SYMBOL INDEX (97 symbols across 1 files)

FILE: the_annotated_transformer.py
  function is_interactive_notebook (line 143) | def is_interactive_notebook():
  function show_example (line 147) | def show_example(fn, args=[]):
  function execute_example (line 152) | def execute_example(fn, args=[]):
  class DummyOptimizer (line 157) | class DummyOptimizer(torch.optim.Optimizer):
    method __init__ (line 158) | def __init__(self):
    method step (line 162) | def step(self):
    method zero_grad (line 165) | def zero_grad(self, set_to_none=False):
  class DummyScheduler (line 169) | class DummyScheduler:
    method step (line 170) | def step(self):
  class EncoderDecoder (line 230) | class EncoderDecoder(nn.Module):
    method __init__ (line 236) | def __init__(self, encoder, decoder, src_embed, tgt_embed, generator):
    method forward (line 244) | def forward(self, src, tgt, src_mask, tgt_mask):
    method encode (line 248) | def encode(self, src, src_mask):
    method decode (line 251) | def decode(self, memory, src_mask, tgt, tgt_mask):
  class Generator (line 256) | class Generator(nn.Module):
    method __init__ (line 259) | def __init__(self, d_model, vocab):
    method forward (line 263) | def forward(self, x):
  function clones (line 286) | def clones(module, N):
  class Encoder (line 292) | class Encoder(nn.Module):
    method __init__ (line 295) | def __init__(self, layer, N):
    method forward (line 300) | def forward(self, x, mask):
  class LayerNorm (line 315) | class LayerNorm(nn.Module):
    method __init__ (line 318) | def __init__(self, features, eps=1e-6):
    method forward (line 324) | def forward(self, x):
  class SublayerConnection (line 344) | class SublayerConnection(nn.Module):
    method __init__ (line 350) | def __init__(self, size, dropout):
    method forward (line 355) | def forward(self, x, sublayer):
  class EncoderLayer (line 367) | class EncoderLayer(nn.Module):
    method __init__ (line 370) | def __init__(self, size, self_attn, feed_forward, dropout):
    method forward (line 377) | def forward(self, x, mask):
  class Decoder (line 390) | class Decoder(nn.Module):
    method __init__ (line 393) | def __init__(self, layer, N):
    method forward (line 398) | def forward(self, x, memory, src_mask, tgt_mask):
  class DecoderLayer (line 413) | class DecoderLayer(nn.Module):
    method __init__ (line 416) | def __init__(self, size, self_attn, src_attn, feed_forward, dropout):
    method forward (line 424) | def forward(self, x, memory, src_mask, tgt_mask):
  function subsequent_mask (line 441) | def subsequent_mask(size):
  function example_mask (line 457) | def example_mask():
  function attention (line 519) | def attention(query, key, value, mask=None, dropout=None):
  class MultiHeadedAttention (line 589) | class MultiHeadedAttention(nn.Module):
    method __init__ (line 590) | def __init__(self, h, d_model, dropout=0.1):
    method forward (line 601) | def forward(self, query, key, value, mask=None):
  class PositionwiseFeedForward (line 677) | class PositionwiseFeedForward(nn.Module):
    method __init__ (line 680) | def __init__(self, d_model, d_ff, dropout=0.1):
    method forward (line 686) | def forward(self, x):
  class Embeddings (line 704) | class Embeddings(nn.Module):
    method __init__ (line 705) | def __init__(self, d_model, vocab):
    method forward (line 710) | def forward(self, x):
  class PositionalEncoding (line 748) | class PositionalEncoding(nn.Module):
    method __init__ (line 751) | def __init__(self, d_model, dropout, max_len=5000):
    method forward (line 766) | def forward(self, x):
  function example_positional (line 778) | def example_positional():
  function make_model (line 822) | def make_model(
  function inference_test (line 857) | def inference_test():
  function run_tests (line 880) | def run_tests():
  class Batch (line 907) | class Batch:
    method __init__ (line 910) | def __init__(self, src, tgt=None, pad=2):  # 2 = <blank>
    method make_std_mask (line 920) | def make_std_mask(tgt, pad):
  class TrainState (line 939) | class TrainState:
  function run_epoch (line 949) | def run_epoch(
  function rate (line 1058) | def rate(step, model_size, factor, warmup):
  function example_learning_schedule (line 1071) | def example_learning_schedule():
  class LabelSmoothing (line 1148) | class LabelSmoothing(nn.Module):
    method __init__ (line 1151) | def __init__(self, size, padding_idx, smoothing=0.0):
    method forward (line 1160) | def forward(self, x, target):
  function example_label_smoothing (line 1182) | def example_label_smoothing():
  function loss (line 1234) | def loss(x, crit):
  function penalization_visualization (line 1240) | def penalization_visualization():
  function data_gen (line 1275) | def data_gen(V, batch_size, nbatches):
  class SimpleLossCompute (line 1289) | class SimpleLossCompute:
    method __init__ (line 1292) | def __init__(self, generator, criterion):
    method __call__ (line 1296) | def __call__(self, x, y, norm):
  function greedy_decode (line 1313) | def greedy_decode(model, src, src_mask, max_len, start_symbol):
  function example_simple_model (line 1333) | def example_simple_model():
  function load_tokenizers (line 1399) | def load_tokenizers():
  function tokenize (line 1417) | def tokenize(text, tokenizer):
  function yield_tokens (line 1421) | def yield_tokens(data_iter, tokenizer, index):
  function build_vocabulary (line 1429) | def build_vocabulary(spacy_de, spacy_en):
  function load_vocab (line 1458) | def load_vocab(spacy_de, spacy_en):
  function collate_batch (line 1488) | def collate_batch(
  function create_dataloaders (line 1551) | def create_dataloaders(
  function train_worker (line 1616) | def train_worker(
  function train_distributed_model (line 1713) | def train_distributed_model(vocab_src, vocab_tgt, spacy_de, spacy_en, co...
  function train_model (line 1728) | def train_model(vocab_src, vocab_tgt, spacy_de, spacy_en, config):
  function load_trained_model (line 1739) | def load_trained_model():
  function average (line 1822) | def average(model, models):
  function check_outputs (line 1862) | def check_outputs(
  function run_model_example (line 1905) | def run_model_example(n_examples=5):
  function mtx2df (line 1944) | def mtx2df(m, max_row, max_col, row_tokens, col_tokens):
  function attn_map (line 1966) | def attn_map(attn, layer, head, row_tokens, col_tokens, max_dim=30):
  function get_encoder (line 1989) | def get_encoder(model, layer):
  function get_decoder_self (line 1993) | def get_decoder_self(model, layer):
  function get_decoder_src (line 1997) | def get_decoder_src(model, layer):
  function visualize_layer (line 2001) | def visualize_layer(model, layer, getter_fn, ntokens, row_tokens, col_to...
  function viz_encoder_self (line 2034) | def viz_encoder_self():
  function viz_decoder_self (line 2063) | def viz_decoder_self():
  function viz_decoder_src (line 2095) | def viz_decoder_src():