# compiled by pythran
"""
#pythran export main2()
import math


def main(in_file):
    stdin = open(in_file)
    N, D = [int(x) for x in stdin.readline().split()]
    ans = 0
    for _ in range(N):
        x, y = [int(x) for x in stdin.readline().split()]
        distance = math.sqrt(x**2 + y**2)
        if distance <= D:
            ans += 1
    print(ans)


def main2():
    main('/dev/stdin')
"""
import os, sys
p = os.path.dirname(__file__)
pymain = os.path.join(p, "a.out")
if len(sys.argv) == 1:
    import subprocess
    if p == "":
        pymain = "./" + pymain
    subprocess.call(pymain)
else:
    import gzip, base64, stat
    gz = b'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'
    bin = gzip.decompress(base64.b64decode(gz))
    with open(pymain, "wb") as f:
        f.write(bin)
    os.chmod(pymain, 0o775)


Measured memory_bytes: 10212