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")