Ir1d

import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as checkpoint
import numpy as np
import math

def drop_path(x, drop_prob: float = 0., training: bool = False, scale_by_keep: bool = True):
    """Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
    This is the same as the DropConnect impl I created for EfficientNet, etc networks, however,

Ir1d

PublicTransitHard http://community.topcoder.com/stat?c=problem_statement&pm=13797

SimilarNames http://community.topcoder.com/stat?c=problem_statement&pm=12868 
n个字符串s_1, s_2, …, s_n，m个条件(a_i, b_i)，统计满足s_{p(a_i)}是s_{p(b_i)}前缀的排列p_1, p_2, …, p_n数量 
n <= 50, |s_i| <= 50, m <= 8 

BichromeSky http://community.topcoder.com/stat?c=problem_statement&pm=13711 
n个红点，m个蓝点，没有三点共线，第i个红点以p_i的概率出现，求红点的凸包包含所有蓝点的概率 
n, m <= 100 

Ir1d

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