Vlado Boza usamec
usamec
/ resumable_sampler.py
Created
August 25, 2020 10:50
Resumable (and savable) random sampler for Pytorch data loader
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| import torch | |
| class ResumableRandomSampler(torch.utils.data.Sampler): | |
| r"""Samples elements randomly. If without replacement, then sample from a shuffled dataset. | |
| If with replacement, then user can specify :attr:`num_samples` to draw. | |
| Arguments: | |
| data_source (Dataset): dataset to sample from | |
| replacement (bool): samples are drawn on-demand with replacement if ``True``, default=``False`` | |
| num_samples (int): number of samples to draw, default=`len(dataset)`. This argument | |
| is supposed to be specified only when `replacement` is ``True``. |
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usamec
/ AhoCorasick.Scala
Last active
September 17, 2017 22:18
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| package com.example | |
| import scala.annotation.tailrec | |
| import scala.collection.immutable.Queue | |
| case class TrieNode[Char, Value](values: List[Value], next: Map[Char, TrieNode[Char, Value]]) { | |
| def add(str: Seq[Char], value: Value): TrieNode[Char, Value] = { | |
| @tailrec | |
| def addWalkDown(node: TrieNode[Char, Value], stack: List[(Char, TrieNode[Char, Value])], remaining: List[Char], value: Value): TrieNode[Char, Value] = { | |
| remaining match { |