rwightman

import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.utils import _pair, _quadruple


class MedianPool2d(nn.Module):
    """ Median pool (usable as median filter when stride=1) module.
    

kevinzakka

"""
Create train, valid, test iterators for CIFAR-10 [1].
Easily extended to MNIST, CIFAR-100 and Imagenet.

[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4
"""

import torch
import numpy as np

simonepri

// Includes functions for exporting active sheet or all sheets as JSON object (also Python object syntax compatible).
// Tweak the makePrettyJSON_ function to customize what kind of JSON to export.

var FORMAT_ONELINE   = 'One-line';
var FORMAT_MULTILINE = 'Multi-line';
var FORMAT_PRETTY    = 'Pretty';

var LANGUAGE_JS      = 'JavaScript';
var LANGUAGE_PYTHON  = 'Python';

xsleonard

unsigned char* hexstr_to_char(const char* hexstr)
{
    size_t len = strlen(hexstr);
    IF_ASSERT(len % 2 != 0)
        return NULL;
    size_t final_len = len / 2;
    unsigned char* chrs = (unsigned char*)malloc((final_len+1) * sizeof(*chrs));
    for (size_t i=0, j=0; j<final_len; i+=2, j++)
        chrs[j] = (hexstr[i] % 32 + 9) % 25 * 16 + (hexstr[i+1] % 32 + 9) % 25;
    chrs[final_len] = '\0';