SYMBOL INDEX (103 symbols across 12 files)

FILE: adam.py
  class AdamWeightDecayOptimizer (line 5) | class AdamWeightDecayOptimizer(Optimizer):
    method __init__ (line 9) | def __init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8,
    method __setstate__ (line 23) | def __setstate__(self, state):
    method step (line 28) | def step(self, closure=None):

FILE: biglm.py
  class BIGLM (line 9) | class BIGLM(nn.Module):
    method __init__ (line 10) | def __init__(self, local_rank, vocab, embed_dim, ff_embed_dim, num_hea...
    method reset_parameters (line 35) | def reset_parameters(self):
    method label_smotthing_loss (line 41) | def label_smotthing_loss(self, y_pred, y, y_mask, avg=True):
    method nll_loss (line 51) | def nll_loss(self, y_pred, y, y_mask, avg=True):
    method work_incremental (line 64) | def work_incremental(self, enc, src_padding_mask, ys_inp, ys_tpl, ys_s...
    method work (line 92) | def work(self, enc, src_padding_mask, ys_inp, ys_tpl, ys_seg, ys_pos):
    method encode (line 114) | def encode(self, xs_tpl, xs_seg, xs_pos):
    method ppl (line 120) | def ppl(self, xs_tpl, xs_seg, xs_pos, ys_truth, ys_inp, ys_tpl, ys_seg...
    method forward (line 141) | def forward(self, xs_tpl, xs_seg, xs_pos, ys_truth, ys_inp, ys_tpl, ys...

FILE: data.py
  function ListsToTensor (line 17) | def ListsToTensor(xs, vocab=None):
  function _back_to_text_for_check (line 28) | def _back_to_text_for_check(x, vocab):
  function batchify (line 33) | def batchify(data, vocab):
  function s2t (line 61) | def s2t(strs, vocab):
  function s2xy (line 71) | def s2xy(lines, vocab, max_len, min_len):
  function parse_line (line 80) | def parse_line(line, max_len, min_len):
  function s2xy_polish (line 140) | def s2xy_polish(lines, vocab, max_len, min_len):
  function parse_line_polish (line 147) | def parse_line_polish(line, max_len, min_len):
  class DataLoader (line 204) | class DataLoader(object):
    method __init__ (line 205) | def __init__(self, vocab, filename, batch_size, max_len_y, min_len_y):
    method __iter__ (line 214) | def __iter__(self):
  class Vocab (line 238) | class Vocab(object):
    method __init__ (line 239) | def __init__(self, filename, min_occur_cnt, specials = None):
    method size (line 255) | def size(self):
    method unk_idx (line 259) | def unk_idx(self):
    method padding_idx (line 263) | def padding_idx(self):
    method random_token (line 266) | def random_token(self):
    method idx2token (line 269) | def idx2token(self, x):
    method token2idx (line 274) | def token2idx(self, x):

FILE: eval.py
  function init_model (line 14) | def init_model(m_path, device, vocab):

FILE: label_smoothing.py
  class LabelSmoothing (line 5) | class LabelSmoothing(nn.Module):
    method __init__ (line 7) | def __init__(self, device, size, padding_idx, label_smoothing=0.0):
    method forward (line 20) | def forward(self, output, target):

FILE: metrics.py
  function eval_tpl (line 29) | def eval_tpl(sents1, sents2):
  function rhythm_labellig (line 53) | def rhythm_labellig(sents):
  function eval_rhythm (line 86) | def eval_rhythm(sents1, sents2):
  function eval_endings (line 109) | def eval_endings(sents1, sents2):
  function eval (line 126) | def eval(res_file, fid):

FILE: optim.py
  class Optim (line 3) | class Optim:
    method __init__ (line 5) | def __init__(self, model_size, factor, warmup, optimizer):
    method step (line 13) | def step(self):
    method rate (line 22) | def rate(self, step = None):
    method state_dict (line 28) | def state_dict(self):
    method load_state_dict (line 31) | def load_state_dict(self, m):

FILE: polish.py
  function init_model (line 13) | def init_model(m_path, device, vocab):
  function top_k_inc (line 29) | def top_k_inc(enc, src_padding_mask, inp_ys_tpl, inp_ys_seg, inp_ys_pos,...
  function top_k (line 78) | def top_k(enc, src_padding_mask, inp_ys_tpl, inp_ys_seg, inp_ys_pos, s):

