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#!/usr/bin/env python
'''
minimal reference implementation of bitcoin's secp256k1 with general prime field

requires pari && cypari2 for certain operations.
'''

class EcPoint:
    __slots__ = ('x', 'y')
    def __init__(self, x, y):

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class memfd_create:
    '''create in memory file with actual fileno using memfd_create
    usage:
        with memfd_create('file_name') as f:
            pass # treat f as file-like in binary mode
    '''
    import ctypes, os
    _libc = ctypes.CDLL(None)
    _syscall = _libc.syscall
    def __init__(self, name:str):

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#!/usr/bin/env python
import io
import tarfile
a_content = '''
content:aaa
content:111
'''
b_content = '''
content:bbb
content:222

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# binary carry accumulator with O(log(N)) space requirement
# better numerical stability when adding lots of small numbers
class Accumulator:
    __slots__ = ('fn', 'data', 'index', 'init')
    def __init__(self, size=31, init=0., fn='add'):
        if fn == 'mean':
            fn=lambda x,wx,y,wy:(x*wx+y*wy)/(wx+wy)
        elif fn == 'add':
            fn=lambda x,wx,y,wy:x+y
        self.fn = fn

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#!/usr/bin/env python3
import os
import sys
import subprocess as subp

if len(sys.argv) != 2:
    appname = sys.argv[0]
    print('%s - unmount USB directory and power it off' % appname, file=sys.stderr)
    print('Usage: %s <directory>' % appname, file=sys.stderr)
    sys.exit(-1)

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#include <stdlib.h>
#include <vector>
#include <string>
#include "wstp.h"

using namespace std;

int main() {
    int err;
    auto env_p = WSInitialize((void*)0);

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from random import randint
from time import time
import numpy as np
import theano as th
import theano.tensor as T
from theano.tensor.padding import idx, at_idx

N = 256

x = T.matrix()

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from itertools import product
from random import randint
from time import time
import numpy as np
import theano as th
T = th.tensor
from theano.tensor.padding import idx, at_idx
from theano.tensor.signal import conv

N = 256

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The snippet for scan test is:

x = T.matrix()
y, _ = th.scan(fn=lambda x : T.sum(x*x), sequences=x)
fn_sum_scan = theano.function([x], y)
xval = np.random.randn(5000,10000).astype(np.float32)
timeit(fn(xval))

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from __future__ import print_function
from time import time

import theano as th
import theano.tensor as T
import numpy as np

USE_PROFILER = True

if not USE_PROFILER: