Steganografiya quyidagi sohalarda qo'llaniladi, lekin ular bilan cheklanmaydi

# Verify stolen model
verification = trainer_wm.verify(ownership)
assert verification['is_stolen'] is True


if __name__ == '__main__':
tweet_analysis()


import hashlib
import hmac
import random
from math import floor

import bitstring
import numpy as np
from cryptography.fernet import Fernet
from sklearn import svm
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
from sklearn.linear_model import LogisticRegression, RidgeClassifier

from mlmodelwatermarking.verification import verify


class Trainer:

def __init__(self,
model,
args):
"""Main wrapper class to watermark sk models.

Args:
model (Object): Model
args (dict): args for watermarking

"""
self.model = model
self.args = args
self.encryption = args.encryption
self.nb_blocks = args.nb_blocks
self.metric = args.metric
self.trigger_size = args.trigger_size
self.watermarked = False
# Supported models
self.Classifiers = [RandomForestClassifier,
svm.SVC,
RidgeClassifier,
LogisticRegression]
self.Regressors = [RandomForestRegressor]

def get_trigger_block(self, block_id):
"""Return a precise trigger block."""
return self.triggers['block_' + str(block_id)], self.triggers['shape']

def generate_trigger(self, X_train, y_train, mode='CLASSIFICATION'):
"""Generate trigger data for watermark.

Returns:
ownership (dict): Watermark triggers information