FILE: test.py
  function init_seeds (line 14) | def init_seeds():
  function init_model (line 23) | def init_model(m_path, device, vocab):
  function top_k_inc (line 38) | def top_k_inc(enc, src_padding_mask, inp_ys_tpl, inp_ys_seg, inp_ys_pos,...
  function top_k (line 87) | def top_k(enc, src_padding_mask, inp_ys_tpl, inp_ys_seg, inp_ys_pos, s):
  function greedy (line 129) | def greedy(enc, src_padding_mask, inp_ys_tpl, inp_ys_seg, inp_ys_pos, s):
  function beam_decode (line 175) | def beam_decode(s, x, enc, src_padding_mask, inp_ys_tpl, inp_ys_seg, inp...
  function beam_search (line 293) | def beam_search(enc, src_padding_mask, ys_tpl, ys_seg, ys_pos, s):

FILE: train.py
  function parse_config (line 15) | def parse_config():
  function update_lr (line 48) | def update_lr(optimizer, lr):
  function average_gradients (line 52) | def average_gradients(model):
  function eval_epoch (line 65) | def eval_epoch(lm_args, model, lm_vocab, local_rank, label):
  function run (line 104) | def run(args, local_rank):
  function init_processes (line 177) | def init_processes(args, local_rank, fn, backend='nccl'):

FILE: transformer.py
  class TransformerLayer (line 9) | class TransformerLayer(nn.Module):
    method __init__ (line 11) | def __init__(self, embed_dim, ff_embed_dim, num_heads, dropout, with_e...
    method reset_parameters (line 25) | def reset_parameters(self):
    method forward (line 31) | def forward(self, x, kv = None,
    method work_incremental (line 62) | def work_incremental(self, x, self_padding_mask = None, self_attn_mask...
  class MultiheadAttention (line 82) | class MultiheadAttention(nn.Module):
    method __init__ (line 84) | def __init__(self, embed_dim, num_heads, dropout=0., weights_dropout=T...
    method reset_parameters (line 100) | def reset_parameters(self):
    method forward (line 106) | def forward(self, query, key, value, key_padding_mask=None, attn_mask=...
    method in_proj_qkv (line 206) | def in_proj_qkv(self, query):
    method in_proj_kv (line 209) | def in_proj_kv(self, key):
    method in_proj_q (line 212) | def in_proj_q(self, query):
    method in_proj_k (line 215) | def in_proj_k(self, key):
    method in_proj_v (line 218) | def in_proj_v(self, value):
    method _in_proj (line 221) | def _in_proj(self, input, start=0, end=None):
    method _get_input_buffer (line 229) | def _get_input_buffer(self, incremental_state):
    method _set_input_buffer (line 236) | def _set_input_buffer(self, incremental_state, buffer):
    method _get_bidx (line 243) | def _get_bidx(self, incremental_state):
  function Embedding (line 249) | def Embedding(num_embeddings, embedding_dim, padding_idx):
  class SelfAttentionMask (line 255) | class SelfAttentionMask(nn.Module):
    method __init__ (line 256) | def __init__(self, init_size = 100, device = 0):
    method get_mask (line 262) | def get_mask(size):
    method forward (line 266) | def forward(self, size):
  class LearnedPositionalEmbedding (line 272) | class LearnedPositionalEmbedding(nn.Module):
    method __init__ (line 275) | def __init__(self, embedding_dim, init_size=1024, device=0):
    method reset_parameters (line 281) | def reset_parameters(self):
    method forward (line 284) | def forward(self, input, offset=0):
  class SinusoidalPositionalEmbedding (line 291) | class SinusoidalPositionalEmbedding(nn.Module):
    method __init__ (line 294) | def __init__(self, embedding_dim, init_size=1024, device=0):
    method get_embedding (line 304) | def get_embedding(num_embeddings, embedding_dim):
    method forward (line 318) | def forward(self, input, offset=0):

FILE: utils.py
  function gelu (line 8) | def gelu(x):
  class LayerNorm (line 12) | class LayerNorm(nn.Module):
    method __init__ (line 13) | def __init__(self, hidden_size, eps=1e-12):
    method reset_parameters (line 19) | def reset_parameters(self):
    method forward (line 23) | def forward(self, x):
  function _get_full_incremental_state_key (line 32) | def _get_full_incremental_state_key(module_instance, key):
  function get_incremental_state (line 43) | def get_incremental_state(module, incremental_state, key):
  function set_incremental_state (line 50) | def set_incremental_state(module, incremental_state, key, value):