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328c149ed45a41c0b9d6f14659e63599
arena-hard-v0.1
ABC Sequence Puzzles & Groups
[ { "content": "Use ABC notation to write a melody in the style of a folk tune." } ]
b43c07656ead4150b360294ee932b410
arena-hard-v0.1
ABC Sequence Puzzles & Groups
[ { "content": "SOLVE THIS IN C++ : There are three cards with letters a\n, b\n, c\n placed in a row in some order. You can do the following operation at most once:\n\nPick two cards, and swap them.\nIs it possible that the row becomes abc\n after the operation? Output \"YES\" if it is possible, and \"NO\" otherwise.\nInput\nThe first line contains a single integer t\n (1≤t≤6\n) — the number of test cases.\n\nThe only line of each test case contains a single string consisting of each of the three characters a\n, b\n, and c\n exactly once, representing the cards.\n\nOutput\nFor each test case, output \"YES\" if you can make the row abc\n with at most one operation, or \"NO\" otherwise.\n\nYou can output the answer in any case (for example, the strings \"yEs\", \"yes\", \"Yes\" and \"YES\" will be recognized as a positive answer).\n\nExample\ninputCopy\n6\nabc\nacb\nbac\nbca\ncab\ncba\noutputCopy\nYES\nYES\nYES\nNO\nNO\nYES\nNote\nIn the first test case, we don't need to do any operations, since the row is already abc\n.\n\nIn the second test case, we can swap c\n and b\n: acb→abc\n.\n\nIn the third test case, we can swap b\n and a\n: bac→abc\n.\n\nIn the fourth test case, it is impossible to make abc\n using at most one operation." } ]
1f07cf6d146d4038b2b93aaba3935ce0
arena-hard-v0.1
AI & Sequence Alignment Challenges
[ { "content": "Explain the book the Alignment problem by Brian Christian. Provide a synopsis of themes and analysis. Recommend a bibliography of related reading. " } ]
9f25ff7c0d6a4d74846bfe76af8d925c
arena-hard-v0.1
AI & Sequence Alignment Challenges
[ { "content": "Design a semikinematic mounting for a right angle prism with preload provided by a compressed elastomeric pad. The mounting should be designed to ensure proper alignment of the prism with its mounting surface and provide adequate tension to maintain proper load transfer." } ]
04ba0aeb79524f6c8520d47cada34f25
arena-hard-v0.1
AI Image Upscaling
[ { "content": "I have a dataset which contains a list of 2D images, given a new image, how to find the closest image in the dataset" } ]
93c9b4bb32f4422f954c7af9ea2bdfcd
arena-hard-v0.1
AI Image Upscaling
[ { "content": "I have black and white images with 1 pixel width white horizonal lines going through the image. How to detect the lines and remove it?" } ]
ed3077a3443a4cf88233f5bc636e7394
arena-hard-v0.1
AI Startup Business Strategies
[ { "content": "if you were a corporate law with 15 years of mergers and acquisitions experience, how would you pivot to launch an AI enable tech startup step by step and in detail?\n" } ]
90b29911b57848ec89fc7d8c15f27c88
arena-hard-v0.1
AI Startup Business Strategies
[ { "content": "Describe how to incorporate AI in the private equity deal sourcing process" } ]
f54e99e9686549e7a096dd16dbab28e1
arena-hard-v0.1
AWS Cloud Services Essentials
[ { "content": "how does memory affect performance of aws lambda written in nodejs" } ]
7bcf40b22c164f36a85efcbf169da647
arena-hard-v0.1
AWS Cloud Services Essentials
[ { "content": "I have a Python script that scrapes a webpage using Playwright. Now I want to start ten instances of that script in parallel on one AWS EC2 instance, but so that each script binds to a different IP address. How can I do that with Terraform?" } ]
847e0891929a4521aee127ee20b50e30
arena-hard-v0.1
Acrobat PDF Management Tips
