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#!/usr/bin/env python3
import argparse
import re
import yaml
import json
from pathlib import Path
from comet_ml import ExistingExperiment

from src.marcos import *
from src.utils import run_cmd

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#!/usr/bin/env python3

from pathlib import Path
import json
import time
import re
from numpy.lib.format import open_memmap
import numpy as np
import kaldiio
import pickle

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GAMMA =1.0/10 # (1/D)

### Model ###
def sir_diff_eq(y, t, r0, gamma, N, t_y_interpolated):
    S, I, R = y

    def beta(t):
        try:
            return t_y_interpolated[int(t)] * r0 * gamma
        except:

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# for  mathjax and katex usage
snippet $$
	<span>$${1}$</span>${0}

snippet \[
	<div>
	\[
	${1}
	\]
	</div>

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snippet my_template
	#pragma GCC optimize ("O2")
	#include<bits/stdc++.h>
	#include<unistd.h>
	using namespace std;
	#define ALL(x) begin(x),end(x)
	#define IOS ios_base::sync_with_stdio(0); cin.tie(0)
	//freopen(name".in", "r", stdin);
	//freopen(name".out", "w", stdout);
	template<typename A, typename B>

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{{ $ := .root }}
{{ $page := .page }}

<!-- Accomplishments widget -->
<div class="row">
  <div class="col-12 col-lg-4 section-heading">
    <h1>{{ with $page.Title }}{{ . | markdownify }}{{ end }}</h1>
    {{ with $page.Params.subtitle }}<p>{{ . | markdownify }}</p>{{ end }}
  </div>
  <div class="col-12 col-lg-8">

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import os
from pathlib import Path
from comet_ml import Experiment, ExistingExperiment

from src.marcos import *
import src.monitor.logger as logger

class Dashboard:
    """Record training/evaluation statistics to comet
    :params config: dict

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import torch 
import numpy as np
from pathlib import Path
from torch.utils.data import Dataset, DataLoader, Sampler
from torch.nn.utils.rnn import pad_sequence
import src.monitor.logger as logger
import random

# from numpy.lib.format import open_memmap

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class DataContainer:
    def __init__(self, data_dirs, batch_size, dev_batch_size, is_memmap, 
                 is_bucket, num_workers=0, min_ilen=None, max_ilen=None, 
                 half_batch_ilen=None, bucket_reverse=False, shuffle=True, 
                 read_file=False, drop_last=False, pin_memory=True):

        self.data_dirs = data_dirs
        self.num_datasets = len(self.data_dirs)
        self.batch_size = batch_size
        self.is_memmap = is_memmap

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#include<bits/stdc++.h>
using namespace std;

class Solution{
  public:
    vector<int> findOrder(int numCourses, vector<pair<int, int>>& prerequisites) {
      vector<int> seq;
      // 0 -> not visited
      // 1 -> visiting
      // 2 -> already left