SYMBOL INDEX (108 symbols across 16 files)

FILE: data/arxiv_dataset.py
  class ArxivDataset (line 6) | class ArxivDataset(torch.utils.data.Dataset):
    method __init__ (line 11) | def __init__(self, texts, preprocess=lambda x: x, sort=False):
    method __len__ (line 30) | def __len__(self):
    method __getitem__ (line 33) | def __getitem__(self, i):

FILE: data/plot_dataset.py
  class PlotDataset (line 6) | class PlotDataset(torch.utils.data.Dataset):
    method __init__ (line 11) | def __init__(self, texts, preprocess=lambda x: x, sort=False):
    method __len__ (line 30) | def __len__(self):
    method __getitem__ (line 33) | def __getitem__(self, i):

FILE: data/prompt_dataset.py
  class PromptDataset (line 6) | class PromptDataset(torch.utils.data.Dataset):
    method __init__ (line 11) | def __init__(self, source, target, preprocess=lambda x: x, sort=False):
    method __len__ (line 37) | def __len__(self):
    method __getitem__ (line 40) | def __getitem__(self, i):

FILE: data/util.py
  function compose (line 22) | def compose(*functions):
  function prefix_truncate (line 27) | def prefix_truncate(window):
  class Preprocessor_base (line 38) | class Preprocessor_base():
    method __init__ (line 39) | def __init__(self):
    method make_fn (line 42) | def make_fn(self):
    method __call__ (line 45) | def __call__(self, x):
  function encode_tuple (line 56) | def encode_tuple(tokenizer, t):
  function truncate_tuple (line 60) | def truncate_tuple(truncator, t):
  class Preprocessor (line 64) | class Preprocessor(Preprocessor_base):
    method __init__ (line 65) | def __init__(self, tokenizer, seq_len, data_type):
    method make_fn (line 71) | def make_fn(self):
  function wp_preprocess (line 80) | def wp_preprocess(text):
  function detect_dialog (line 93) | def detect_dialog(t):
  function get_paragraph (line 102) | def get_paragraph(story):
  function extract_keywords (line 120) | def extract_keywords(text, r):
  function insert_keywords (line 273) | def insert_keywords(tokenizer, data_type):
  function collate_fn (line 419) | def collate_fn(samples):
  function prepare_dataset (line 442) | def prepare_dataset(data_dir, dataset_name, tokenizer, train_bsz, train_...

FILE: data/yelp_dataset.py
  class YelpDataset (line 6) | class YelpDataset(torch.utils.data.Dataset):
    method __init__ (line 11) | def __init__(self, source, preprocess=lambda x: x, sort=False):
    method __len__ (line 21) | def __len__(self):
    method __getitem__ (line 24) | def __getitem__(self, i):

FILE: dist_utils.py
  class SimpleDistributedDataParallel (line 26) | class SimpleDistributedDataParallel(nn.Module):
    method __init__ (line 43) | def __init__(self, module, world_size, process_group=None, buffer_size...
    method __getstate__ (line 68) | def __getstate__(self):
    method __setstate__ (line 72) | def __setstate__(self, state):
    method forward (line 76) | def forward(self, *inputs, **kwargs):
    method _register_grad_hook (line 79) | def _register_grad_hook(self):

FILE: eval_ppl.py
  function compute_loss (line 21) | def compute_loss(device, model, x_mask, x_tokens, y_mask, y_tokens, inpu...
  function compute_loss_ae (line 50) | def compute_loss_ae(device, model, x_mask, x_tokens, y_mask, y_tokens, i...
  function run_model (line 77) | def run_model():

FILE: eval_ppl_prefix.py
  function compute_loss (line 21) | def compute_loss(device, model, x_mask, x_tokens, y_mask, y_tokens, inpu...
  function compute_loss_ae (line 50) | def compute_loss_ae(device, model, x_mask, x_tokens, y_mask, y_tokens, i...
  function run_model (line 77) | def run_model():

FILE: generate.py
  function top_k_top_p_filtering (line 25) | def top_k_top_p_filtering(logits, top_k=100, top_p=0.95, filter_value=-f...
  function repeat_score (line 57) | def repeat_score(text, ngram=[3, 4, 5, 6]):
  function sample_sequence (line 76) | def sample_sequence(model, tokenizer, length, batch_size=None, x_mask=No...
  function run_model (line 131) | def run_model():

FILE: generate_prefix.py
  function top_k_top_p_filtering (line 25) | def top_k_top_p_filtering(logits, top_k=100, top_p=0.95, filter_value=-f...
  function repeat_score (line 57) | def repeat_score(text, ngram=[3, 4, 5, 6]):
  function sample_sequence (line 76) | def sample_sequence(model, tokenizer, length, batch_size=None, x_mask=No...
  function run_model (line 131) | def run_model():

