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run.py
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import os
# import subprocess
import os.path
import sys
import ntpath
def preprocess(lang):
# python run.py preprocess sql
run = 'python preprocess.py ' \
'-token_src ../../data/source/%s_index_to_tokenized_code.pkl ' \
'-token_tgt ../../data/source/%s_index_to_tokenized_qt.pkl ' \
'-split_indices ../../data/source/split_indices_%s_cleaned.pkl ' \
'-src_word2id ../../data/source/%s.code.vocab.pkl ' \
'-src_seq_length 120 -tgt_seq_length 20 '\
'-tgt_word2id ../../data/source/%s.qt.vocab.pkl ' \
'-save_data dataset/train_qt_new_cleaned/%s.processed_all ' \
'--DEV_src ../../data/source/codenn_%s/codenn.dev.ix_to_tokenized_code.pkl ' \
'--DEV_tgt ../../data/source/codenn_%s/codenn.dev.ix_to_tokenized_qt.pkl ' \
'--DEV_indices ../../data/source/codenn_%s/codenn.dev.qid_cid_pair.gen.dataset.pkl ' \
'--EVAL_src ../../data/source/codenn_%s/codenn.eval.ix_to_tokenized_code.pkl ' \
'--EVAL_tgt ../../data/source/codenn_%s/codenn.eval.ix_to_tokenized_qt.pkl ' \
'--EVAL_indices ../../data/source/codenn_%s/codenn.eval.qid_cid_pair.gen.dataset.pkl ' \
'> log_qt_new_cleaned/log.%s.preprocess' % (lang, lang, lang, lang, lang, lang, lang, lang, lang, lang, lang, lang, lang)
print(run)
a = os.system(run)
if a == 0:
print("finished.")
else:
print("failed.")
sys.exit()
def train_a2c(lang, bool_toy, bool_has_baseline, max_predict_length, pred_mask, sent_reward,
load_from, start_reinforce, end_epoch, critic_pretrain_epochs,
attn, brnn, decay_ep, lr, emb_dim, h_dim, dropout, batch_size, pretrain_emb, layers):
# pretrain: python run.py train_a2c sql 1/0 1/0 20 pred_mask {cr|bleu} None None 20 0 attributes...
# pretrain critic: python run.py train_a2c sql 1/0 1 20 pred_mask {cr|bleu} load_from start_ep end_ep 10 ...
# RL: python run.py train_a2c sql 1/0 1/0 20 pred_mask {cr|bleu} load_from_path best_pretrain_ep+1 64 10 1 1 45 0.0001 ...
data_name = "_toy" if int(bool_toy) else ""
arg_str = '-lang %s ' \
'-data dataset/train_qt_new_cleaned/%s.processed_all.train%s.pt ' \
'-save_dir dataset/result_%s_qt_new_cleaned/ -max_predict_length %s -predict_mask %s ' \
'-end_epoch %s ' \
'-critic_pretrain_epochs %s ' \
'-sent_reward %s ' \
'-has_attn %s -has_baseline %s -start_decay_at %s -word_vec_size %s -rnn_size %s ' \
'-dropout %s -batch_size %s -layers %s ' \
'-gpus 0 ' % (
lang, lang, data_name, lang, max_predict_length, pred_mask,
end_epoch, critic_pretrain_epochs, sent_reward,
attn, bool_has_baseline, decay_ep, emb_dim, h_dim, dropout, batch_size, layers)
if brnn == '1':
arg_str += '-brnn '
if len(data_name):
arg_str += '-data_name %s ' % data_name
if start_reinforce != "None":
# RL
if lr != '0.0001':
arg_str += '-reinforce_lr %s ' % lr
arg_str += '-start_reinforce %s ' % start_reinforce
log_str = '> log_qt_new_cleaned/log.%s.a2c-train%s_RL%s_%s_%s_%s' % (
lang, data_name, "hasBaseline" if bool_has_baseline == '1' else "noBaseline",
start_reinforce, end_epoch, critic_pretrain_epochs)
else:
# SL
if lr != '0.001':
arg_str += '-lr %s ' % lr
log_str = '> log_qt_new_cleaned/log.%s.a2c-train%s_noRL_%s_%s' % (
lang, data_name, end_epoch, critic_pretrain_epochs)
