Python reset_root_log_handler Examples

Example #1

File: run_ex.py Project: clover3/Chair

def main(start_model_path,
         start_type,
         save_dir,
         modeling_option,
         target_idx_,
         num_gpu=1):
    num_gpu = int(num_gpu)
    tf_logging.info("train_from : nli_ex")
    hp = HPCommon()
    nli_setting = BertNLI()
    set_level_debug()
    reset_root_log_handler()
    train_config = NLIPairingTrainConfig()
    train_config.num_gpu = num_gpu

    tf_logging.info("loading batches")
    data = get_nli_data(hp, nli_setting)

    def init_fn(sess):
        return init_fn_generic(sess, start_type, start_model_path)

    class LMSConfig2(LMSConfigI):
        num_tags = 3
        target_idx = target_idx_
        use_embedding_out = True
        per_layer_component = 'linear'

    train_LMS(hp, train_config, LMSConfig2(), save_dir, data, modeling_option,
              init_fn)

Example #2

def main(_):
    print("Main")
    check("point2")
    tf_logging.info("Log")

    reset_root_log_handler()
    set_level_debug()
    check("point3")
    tf_logging.info("Log")

Example #3

File: predict_train.py Project: clover3/Chair

def main(start_model_path, modeling_option, num_gpu=1):
    num_gpu = int(num_gpu)
    hp = HPCommon()
    nli_setting = BertNLI()
    set_level_debug()
    reset_root_log_handler()
    train_config = NLIPairingTrainConfig()
    train_config.num_gpu = num_gpu

    def init_fn(sess):
        return init_fn_generic(sess, "as_is", start_model_path)

    data = get_nli_data(hp, nli_setting)
    do_predict(hp, train_config, data, LMSConfig(), modeling_option, init_fn)

Example #4

def main(start_model_path, modeling_option, input_path, save_name, num_gpu=1):
    num_gpu = int(num_gpu)
    hp = HPCommon()
    nli_setting = BertNLI()
    set_level_debug()
    reset_root_log_handler()
    train_config = NLIPairingTrainConfig()
    train_config.num_gpu = num_gpu

    def init_fn(sess):
        return init_fn_generic(sess, "as_is", start_model_path)

    batches = get_batches(input_path, nli_setting, HPCommon.batch_size)
    output_d = do_predict(hp, train_config, batches, LMSConfig(),
                          modeling_option, init_fn)
    save_to_pickle(output_d, save_name)

Example #5

def main(start_model_path, start_type, save_dir, modeling_option, num_gpu=1):
    num_gpu = int(num_gpu)
    tf_logging.info("train_from : nli_ex")
    hp = HPCommon()
    nli_setting = BertNLI()
    set_level_debug()
    reset_root_log_handler()
    train_config = NLIPairingTrainConfig()
    train_config.num_gpu = num_gpu

    tf_logging.info("loading batches")
    data = get_nli_data(hp, nli_setting)

    def init_fn(sess):
        return init_fn_generic(sess, start_type, start_model_path)

    train_LMS(hp, train_config, LMSConfig(), save_dir, data, modeling_option,
              init_fn)

Example #6

File: run_train_mlp.py Project: clover3/Chair

def main(start_model_path, start_type, save_dir,
         modeling_option, num_gpu=1):
    num_gpu = int(num_gpu)
    tf_logging.info("Train with MLP")
    hp = HPCommon()
    hp.per_layer_component = 'mlp'
    nli_setting = BertNLI()
    set_level_debug()
    reset_root_log_handler()
    train_config = NLIPairingTrainConfig()
    train_config.num_gpu = num_gpu

    lms_config = LMSConfig()
    tf_logging.info("loading batches")
    data = get_nli_data(hp, nli_setting)

    def init_fn(sess):
        return init_fn_generic(sess, start_type, start_model_path)

    train_LMS(hp, train_config, lms_config, save_dir, data, modeling_option, init_fn)