| from tensorflow.keras.models import load_model |
| from tensorflow.keras.preprocessing.sequence import pad_sequences |
| import numpy as np |
| import csv |
| from tqdm import tqdm |
|
|
| model = load_model("net.h5") |
|
|
| dataset = "dataset_test.csv" |
| inp_len = 32 |
|
|
| X = [] |
| y = [] |
|
|
| with open(dataset, 'r') as f: |
| csv_reader = csv.reader(f) |
| for row in tqdm(csv_reader): |
| if row == []: continue |
| label = int(row[0]) |
| text = row[1] |
| text = [ord(char) for char in text] |
| X.append(text) |
| y.append(label) |
|
|
| X = np.array(pad_sequences(X, maxlen=inp_len, padding='post')) |
| y = np.array(y) |
|
|
| loss, accuracy = model.evaluate(X, y) |
| print(f"Loss: {loss}\nAccuracy: {accuracy}") |
|
|
|
|
