Kazuhiro Serizawa serihiro

結果

解答

A

B

C

[:contents]

結果

問題	ACまでに要した時間	AC	WA	TLE
A	:	0	0	0
B	:	0	0	0

I have tried the quickstart of https://github.com/blue-oil/blueoil/tree/master/dlk .

venv ❯ PYTHONPATH=python/dlk python python/dlk/scripts/generate_project.py --help

Options:
  -i, --input_path PATH           protobuf path which you want to convert to C
                                  codes
  -o, --output_path TEXT          output path which you want to export any
                                  generated files

	package org.example;

	import java.io.IOException;
	import org.apache.lucene.analysis.standard.StandardAnalyzer;
	import org.apache.lucene.document.Document;
	import org.apache.lucene.document.Field;
	import org.apache.lucene.document.StringField;
	import org.apache.lucene.document.TextField;
	import org.apache.lucene.index.DirectoryReader;
	import org.apache.lucene.index.IndexWriter;

	import streamlit as st
	from elasticsearch import Elasticsearch


	def main():
	st.title("Streamlit ES Viewer")
	with st.form("my_form", clear_on_submit=False):
	keyword = st.text_input("keyword", "Python")
	title_weight = st.number_input(
	label="title weight", value=1.0, min_value=0.0, max_value=5.0, step=0.1

	import javax.annotation.Nullable;

	public class Employee {
	private String firstName;
	private String lastName;
	private Integer age;

	public Employee(String firstName, String lastName, Integer age){
	this.firstName = firstName;
	this.lastName = lastName;

	---
	title: "distance_graph"
	output: html_document
	---

	```{r setup, include=FALSE}
	knitr::opts_chunk$set(echo = TRUE)
	library(ggplot2)
	```

	#include <bits/stdc++.h>

	#define REP(i, x) REPI(i, 0, x)
	#define REPI(i,a,b) for(int i=int(a);i<int(b);++i)
	#define ALL(x) (x).begin(), (x).end()

	typedef long long ll;
	using namespace std;

	int main() {

	#!/bin/bash

	BASE_DIR="/path/to/imagenet/train"
	ALL_DIRS=`ls $BASE_DIR \| grep -v .tar \| grep -v .sh`

	total_size=0
	total_count=0
	for dir in $ALL_DIRS
	do
	target_dir="${BASE_DIR}/${dir}"

	import argparse
	import onnx
	import numpy as np
	from onnx import numpy_helper
	from PIL import Image


	def relu(x: np.ndarray) -> np.ndarray:
	return np.maximum(x, 0)