[ { "content": "How to add toolbar in a fragment?" } ]
b26d8c58eaa04b1f8e7e88da9ddd4ed9
arena-hard-v0.1
Acrobat PDF Management Tips
[ { "content": "Hi. I have this URL which I can paste in my Microsoft Edge browser, and it downloads a PDF file for me from my Power BI online report. URL is: https://app.powerbi.com/groups/me/rdlreports/1bdef01c-30a3-4150-aff2-b3ec4c9edf86?rp:AdviceDeathScriptMERGEDMonthStartDate=6/1/2023&rp:AdviceDeathScriptMERGEDIncomingcall=Aria%20Park&rdl:format=PDF\n\nOf course, it first asks me to log in to my Power BI account when I first enter the URL, and then it goes directly to the report and downloads the PDF. I wrote a python code to do this for me. The code has managed to download a PDF. However, the PDF produced by the python code won't open - it gives an error when I try to open it \"Adobe acrobat reader could not open 'AriaPark.pdf'...\". I am unsure what the issue is. Perhaps, the issue is that Python code doesn't know my Power-BI login details to access the PDF, or maybe it is something else? Can you please help? The Python code I'm using is below:\n\nimport requests\nimport os\n# Main Power BI report URL\nfull_url = \"https://app.powerbi.com/groups/me/rdlreports/1bdef01c-30a3-4150-aff2-b3ec4c9edf86?rp:AdviceDeathScriptMERGEDMonthStartDate=6/1/2023&rp:AdviceDeathScriptMERGEDIncomingcall=Aria%20Park&rdl:format=PDF\"\n\nresponse = requests.get(full_url)\nfilename = f\"AriaPark.pdf\"\nwith open(filename, 'wb') as file:\n file.write(response.content)\n\nprint(\"Reports have been successfully downloaded.\")\n\n\n" } ]
379a490a6eae40608abf3501807b2545
arena-hard-v0.1
Advanced Algebra and Number Theory
[ { "content": " Consider the state:\n$$\\ket{\\psi} = \\frac{\\ket{00} + \\ket{01} + \\ket{10}}{\\sqrt{3}}$$\n\n(a). Calculate the reduced density matrix of the second qubit of $\\ket{\\psi}$." } ]
92abeb14dc734237a9ff52c4062b9b98
arena-hard-v0.1
Advanced Algebra and Number Theory
[ { "content": "Proof that Q(sqrt(-11)) is a principal ideal domain" } ]
3f85bf93f18343dbb17e228a214a3800
arena-hard-v0.1
Advanced Guitar Chord Theory
[ { "content": "Write me a chord progression in the key of C major. Make it sound sad and slow." } ]
51c444da19ec4cf1a5fc387667e4a7cf
arena-hard-v0.1
Advanced Guitar Chord Theory
[ { "content": "Can you come up with a 12 bar chord progression in C that works in the lydian mode?\n" } ]
e9a2e1240f4a46b6a832bb5d71b20ee1
arena-hard-v0.1
Advanced Mathematical Problem-Solving
[ { "content": "Alice and Bob have two dice. \n\nThey roll the dice together, note the sum of the two values shown, and repeat.\n\nFor Alice to win, two consecutive turns (meaning, two consecutive sums) need to result in 7. For Bob to win, he needs to see an eight followed by a seven. Who do we expect to win this game?\n\nYou are required to provide an analysis which coincides with simulation results. You can supply multiple answers in successive iterations. You are allowed to run a simulation after 2 iterations. After each analysis, provide a reflection on the accuracy and completeness so we might improve in another iteration. If so, end a reply with \"CONTINUE TO ITERATION [x]\" and wait for my input. When there is no more accuracy or completeness issue left to resolve and the mathematical analysis agrees with the simulation results, please end by typing \"SOLVED\". Always end with either \"CONTINUE TO ITERATION [x]\" or \"SOLVED\"." } ]
6b31320632de4e0bbf9b63d3cc78c58e
arena-hard-v0.1
Advanced Mathematical Problem-Solving
[ { "content": "A table-tennis championship for $2^n$ players is organized as a knock-out tournament with $n$ rounds, the last round being the final. Two players are chosen at random. Calculate the probability that they meet: (a) in the first round, (b) in the final, (c) in any round." } ]