if load_from != "None":
arg_str += '-load_from %s ' % load_from
if pretrain_emb == '1':
arg_str += '-load_embedding_from dataset/train_qt_new_cleaned/ '
# show_str as
show_str = "_attn%s_brnn%s" % (attn, brnn)
if decay_ep != "5":
if int(decay_ep) == int(end_epoch) + 1:
show_str += "_nodecay"
else:
show_str += "_decay%s" % decay_ep
if start_reinforce == "None" and lr != "0.001":
show_str += "_lr%s" % lr
elif start_reinforce != "None" and lr != "0.0001":
show_str += "_rflr%s" % lr
if emb_dim != "512":
show_str += "_emb%s" % emb_dim
if h_dim != "512":
show_str += "_rnn%s" % h_dim
if dropout != "0.3":
show_str += "_dropout%s" % dropout
if batch_size != "64":
show_str += "_bs%s" % batch_size
if start_reinforce != "None": #RL signal
show_str += "_Sent%s" % sent_reward
if pretrain_emb == '1':
show_str += '_embPre'
if int(layers) > 1:
show_str += "_layers%s" % layers
if pred_mask == '1':
show_str += "_predMask"
arg_str += '-show_str %s ' % show_str
log_str += show_str
# logging
arg_str += log_str
run = 'python a2c-train.py %s' % arg_str
print(run)
a = os.system(run)
if a == 0:
print("finished.")
else:
print("failed.")
sys.exit()
def test_a2c(lang, bool_toy, max_predict_length, pred_mask, sent_reward,
load_from_path, eval_set, collect, attn, layers):
# python run.py test_a2c sql 1/0 20 pred_mask cr_or_bleu load_from_path default|codenn|codenn_all collect attn layers
data_name = "_toy" if int(bool_toy) else ""
arg_str = '-lang %s -load_from %s -sent_reward %s ' \
'-max_predict_length %s -predict_mask %s ' \
'-eval -save_dir . ' \
'-has_attn %s ' \
'-gpus 0 -show_str None -layers %s ' \
% (lang, load_from_path, sent_reward, max_predict_length, pred_mask,
attn, layers)
if eval_set == "default":
arg_str += '-data dataset/train_%s/%s.processed_all.train%s.pt ' % ("qt_new_cleaned", lang, data_name)
elif eval_set == "codenn":
arg_str += '-data dataset/train_%s/%s.processed_all.train%s.pt ' % ("qt_new_cleaned", lang, data_name)
arg_str += '-eval_codenn '
elif eval_set == "codenn_all":
arg_str += '-data dataset/train_%s/%s.processed_all.codenn_all.pt ' % ("qt_new_cleaned", lang)
arg_str += '-eval_codenn_all '
if collect == "1":
arg_str += '-collect_anno '
checkpoint_name = ntpath.basename(load_from_path)
log_str = '> log_%s/log.%s.a2c-test%s_Sent%s_%s%s%s' % (
"qt_new_cleaned", lang, data_name, sent_reward, checkpoint_name,
(eval_set if eval_set != "default" else ""), ("_collect" if collect == '1' else ""))
if pred_mask == '1':
log_str += "_predMask"
arg_str += log_str
run = 'python a2c-train.py %s' % arg_str
print(run)
a = os.system(run)
if a == 0:
print("finished.")
else:
print("failed.")
sys.exit()
if sys.argv[1] == 'preprocess':
preprocess(sys.argv[2])
if sys.argv[1] == 'train_a2c':
train_a2c(sys.argv[2], sys.argv[3], sys.argv[4],
sys.argv[5], sys.argv[6], sys.argv[7],
sys.argv[8], sys.argv[9], sys.argv[10],
sys.argv[11], sys.argv[12], sys.argv[13],
sys.argv[14], sys.argv[15], sys.argv[16],
sys.argv[17], sys.argv[18], sys.argv[19],
sys.argv[20], sys.argv[21])
if sys.argv[1] == 'test_a2c':
test_a2c(sys.argv[2], sys.argv[3], sys.argv[4], sys.argv[5],
sys.argv[6], sys.argv[7], sys.argv[8], sys.argv[9],
sys.argv[10], sys.argv[11])