SYMBOL INDEX (99 symbols across 14 files)

FILE: bleu.py
  function _get_ngrams (line 27) | def _get_ngrams(segment, max_order):
  function compute_bleu (line 45) | def compute_bleu(reference_corpus, translation_corpus, max_order=4,
  function bleu_metrics (line 128) | def bleu_metrics(per_segment_references, translations, smooth=False, max...

FILE: modules_v2.py
  function positional_encoding (line 8) | def positional_encoding(seq_len, num_units, visualization=False):
  function scaled_dot_product_attention (line 44) | def scaled_dot_product_attention(q, k, v, mask=None):
  class multihead_attention (line 70) | class multihead_attention(tf.keras.layers.Layer):
    method __init__ (line 71) | def __init__(self, d_model, num_heads):
    method split_heads (line 85) | def split_heads(self, x, batch_size):
    method call (line 94) | def call(self, v, k, q, mask):
  class pointwise_feedforward (line 113) | class pointwise_feedforward(tf.keras.layers.Layer):
    method __init__ (line 114) | def __init__(self, d_model, dff):
    method call (line 122) | def call(self, x):
  class EncoderBlock (line 129) | class EncoderBlock(tf.keras.layers.Layer):
    method __init__ (line 130) | def __init__(self, d_model, num_heads, dff, rate=0.1):
    method call (line 141) | def call(self, x, training, padding_mask):
  class DecoderBlock (line 153) | class DecoderBlock(tf.keras.layers.Layer):
    method __init__ (line 154) | def __init__(self, d_model, num_heads, dff, rate=0.1):
    method call (line 169) | def call(self, x, enc_output, training, look_ahead_mask, padding_mask):
  class Encoder (line 185) | class Encoder(tf.keras.layers.Layer):
    method __init__ (line 186) | def __init__(self, num_blocks, d_model, num_heads, dff, input_vocab_si...
    method call (line 198) | def call(self, x, training, padding_mask, attn_dict):
  class Decoder (line 214) | class Decoder(tf.keras.layers.Layer):
    method __init__ (line 215) | def __init__(self, num_blocks, d_model, num_heads, dff, target_vocab_s...
    method call (line 227) | def call(self, x, enc_output, training, look_ahead_mask, padding_mask,...
  class Transformer (line 244) | class Transformer(tf.keras.Model):
    method __init__ (line 245) | def __init__(self, num_blocks, d_model, num_heads, dff, input_vocab_si...
    method call (line 252) | def call(self, inp, tar, training, enc_padding_mask, look_ahead_mask, ...

FILE: old_version/data_loader.py
  function load_vocab (line 10) | def load_vocab(vocab):
  function generate_dataset (line 23) | def generate_dataset(source_sents, target_sents):
  function load_data (line 60) | def load_data(l_data):
  function get_batch_data (line 90) | def get_batch_data():

FILE: old_version/eval.py
  function eval (line 13) | def eval():

FILE: old_version/make_dic.py
  function make_dic (line 9) | def make_dic(path, fname):

FILE: old_version/modules.py
  function normalize (line 8) | def normalize(inputs,
  function positional_encoding (line 37) | def positional_encoding(inputs,
  function embedding (line 87) | def embedding(inputs,
  function multihead_attention (line 126) | def multihead_attention(queries,
  function feedforward (line 241) | def feedforward(inputs,
  function label_smoothing (line 283) | def label_smoothing(inputs, epsilon = 0.1):

FILE: old_version/params.py
  class Params (line 2) | class Params:

FILE: old_version/train.py
  class Graph (line 11) | class Graph():
    method __init__ (line 12) | def __init__(self, is_training = True):

FILE: params.py
  class Params (line 2) | class Params:

FILE: tf1.12.0-eager/bleu.py
  function _get_ngrams (line 27) | def _get_ngrams(segment, max_order):
  function compute_bleu (line 45) | def compute_bleu(reference_corpus, translation_corpus, max_order=4,
  function bleu_metrics (line 128) | def bleu_metrics(per_segment_references, translations, smooth=False, max...

