SYMBOL INDEX (130 symbols across 20 files)

FILE: 1-1.NNLM/NNLM.py
  function make_batch (line 7) | def make_batch():
  class NNLM (line 22) | class NNLM(nn.Module):
    method __init__ (line 23) | def __init__(self):
    method forward (line 32) | def forward(self, X):

FILE: 1-2.Word2Vec/Word2Vec-Skipgram(Softmax).py
  function random_batch (line 9) | def random_batch():
  class Word2Vec (line 21) | class Word2Vec(nn.Module):
    method __init__ (line 22) | def __init__(self):
    method forward (line 28) | def forward(self, X):

FILE: 2-1.TextCNN/TextCNN.py
  class TextCNN (line 9) | class TextCNN(nn.Module):
    method __init__ (line 10) | def __init__(self):
    method forward (line 18) | def forward(self, X):

FILE: 3-1.TextRNN/TextRNN.py
  function make_batch (line 8) | def make_batch():
  class TextRNN (line 22) | class TextRNN(nn.Module):
    method __init__ (line 23) | def __init__(self):
    method forward (line 29) | def forward(self, hidden, X):

FILE: 3-2.TextLSTM/TextLSTM.py
  function make_batch (line 8) | def make_batch():
  class TextLSTM (line 19) | class TextLSTM(nn.Module):
    method __init__ (line 20) | def __init__(self):
    method forward (line 27) | def forward(self, X):

FILE: 3-3.Bi-LSTM/Bi-LSTM.py
  function make_batch (line 8) | def make_batch():
  class BiLSTM (line 22) | class BiLSTM(nn.Module):
    method __init__ (line 23) | def __init__(self):
    method forward (line 30) | def forward(self, X):

FILE: 4-1.Seq2Seq/Seq2Seq.py
  function make_batch (line 11) | def make_batch():
  function make_testbatch (line 30) | def make_testbatch(input_word):
  class Seq2Seq (line 43) | class Seq2Seq(nn.Module):
    method __init__ (line 44) | def __init__(self):
    method forward (line 51) | def forward(self, enc_input, enc_hidden, dec_input):
  function translate (line 102) | def translate(word):

FILE: 4-2.Seq2Seq(Attention)/Seq2Seq(Attention).py
  function make_batch (line 14) | def make_batch():
  class Attention (line 22) | class Attention(nn.Module):
    method __init__ (line 23) | def __init__(self):
    method forward (line 32) | def forward(self, enc_inputs, hidden, dec_inputs):
    method get_att_weight (line 61) | def get_att_weight(self, dec_output, enc_outputs):  # get attention we...
    method get_att_score (line 71) | def get_att_score(self, dec_output, enc_output):  # enc_outputs [batch...

FILE: 4-3.Bi-LSTM(Attention)/Bi-LSTM(Attention).py
  class BiLSTM_Attention (line 11) | class BiLSTM_Attention(nn.Module):
    method __init__ (line 12) | def __init__(self):
    method attention_net (line 20) | def attention_net(self, lstm_output, final_state):
    method forward (line 28) | def forward(self, X):

FILE: 5-1.Transformer/Transformer(Greedy_decoder).py
  function make_batch (line 15) | def make_batch():
  function get_sinusoid_encoding_table (line 21) | def get_sinusoid_encoding_table(n_position, d_model):
  function get_attn_pad_mask (line 32) | def get_attn_pad_mask(seq_q, seq_k):
  function get_attn_subsequent_mask (line 40) | def get_attn_subsequent_mask(seq):
  class ScaledDotProductAttention (line 46) | class ScaledDotProductAttention(nn.Module):
    method __init__ (line 47) | def __init__(self):
    method forward (line 50) | def forward(self, Q, K, V, attn_mask):
  class MultiHeadAttention (line 57) | class MultiHeadAttention(nn.Module):
    method __init__ (line 58) | def __init__(self):
    method forward (line 66) | def forward(self, Q, K, V, attn_mask):
  class PoswiseFeedForwardNet (line 82) | class PoswiseFeedForwardNet(nn.Module):
    method __init__ (line 83) | def __init__(self):
    method forward (line 89) | def forward(self, inputs):
  class EncoderLayer (line 95) | class EncoderLayer(nn.Module):
    method __init__ (line 96) | def __init__(self):
    method forward (line 101) | def forward(self, enc_inputs, enc_self_attn_mask):
  class DecoderLayer (line 106) | class DecoderLayer(nn.Module):
    method __init__ (line 107) | def __init__(self):
    method forward (line 113) | def forward(self, dec_inputs, enc_outputs, dec_self_attn_mask, dec_enc...
  class Encoder (line 119) | class Encoder(nn.Module):
    method __init__ (line 120) | def __init__(self):
    method forward (line 126) | def forward(self, enc_inputs): # enc_inputs : [batch_size x source_len]
  class Decoder (line 135) | class Decoder(nn.Module):
    method __init__ (line 136) | def __init__(self):
    method forward (line 142) | def forward(self, dec_inputs, enc_inputs, enc_outputs): # dec_inputs :...
  class Transformer (line 157) | class Transformer(nn.Module):
    method __init__ (line 158) | def __init__(self):
    method forward (line 163) | def forward(self, enc_inputs, dec_inputs):
  function greedy_decoder (line 169) | def greedy_decoder(model, enc_input, start_symbol):
  function showgraph (line 191) | def showgraph(attn):

