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np.repeat([1,2], 4)
array([1, 1, 1, 1, 2, 2, 2, 2])

np.tile([1,2], 4)
array([1, 2, 1, 2, 1, 2, 1, 2])

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两者是一样的

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curl ipinfo.io/ip

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sudo usermod -a -G sudo <username>

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按照每个channel进行做batch norm

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.if
.ifn
.ifnn
.main
.not
.par
.print
.return
.while

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先按v

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iw …inner word
aw …a word
iW …inner WORD
aW …a WORD
is …inner sentence
as …a sentence
ip …inner paragraph
ap …a paragraph
it …inner tag
at …a tag
i( or i) …inner block
a( or a) …a block
i< or i> …inner block
a< or a> …a block
i{ or i} …inner block
a{ or a} …a block
i[ or i] …inner block
a[ or a] …a block
i" …inner block
a" …a block
i` …inner block
a` …a block

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import glob
import tqdm
from multiprocessing import Process, Queue
import time
import math
import alog, os
from skimage import io
import argparse

# 在主进程中创建特殊字典
m = Manager()
d = m.dict()

# split a list into evenly sized chunks
def chunks(l, n):
    return [l[i:i+n] for i in range(0, len(l), n)]

def do_job(job_id, data_slice):
    for filename in (data_slice):
        try:
            # print(filename)
            if not os.path.exists(filename):
                print("not exist")
            img = io.imread(filename)
        except:
            print(filename)

def dispatch_jobs(data, job_number):
    total = len(data)
    chunk_size = math.ceil(total / job_number)
    slice = chunks(data, chunk_size)
    jobs = []

    for i, s in enumerate(slice):
        j = Process(target=do_job, args=(i, s))
        j.daemon = True
        jobs.append(j)
    for j in jobs:
        j.start()
    exit_codes = [p.join() for p in jobs]
    print("finish")
    return exit_codes

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Process some integers.')
    parser.add_argument('--path', type=str, 
                    help='path')

    args = parser.parse_args()

    print("waiting...")
    img_path = os.path.join(args.path, "*.jpg")
    data = [x for x in glob.glob(img_path)]

    dispatch_jobs(data, 40)