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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 {
@usamec
usamec / GRU tuning.ipynb
Created February 6, 2020 14:24
GRU tuning
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@usamec
usamec / resumable_sampler.py
Created August 25, 2020 10:50
Resumable (and savable) random sampler for Pytorch data loader
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``.