import pickle
import sys
import torch
import pandas as pd

def read_data_file(filepath):
    df = pd.read_csv(filepath, sep='\t', header=None, index_col=None)
    dataframe = df.iloc[:, [7,10]]
    dataframe.columns = ['biggy','type']
    #print(dataframe.size[0])
    # for x in range(len(dataframe)):
    #     dataframe['biggy'].loc[x] = dataframe['biggy'].loc[x].replace(" ","")
        #such dumb solution, well, but at least it works
    dataframe['bias'] = 1
    dataframe['biggy'] = dataframe['biggy'].astype(float)
    return dataframe

def dataframe_to_arrays(dataframe):
    dataframe1 = dataframe.copy(deep=True)
    dataframe1["type"] = dataframe1["type"].astype('category').cat.codes
    return dataframe1

#PREDICT_FILE_PATH = 'dev-0/in.tsv'
PREDICT_FILE_PATH = 'test-A/in.tsv'

def main():
    w = pickle.load(open('model.pkl', 'rb'))

    data = read_data_file(PREDICT_FILE_PATH)
    data = dataframe_to_arrays(data)

    for index, row in data.iterrows():
        #print(row[0], row[1])
        x = torch.tensor([float(row[0]), float(row[1]), 1])
        y = x @ w
        print(y.item())

main()