FILE: 5-1.Transformer/Transformer.py
  function make_batch (line 15) | def make_batch(sentences):
  function get_sinusoid_encoding_table (line 21) | def get_sinusoid_encoding_table(n_position, d_model):
  function get_attn_pad_mask (line 32) | def get_attn_pad_mask(seq_q, seq_k):
  function get_attn_subsequent_mask (line 39) | def get_attn_subsequent_mask(seq):
  class ScaledDotProductAttention (line 45) | class ScaledDotProductAttention(nn.Module):
    method __init__ (line 46) | def __init__(self):
    method forward (line 49) | def forward(self, Q, K, V, attn_mask):
  class MultiHeadAttention (line 56) | class MultiHeadAttention(nn.Module):
    method __init__ (line 57) | def __init__(self):
    method forward (line 65) | def forward(self, Q, K, V, attn_mask):
  class PoswiseFeedForwardNet (line 81) | class PoswiseFeedForwardNet(nn.Module):
    method __init__ (line 82) | def __init__(self):
    method forward (line 88) | def forward(self, inputs):
  class EncoderLayer (line 94) | class EncoderLayer(nn.Module):
    method __init__ (line 95) | def __init__(self):
    method forward (line 100) | def forward(self, enc_inputs, enc_self_attn_mask):
  class DecoderLayer (line 105) | class DecoderLayer(nn.Module):
    method __init__ (line 106) | def __init__(self):
    method forward (line 112) | def forward(self, dec_inputs, enc_outputs, dec_self_attn_mask, dec_enc...
  class Encoder (line 118) | class Encoder(nn.Module):
    method __init__ (line 119) | def __init__(self):
    method forward (line 125) | def forward(self, enc_inputs): # enc_inputs : [batch_size x source_len]
  class Decoder (line 134) | class Decoder(nn.Module):
    method __init__ (line 135) | def __init__(self):
    method forward (line 141) | def forward(self, dec_inputs, enc_inputs, enc_outputs): # dec_inputs :...
  class Transformer (line 156) | class Transformer(nn.Module):
    method __init__ (line 157) | def __init__(self):
    method forward (line 162) | def forward(self, enc_inputs, dec_inputs):
  function showgraph (line 168) | def showgraph(attn):

FILE: 5-2.BERT/BERT.py
  function make_batch (line 14) | def make_batch():
  function get_attn_pad_mask (line 58) | def get_attn_pad_mask(seq_q, seq_k):
  function gelu (line 65) | def gelu(x):
  class Embedding (line 69) | class Embedding(nn.Module):
    method __init__ (line 70) | def __init__(self):
    method forward (line 77) | def forward(self, x, seg):
  class ScaledDotProductAttention (line 84) | class ScaledDotProductAttention(nn.Module):
    method __init__ (line 85) | def __init__(self):
    method forward (line 88) | def forward(self, Q, K, V, attn_mask):
  class MultiHeadAttention (line 95) | class MultiHeadAttention(nn.Module):
    method __init__ (line 96) | def __init__(self):
    method forward (line 101) | def forward(self, Q, K, V, attn_mask):
  class PoswiseFeedForwardNet (line 117) | class PoswiseFeedForwardNet(nn.Module):
    method __init__ (line 118) | def __init__(self):
    method forward (line 123) | def forward(self, x):
  class EncoderLayer (line 127) | class EncoderLayer(nn.Module):
    method __init__ (line 128) | def __init__(self):
    method forward (line 133) | def forward(self, enc_inputs, enc_self_attn_mask):
  class BERT (line 138) | class BERT(nn.Module):
    method __init__ (line 139) | def __init__(self):
    method forward (line 156) | def forward(self, input_ids, segment_ids, masked_pos):

FILE: archive/tensorflow/v1/1-1.NNLM/NNLM.py
  function make_batch (line 19) | def make_batch(sentences):

FILE: archive/tensorflow/v1/1-2.Word2Vec/Word2Vec-Skipgram(NCE_loss).py
  function random_batch (line 28) | def random_batch(data, size):

FILE: archive/tensorflow/v1/1-2.Word2Vec/Word2Vec-Skipgram(Softmax).py
  function random_batch (line 26) | def random_batch(data, size):

FILE: archive/tensorflow/v1/3-1.TextRNN/TextRNN.py
  function make_batch (line 21) | def make_batch(sentences):

FILE: archive/tensorflow/v1/3-2.TextLSTM/TextLSTM.py
  function make_batch (line 20) | def make_batch(seq_data):

FILE: archive/tensorflow/v1/3-3.Bi-LSTM/Bi-LSTM.py
  function make_batch (line 21) | def make_batch(sentence):

FILE: archive/tensorflow/v1/4-1.Seq2Seq/Seq2Seq.py
  function make_batch (line 23) | def make_batch(seq_data):
  function translate (line 74) | def translate(word):

FILE: archive/tensorflow/v1/4-2.Seq2Seq(Attention)/Seq2Seq(Attention).py
  function make_batch (line 22) | def make_batch(sentences):
  function get_att_score (line 37) | def get_att_score(dec_output, enc_output):  # enc_output [n_step, n_hidden]
  function get_att_weight (line 42) | def get_att_weight(dec_output, enc_outputs):