FILE: tf1.12.0-eager/modules.py
  function positional_encoding (line 8) | def positional_encoding(seq_len, num_units, visualization=False):
  function scaled_dot_product_attention (line 44) | def scaled_dot_product_attention(q, k, v, mask=None):
  class multihead_attention (line 70) | class multihead_attention(tf.keras.layers.Layer):
    method __init__ (line 71) | def __init__(self, d_model, num_heads):
    method split_heads (line 85) | def split_heads(self, x, batch_size):
    method call (line 94) | def call(self, v, k, q, mask):
  class pointwise_feedforward (line 113) | class pointwise_feedforward(tf.keras.layers.Layer):
    method __init__ (line 114) | def __init__(self, d_model, dff):
    method call (line 122) | def call(self, x):
  class EncoderBlock (line 129) | class EncoderBlock(tf.keras.layers.Layer):
    method __init__ (line 130) | def __init__(self, d_model, num_heads, dff, rate=0.1):
    method call (line 141) | def call(self, x, training, padding_mask):
  class DecoderBlock (line 153) | class DecoderBlock(tf.keras.layers.Layer):
    method __init__ (line 154) | def __init__(self, d_model, num_heads, dff, rate=0.1):
    method call (line 169) | def call(self, x, enc_output, training, look_ahead_mask, padding_mask):
  class Encoder (line 185) | class Encoder(tf.keras.layers.Layer):
    method __init__ (line 186) | def __init__(self, num_blocks, d_model, num_heads, dff, input_vocab_si...
    method call (line 198) | def call(self, x, training, padding_mask, attn_dict):
  class Decoder (line 214) | class Decoder(tf.keras.layers.Layer):
    method __init__ (line 215) | def __init__(self, num_blocks, d_model, num_heads, dff, target_vocab_s...
    method call (line 227) | def call(self, x, enc_output, training, look_ahead_mask, padding_mask,...
  class Transformer (line 244) | class Transformer(tf.keras.Model):
    method __init__ (line 245) | def __init__(self, num_blocks, d_model, num_heads, dff, input_vocab_si...
    method call (line 252) | def call(self, inp, tar, training, enc_padding_mask, look_ahead_mask, ...

FILE: tf1.12.0-eager/params.py
  class Params (line 2) | class Params:

FILE: tf1.12.0-eager/utils.py
  function build_vocab (line 13) | def build_vocab(path, fname):
  function load_vocab (line 31) | def load_vocab(vocab):
  function tokenize_sequences (line 54) | def tokenize_sequences(source_sent, target_sent):
  function jit_tokenize_sequences (line 74) | def jit_tokenize_sequences(source_sent, target_sent):
  function filter_single_word (line 78) | def filter_single_word(source_sent, target_sent):
  function _byte_features (line 82) | def _byte_features(value):
  function dump2record (line 86) | def dump2record(filename, corpus1, corpus2):
  function build_dataset (line 112) | def build_dataset(mode, filename=None, corpus=None, is_training=True):
  function LRSchedule (line 162) | def LRSchedule(global_step, d_model, warmup_steps=4000):
  function masking (line 180) | def masking(sequence, task='padding'):
  function create_masks (line 200) | def create_masks(inp, tar):

FILE: utils_v2.py
  function build_vocab (line 11) | def build_vocab(path, fname):
  function load_vocab (line 29) | def load_vocab(vocab):
  function tokenize_sequences (line 52) | def tokenize_sequences(source_sent, target_sent):
  function jit_tokenize_sequences (line 77) | def jit_tokenize_sequences(source_sent, target_sent):
  function filter_single_word (line 81) | def filter_single_word(source_sent, target_sent):
  function _byte_features (line 85) | def _byte_features(value):
  function dump2record (line 89) | def dump2record(filename, corpus1, corpus2):
  function build_dataset (line 115) | def build_dataset(mode, batch_size, cache_name, filename=None, corpus=No...
  class LRSchedule (line 167) | class LRSchedule(tf.keras.optimizers.schedules.LearningRateSchedule):
    method __init__ (line 168) | def __init__(self, d_model, warmup_steps=4000):
    method __call__ (line 175) | def __call__(self, step):
  class polynomialLR (line 182) | class polynomialLR(tf.keras.optimizers.schedules.LearningRateSchedule):
    method __init__ (line 183) | def __init__(self, sl, el, decay_steps, power):
    method __call__ (line 192) | def __call__(self, step):
  function masking (line 198) | def masking(sequence, task='padding'):
  function create_masks (line 218) | def create_masks(inp, tar):
  function plot_attention_weights (line 229) | def plot_attention_weights(attention, sentence, result, layer):