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import geopandas as gpd
import matplotlib.pyplot as plt
import pandas as pd
import matplotlib.colors as mcolors
from shapely.geometry import Polygon, MultiPolygon
import shapely.ops
import os.path
def get_text_color(fill_color):
import instructor
from pydantic import BaseModel, Field
from typing import overload, Union, Literal, Generator
from tqdm.asyncio import tqdm
import asyncio
import numpy as np
import json
import os, sys
import diskcache, inspect, functools
import random
import instructor
from pydantic import BaseModel, Field
from typing import overload, Union, Literal, Generator
from tqdm.asyncio import tqdm
import asyncio
import numpy as np
import json
import os, sys
import diskcache, inspect, functools
import random
@thomasahle
thomasahle / mlps.py
Created July 7, 2024 17:30
Randomly Initialized MLPs with Different Activation Functions
import torch
import math
from torch import nn
import torch.nn.functional as F
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as mcolors
import numpy as np
import seaborn as sns
from collections import Counter
from manim import *
import networkx as nx
import random
import numpy as np
import itertools
class UF:
def __init__(self, ids):
from collections import Counter
from manim import *
import networkx as nx
import random
import numpy as np
import itertools
class UF:
def __init__(self, ids):
from collections import Counter
from manim import *
import networkx as nx
import random
import numpy as np
import itertools
class UF:
def __init__(self, ids):
import networkx as nx
import matplotlib.pyplot as plt
import random
import matplotlib.animation as animation
import numpy as np
# Step 1: Create the graph
G = nx.MultiGraph()
edges = [
(1, 2), (1, 3), (1, 4), (1, 5), (2, 3), (2, 4), (2, 5), (2, 6), (3, 4), (3, 5), (3, 6),
import torch
import torch.nn as nn
import torch.optim as optim
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import tqdm
# Generate random dataset
np.random.seed(0)
import dspy
from pydantic import BaseModel
from typing import List
class State(BaseModel):
name: str
abbreviation: str
capital: str
class States(BaseModel):