import argparse
import torch
import torchvision.models
import sys
import pandas



'''
filename:train_model_1.0.py
create date: 11/17/2020 Tue
Author: Jeong Geol Kim
Contact: atarib4816@gmail.com
Description: This .py file will train, save weight and save Results with parameters. parameters will input by .txt file.
eg) train_model_1.0.py -r train_parameter.lcfg
guidelines for train_parameter.txt
filename format: partofarchitecture_backbone_yymmdd.lcfg
eg) shapesort_mobilenetv2_201118.txt
'''


def Params_Set():
    '''
    Description: read options from .lcfg and initialize learning options.
    You should write 
    '''
    HELP_TEXT = "how to use .py" #TODO: write description more precisely
    N_OF_PARAMS = 3 #from now on, .txt file has 3 pramas(backbone Name, iterations, save period)

    parser = argparse.ArgumentParser(description = HELP_TEXT)
    parser.add_argument("-r", required = True, help = '.lcfg file contains with learning configures')
    args = parser.parse_args()

    f = open(args.r, 'r')    
    p_string = f.readline()
    f.close()
    params = p_string.split()

    if str(args.r[-4:]) != 'lcfg':
        print ("Error: {} is wrong filename extension. Learning configures must written in .lcfg file")
        return 
    elif len(params) != N_OF_PARAMS: 
        print("Error: {} is broken. please check learning configures.".format(args.r))
        return
    else:
        print("---Learning Options---")
        print("Backbone Name: {}".format(params[0]))
        print("Number of iterations: {}".format(params[1]))
        print("Period of saving weight: {}".format(params[2]))
        return params, args.r


def Preprocess():
    pass



def Model_Construct():
    pass

def Train():
    pass

def Save_Weight():
    pass


def Result():
    pass




if __name__ == "__main__":
    #get all params from option files
    params, name_of_lcfg = Params_Set()

    Preprocess()

    Model_Construct()

    Train()   

    Save_Weight()

    Result()