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| import argparse | |
| import os | |
| import sys | |
| import time | |
| import tempfile | |
| import json | |
| import urllib.request | |
| import shutil | |
| import platform | |
| from pathlib import Path |
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| 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; |
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| 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 |
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| 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; |
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| --- | |
| title: "distance_graph" | |
| output: html_document | |
| --- | |
| ```{r setup, include=FALSE} | |
| knitr::opts_chunk$set(echo = TRUE) | |
| library(ggplot2) | |
| ``` |
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| #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() { |
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| #!/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}" |
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| 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) |
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