@理解：
"""
import pickle
from src.base.config import save_model, model_file_path, model_file_prefix
from src.base.tools import beep_end, show_title
# ----------------------------------------------------------------------
def main():
pass
if __name__ == '__main__':
main()
beep_end()
def save_model_m0(model):
if save_model:
show_title("保存网络模型")
file_name = model_file_path + model_file_prefix + 'm0.h5'
print("保存原始模型:{} →".format(file_name), end='')
model.save(file_name)
print("模型保存成功。")
def save_model_m1(history, model):
if save_model:
show_title("保存网络模型")
file_name = model_file_path + model_file_prefix + 'm1.bin'
from src.base.tools import beep_end, show_title
# ----------------------------------------------------------------------
def main():
show_title("数据清洗开始...")
from src.data.export_data import export_base_data
x_data, y_data = export_base_data()
# from src.data.load_data import load_base_data
# x_data, y_data = load_base_data()
from src.data.export_data import export_train_test_data
x_train, y_train = export_train_test_data(x_data, y_data)
# from src.data.load_data import load_train_data
# x_train, y_train = load_train_data()
# export_train_balance(x_train, y_train)
from src.data.export_data import export_val_data
x_train_val, y_train_val = export_val_data(x_train, y_train)
# from src.data.load_data import load_val_data
# x_train_val, y_train_val = load_val_data()
# export_val_balance(x_train_val, y_train_val)
show_title("数据清洗完成！")
# ----------------------------------------------------------------------
if __name__ == '__main__':
main()
beep_end() # 运行结束的提醒
from src.model.save_model import save_model_m1
save_model_m1(history, model)
from src.data.load_data import load_test_data
show_title("加载与填充测试数据集")
x_test, y_test = load_test_data()
x_test = single_data_reshape(day_feature_idx, x_test, y_test.shape[0])
results = model.evaluate(x_test, y_test, verbose=0)
predictions = model.predict(x_test).squeeze()
show_result(results, predictions, y_test)
show_title("没有验证集训练网络模型，训练次数减半")
from src.data.load_data import load_train_data
show_title("加载与填充{}".format(train_data_type))
x_train, y_train = load_train_data()
x_train = single_data_reshape(day_feature_idx, x_train, y_train.shape[0])
history = model.fit(x_train, y_train, epochs=epochs // 2, batch_size=batch_size, verbose=2)
from src.model.save_model import save_model_m2
save_model_m2(history, model)
results = model.evaluate(x_test, y_test, verbose=0)
predictions = model.predict(x_test).squeeze()
show_result(results, predictions, y_test)
pass
if __name__ == '__main__':
# 运行结束的提醒
tools.beep_end()