Flecart

import torch
import torch.nn as nn
import torch.optim as optim
from torch.distributions import Categorical
import numpy as np

# Define a simple Bayesian Neural Network (BNN) with MC Dropout
class BayesianNN(nn.Module):
    def __init__(self, input_dim, output_dim, hidden_dim=50):
        super(BayesianNN, self).__init__()

Flecart

from re import I
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import multivariate_normal

# Generate synthetic data (2D points for visualization)
def generate_data():
    np.random.seed(42)
    data = np.vstack([
        np.random.multivariate_normal([5, 5], [[1, 0], [0, 1]], 50),

Flecart

#!/usr/bin/env python3

import sys
import os
import re
import subprocess

# Function to display help information
def display_help():
    print("A script to build tex files for your papers")

Flecart

import pandas as pd
from geopy.geocoders import Nominatim
import folium

# Load the CSV file with pandas
df = pd.read_csv('access-log.csv')  # Replace 'ip_addresses.csv' with your CSV file name


filtered_df = df[~df['Source IP'].str.startswith('192.168.1.')]
# Initialize geocoder

Flecart

#diary #pensieri
import os

def add_tag(file_name):
    with open(file_name, 'r+') as f:
        content = f.read()
        f.seek(0, 0)
        
        # if a string is in the file then print helloworld