def main():
# create instance of config
config = Config()
pretrain_path = "/home/yinghong/project/tmp/s_t/ray_results/final/exp-final-epoch30" \
"/train_func_0_2018-06-16_01-24-13vmtghosb"
config_path = os.path.join(pretrain_path, "params.json")
with open(config_path) as fin:
content = fin.read().replace('\n', '')
import json
j = json.loads(content)
for (key, val) in j.items():
setattr(config, key, val)
# build model
model = NERModel(config)
model.build()
model.restore_session(
os.path.join(
pretrain_path, "results/tmptmptest/bz=10-training-"
"bieo-nocnn/model.weights/"))
# create dataset
# test = CoNLLDataset(config.filename_test, config.processing_word,
# config.processing_tag, config.max_iter)
dev = CoNLLDataset(config.filename_dev, config.processing_word,
config.processing_tag, config.max_iter)
# evaluate and interact
model.tmp(dev, outfile="result-dev.txt")
interactive_shell(model)
def pretrain():
config = Config()
pretrain_path = "/home/yinghong/project/tmp/s_t_rollback/ray_results/06" \
"-19/01-HasCNN/try5"
# pretrain_path = "/home/yinghong/project/tmp/s_t_rollback/ray_results/06-19/best-HasCNN/try4"
# reverse = True
# cv = False
config_path = os.path.join(pretrain_path, "params.json")
with open(config_path) as fin:
content = fin.read().replace('\n', '')
import json
j = json.loads(content)
for (key, val) in j.items():
setattr(config, key, val)
model = NERModel(config)
model.build()
model.restore_session(
os.path.join(
pretrain_path, "results/tmptmptest/bz=10-training-"
"bieo-nocnn/model.weights/"))
# create dataset
test = CoNLLDataset(config.filename_test,
config.processing_word,
config.processing_tag,
config.max_iter,
test=True)
dev = CoNLLDataset(config.filename_dev, config.processing_word,
config.processing_tag, config.max_iter)
# evaluate and interact
model.tmp(dev, outfile="result-test-google85.63.txt")
def main():
# create instance of config
config = Config()
prefix = "/home/yinghong/project/tmp/s_t/ray_results"
# pretrain_path = "/home/yinghong/project/tmp/s_t/ray_results/final/exp-final-epoch30" \
# "/train_func_0_2018-06-16_01-24-13vmtghosb"
# pretrain_path = \
# os.path.join(prefix,"06-17/exp-final-epoch30/train_func_fi"
# "nal_0_2018-06-17_11-41-242ciyu4yq")
# pretrain_path = "/home/yinghong/project/tmp/s_t/ray_results/go1-old/exp" \
# "-go3/normal3"
# pretrain_path = "/home/yinghong/project/tmp/s_t/ray_results/final/exp-final-epo" \
# "ch30/train_func_final_0_2018-06-16_10-38-30qfc8b21c"
# config_path = os.path.join(pretrain_path, "params.json")
# with open(config_path) as fin:
# content = fin.read().replace('\n', '')
# import json
# j = json.loads(content)
# for (key, val) in j.items():
# setattr(config, key, val)
# setattr(config, "lstm_layers", 2)
# setattr(config, "clip", 5)
# build model
setattr(config, "lstm_layers", 2)
setattr(config, "nepochs", 100)
import datetime
date_str = datetime.datetime.now().strftime("%Y-%m-%d-%H-%M")
dir_output = "results/finalrun/" + "main_layer2/" + date_str + "/"
setattr(config, "dir_output", dir_output)
setattr(config, "dir_model", dir_output + "model.weights/finalmodel")
setattr(config, "path_log", dir_output + "log.txt")
model = NERModel(config)
model.build()
model.restore_session(
"/home/yinghong/project/tmp/s_t_rollback/ray_results/06-19/01-HasCNN/try3"
)
# create dataset
# test = CoNLLDataset(config.filename_test, config.processing_word,
# config.processing_tag, config.max_iter)
dev = CoNLLDataset(config.filename_dev, config.processing_word,
config.processing_tag, config.max_iter)
# evaluate and interact
model.tmp(dev, outfile="result-dev-goo.txt")