FILE: model.py
  class Unmasked_Attention (line 25) | class Unmasked_Attention(Attention):
    method _attn (line 26) | def _attn(self, q, k, v, attention_mask=None, head_mask=None):
  class Unmasked_Block (line 48) | class Unmasked_Block(Block):
    method __init__ (line 49) | def __init__(self, n_ctx, config, scale=False):
  class AverageSelfAttention (line 58) | class AverageSelfAttention(nn.Module):
    method __init__ (line 59) | def __init__(self, attention_size):
    method forward (line 67) | def forward(self, inputs, attention_mask=None):
  class Cond_Attention (line 100) | class Cond_Attention(Attention):
    method __init__ (line 101) | def __init__(self, nx, n_ctx, config, scale=False):
    method _attn (line 122) | def _attn(self, q, k, v, attention_mask=None, head_mask=None):
    method forward (line 151) | def forward(self, x, z, layer_past=None, attention_mask=None, head_mas...
  class Cond_Block (line 181) | class Cond_Block(Block):
    method __init__ (line 182) | def __init__(self, n_ctx, config, scale=False):
    method forward (line 190) | def forward(self, x, z, layer_past=None, attention_mask=None, head_mas...
  class Encoder (line 205) | class Encoder(GPT2Model):
    method __init__ (line 206) | def __init__(self, config):
    method forward (line 231) | def forward(
  class Decoder (line 358) | class Decoder(GPT2Model):
    method __init__ (line 359) | def __init__(self, config, add_input=False, add_attn=False, attn_proj_...
    method forward (line 397) | def forward(
  class LM_head_rep (line 544) | class LM_head_rep(nn.Module):
    method __init__ (line 545) | def __init__(self, in_dim=768, out_dim=50257):
    method forward (line 551) | def forward(self, z):
  class VAEModel (line 557) | class VAEModel(GPT2LMHeadModel):
    method __init__ (line 558) | def __init__(self, config, add_input=False, add_attn=False, add_softma...
    method reparameterize (line 580) | def reparameterize(self, mean, logvar, z=None):
    method kl_loss (line 586) | def kl_loss(self, mean1, logvar1, mean2, logvar2):
    method forward (line 591) | def forward(

FILE: train.py
  function compute_loss (line 41) | def compute_loss(device, model, x_mask, x_tokens, y_mask, y_tokens, inpu...
  function compute_loss_ae (line 70) | def compute_loss_ae(device, model, x_mask, x_tokens, y_mask, y_tokens, i...
  function train_step (line 97) | def train_step(device, model, optimizer, x_mask, x_tokens, y_mask, y_tok...
  function top_k_top_p_filtering (line 125) | def top_k_top_p_filtering(logits, top_k=100, top_p=0.95, filter_value=-f...
  function repeat_score (line 157) | def repeat_score(text, ngram=[3, 4, 5, 6]):
  function sample_sequence (line 176) | def sample_sequence(model, tokenizer, length, batch_size=None, x_mask=No...
  function main (line 231) | def main():

FILE: train_dist.py
  function compute_loss (line 44) | def compute_loss(device, model, x_mask, x_tokens, y_mask, y_tokens, inpu...
  function compute_loss_ae (line 73) | def compute_loss_ae(device, model, x_mask, x_tokens, y_mask, y_tokens, i...
  function train_step (line 100) | def train_step(device, model, optimizer, x_mask, x_tokens, y_mask, y_tok...
  function top_k_top_p_filtering (line 124) | def top_k_top_p_filtering(logits, top_k=100, top_p=0.95, filter_value=-f...
  function repeat_score (line 156) | def repeat_score(text, ngram=[3, 4, 5, 6]):
  function sample_sequence (line 175) | def sample_sequence(model, tokenizer, length, batch_size=None, x_mask=No...
  function main_worker (line 230) | def main_worker(gpu, ngpus_per_node, args):

FILE: train_dist_half.py
  function compute_loss (line 45) | def compute_loss(device, model, x_mask, x_tokens, y_mask, y_tokens, inpu...
  function compute_loss_ae (line 74) | def compute_loss_ae(device, model, x_mask, x_tokens, y_mask, y_tokens, i...
  function train_step (line 101) | def train_step(device, model, optimizer, x_mask, x_tokens, y_mask, y_tok...
  function top_k_top_p_filtering (line 123) | def top_k_top_p_filtering(logits, top_k=100, top_p=0.95, filter_value=-f...
  function repeat_score (line 155) | def repeat_score(text, ngram=[3, 4, 5, 6]):
  function sample_sequence (line 174) | def sample_sequence(model, tokenizer, length, batch_size=None, x_mask=No...
  function main_worker (line 229) | def main_worker(gpu, ngpus_per_node, args):

FILE: tsne_plot.py
  function remove_outliers (line 172) | def remove_outliers(data, r=2.0):

FILE: util.py
  function num_params (line 12) | def num_params(model):
  function init_para_frompretrained (line 16) | def init_para_frompretrained(m, pm, share_para=False):
  function switch_schedule (line 38) | def switch_schedule(schedule, mult, switch):
  function linear_schedule (line 50) | def linear_schedule(args):