File size: 3,456 Bytes
d758c99 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 | local _base = import 'nl2code-base.libsonnet';
local _output_from = true;
local _fs = 2;
function(args) _base(output_from=_output_from, data_path=args.data_path) + {
local data_path = args.data_path,
local lr_s = '%0.1e' % args.lr,
local bert_lr_s = '%0.1e' % args.bert_lr,
local end_lr_s = if args.end_lr == 0 then '0e0' else '%0.1e' % args.end_lr,
local base_bert_enc_size = 768,
local enc_size = base_bert_enc_size,
model_name: 'bs=%(bs)d,lr=%(lr)s,bert_lr=%(bert_lr)s,end_lr=%(end_lr)s,att=%(att)d' % (args + {
lr: lr_s,
bert_lr: bert_lr_s,
end_lr: end_lr_s,
}),
model+: {
encoder+: {
name: 'spider-bert',
batch_encs_update:: null,
question_encoder:: null,
column_encoder:: null,
table_encoder:: null,
dropout:: null,
update_config+: {
name: 'relational_transformer',
num_layers: args.num_layers,
num_heads: 8,
sc_link: args.sc_link,
cv_link: args.cv_link,
},
summarize_header: args.summarize_header,
use_column_type: args.use_column_type,
bert_version: args.bert_version,
bert_token_type: args.bert_token_type,
top_k_learnable:: null,
word_emb_size:: null,
},
encoder_preproc+: {
word_emb:: null,
min_freq:: null,
max_count:: null,
db_path: data_path + "database",
compute_sc_link: args.sc_link,
compute_cv_link: args.cv_link,
fix_issue_16_primary_keys: true,
bert_version: args.bert_version,
count_tokens_in_word_emb_for_vocab:: null,
save_path: data_path + 'BERTimbau-base_nl2code,output_from=%s,fs=%d,emb=bert,cvlink' % [_output_from, _fs],
},
decoder_preproc+: {
grammar+: {
end_with_from: args.end_with_from,
clause_order: args.clause_order,
infer_from_conditions: true,
factorize_sketch: _fs,
},
save_path: data_path + 'BERTimbau-base_nl2code,output_from=%s,fs=%d,emb=bert,cvlink' % [_output_from, _fs],
compute_sc_link:: null,
compute_cv_link:: null,
db_path:: null,
fix_issue_16_primary_keys:: null,
bert_version:: null,
},
decoder+: {
name: 'NL2Code',
dropout: 0.20687225956012834,
desc_attn: 'mha',
enc_recurrent_size: enc_size,
recurrent_size : args.decoder_hidden_size,
loss_type: 'softmax',
use_align_mat: args.use_align_mat,
use_align_loss: args.use_align_loss,
}
},
train+: {
batch_size: args.bs,
num_batch_accumulated: args.num_batch_accumulated,
clip_grad: 1,
model_seed: args.att,
data_seed: args.att,
init_seed: args.att,
max_steps: args.max_steps,
},
optimizer: {
name: 'bertAdamw',
lr: 0.0,
bert_lr: 0.0,
},
lr_scheduler+: {
name: 'bert_warmup_polynomial_group',
start_lrs: [args.lr, args.bert_lr],
end_lr: args.end_lr,
num_warmup_steps: $.train.max_steps / 8,
},
log: {
reopen_to_flush: true,
}
}
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