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import re


def delimited_case(s: str, *, delimiter: str) -> str:
    return re.sub(
        r"(([a-z0-9])(?=[A-Z][a-zA-Z0-9])|([A-Z0-9])(?=[A-Z0-9][a-z]))",
        rf"\1{delimiter}",
        re.sub(r"[^a-zA-Z0-9]+", delimiter, s),
    )

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import numpy as np

def haversine_distance_matrix(lats, longs):
    lats = np.radians(lats.reshape(-1, 1))
    longs = np.radians(longs.reshape(1, -1))
    return 2 * np.arcsin(np.sqrt((1 - np.cos(lats - lats.T) + np.cos(lats) * np.cos(lats.T) * (1 - np.cos(longs - longs.T))) / 2))
  

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import unittest
from concurrent.futures import ThreadPoolExecutor


def multi_threaded(*, threads=2):
    def decorator(test_cls):
        for name, test_fn in test_cls.__dict__.copy().items():
            if not (name.startswith("test") and callable(test_fn)):
                continue

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from typing import Any

from metadata_filter import MetadataFilter, MetadataFilterOperator

# https://docs.trychroma.com/usage-guide#using-where-filters
OPERATOR_MAP = {
    MetadataFilterOperator.AND: "$and",
    MetadataFilterOperator.OR: "$or",
    MetadataFilterOperator.EQ: "$eq",
    MetadataFilterOperator.NE: "$ne",

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import functools
import pathlib
import sys

import libcst as cst


def main(root):
    root = pathlib.Path(root)
    fn = functools.partial(remove_annotations, annotations_remover=AnnotationRemover())

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Benchmark script and results for torchvision.transforms.functional v1 vs v2

Run benchmark.py to reproduce the results.

To add a new benchmark, add a BenchmarkConfig to BENCHMARK_CONFIGS in configs.py

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import pathlib
from urllib.parse import urlparse

import requests
import tqdm


def download(url, root=".", *, name=None, chunk_size=32 * 1024):
    root = pathlib.Path(root)
    root.mkdir(exist_ok=True, parents=True)

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Hope this works!

Hopefully you can read this 🎉

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import os
import pathlib
import re
import shlex
import subprocess
import sys


def main():
    if git("status", "--porcelain"):

pmeier

import itertools
from typing import Collection

import networkx as nx

# overwrite this with the array API that you want to test
import numpy as array_api


def maybe_add_dtype(