/trees.py class TreebankNode (line 8) | class TreebankNode(object): class InternalTreebankNode (line 11) | class InternalTreebankNode(TreebankNode): method __init__ (line 12) | def __init__(self, label, children): method linearize (line 39) | def linearize(self): method leaves (line 43) | def leaves(self): method convert (line 47) | def convert(self, index=0, nocache=False): class LeafTreebankNode (line 99) | class LeafTreebankNode(TreebankNode): method __init__ (line 100) | def __init__(self, tag, word, head, father, type): method linearize (line 111) | def linearize(self): method leaves (line 114) | def leaves(self): method convert (line 117) | def convert(self, index=0): class ParseNode (line 120) | class ParseNode(object): class InternalParseNode (line 123) | class InternalParseNode(ParseNode): method __init__ (line 124) | def __init__(self, label, children, nocache=False): method leaves (line 163) | def leaves(self): method convert (line 167) | def convert(self): method enclosing (line 174) | def enclosing(self, left, right): method chil_enclosing (line 183) | def chil_enclosing(self, left, right): method oracle_label (line 190) | def oracle_label(self, left, right): method oracle_type (line 196) | def oracle_type(self, left, right): method oracle_head (line 200) | def oracle_head(self, left, right): method oracle_splits (line 204) | def oracle_splits(self, left, right): class LeafParseNode (line 211) | class LeafParseNode(ParseNode): method __init__ (line 212) | def __init__(self, index, tag, word, father, type): method leaves (line 227) | def leaves(self): method chil_enclosing (line 230) | def chil_enclosing(self, left, right): method convert (line 234) | def convert(self): function load_trees (line 237) | def load_trees(path, heads = None, types = None, wordss = None, strip_to... FILE: LAL-Parser/src_joint/utils.py function load_embedding_dict (line 10) | def load_embedding_dict(embedding, embedding_path, normalize_digits= Fal... FILE: LAL-Parser/src_joint/vocabulary.py class Vocabulary (line 3) | class Vocabulary(object): method __init__ (line 4) | def __init__(self): method size (line 11) | def size(self): method value (line 14) | def value(self, index): method index (line 18) | def index(self, value): method index_or_unk (line 33) | def index_or_unk(self, value, unk_value): method count (line 40) | def count(self, value): method freeze (line 43) | def freeze(self):