ium_444498/evaluation.py

37 lines
941 B
Python
Raw Normal View History

2022-05-08 20:13:10 +02:00
import matplotlib.pyplot as plt
import torch
from torch.utils.data import DataLoader
from neutral_network import MLP, AtpDataset, test
def load_model():
model = MLP()
model.load_state_dict(torch.load('./model.zip'))
return model
def load_dev_dataset(batch_size=64):
atp_dev = AtpDataset('atp_dev.csv')
return DataLoader(atp_dev, batch_size=batch_size)
def make_plot(values):
build_nums = list(range(1, len(values) + 1))
plt.xlabel('Build number')
plt.ylabel('MSE Loss')
plt.plot(build_nums, values, label='Model MSE Loss over builds')
plt.legend()
plt.savefig('plot.png')
model = load_model()
dataloader = load_dev_dataset()
loss_fn = torch.nn.MSELoss()
loss = test(dataloader, model, loss_fn)
with open('eval_result.txt', 'a+') as f:
f.write(f'{str(loss)}\n')
with open('eval_result.txt', 'r') as f:
values = [float(line) for line in f.readlines() if line]
make_plot(values)