46e73778f43143199f88b2e354df85eb
arena-hard-v0.1
Advanced Matplotlib Customizations
[ { "content": "How can I generate a seaborn barplot that includes the values of the bar heights and confidence intervals?" } ]
69120423cec04acca9f2b8d5f68b391c
arena-hard-v0.1
Advanced Matplotlib Customizations
[ { "content": "Can you give me some Seaborn code for plotting the ECDF of a KDE-augmented dataset?" } ]
ed426d6069064ad9bf21e83bcb29f356
arena-hard-v0.1
Advanced Random Number Techniques
[ { "content": "Write a function to generate cryptographically secure random numbers. " } ]
9d7d8b61b76f4695a5590a9f6bfc0017
arena-hard-v0.1
Advanced Random Number Techniques
[ { "content": "How to set seeds for random generator in Python in threads?" } ]
2089a27fe9e2495d97a0cf27619d11a3
arena-hard-v0.1
Advanced Regex Techniques
[ { "content": "Regex to delect all <g> elements containing a string `transform=\"matrix(0.998638,0,0,-0.998638,0.39215,439.799858)\"` please. there can be line breaks too." } ]
fae4f754f12f40db8178d3683eb1eddc
arena-hard-v0.1
Advanced Regex Techniques
[ { "content": "write pcre regex for not containing C:\\" } ]
9db47b0594014729b777c10678597e7f
arena-hard-v0.1
Advanced TypeScript Concepts
[ { "content": "make me a javascript code to find an object by its name deep inside a given object, make sure that this code does not use recursion and can return the path used to reach the object" } ]
31615ee9cc8448cd9d225bdb87a5ffdc
arena-hard-v0.1
Advanced TypeScript Concepts
[ { "content": "If I have a TypeScript class:\n\nclass Foo {\n ReactProperties: {\n a: string;\n }\n}\n\nHow do I extract the type of the ReactProperties member object from the type Class?" } ]
51139d7be0fe4a07bc2d577614ac4487
arena-hard-v0.1
Agile Scrum Leadership
[ { "content": "Considering Tools For Thought and the organization of personal knowledge, please list some best practice frameworks that detail a system of procedures and best practice. Please make a comprehensive list of frameworks and summarize the top three in more detail. " } ]
5c5cb72f4d7b43caa476359c57e898de
arena-hard-v0.1
Agile Scrum Leadership
[ { "content": "Introduce Ethan, including his experience-level with software development methodologies like waterfall and agile development. Describe the major differences between traditional waterfall and agile software developments. In his opinion, what are the most notable advantages and disadvantages of each methodology?" } ]
face6a5531854b188dfc266e289ee595
arena-hard-v0.1
Algorithms and Problem Solving
[ { "content": "Problem\nA mother bought a set of \n�\nN toys for her \n2\n2 kids, Alice and Bob. She has already decided which toy goes to whom, however she has forgotten the monetary values of the toys. She only remembers that she ordered the toys in ascending order of their value. The prices are always non-negative.\n\nA distribution is said to be fair when no matter what the actual values were, the difference between the values of the toys Alice got, and the toys Bob got, does not exceed the maximum value of any toy.\n\nFormally, let \n�\n�\nv \ni\n​\n be the value of \n�\ni-th toy, and \n�\nS be a binary string such that \n�\n�\n=\n1\nS \ni\n​\n =1 if the toy is to be given to Alice, and \n�\n�\n=\n0\nS \ni\n​\n =0 if the toy is to be given to Bob.\nThen, the distribution represented by \n�\nS is said to be fair if, for all possible arrays \n�\nv satisfying \n0\n≤\n�\n1\n≤\n�\n2\n≤\n.\n.\n.\n.\n≤\n�\n�\n0≤v \n1\n​\n ≤v \n2\n​\n ≤....≤v \nN\n​\n ,\n\n∣\n∑\n�\n=\n1\n�\n�\n�\n⋅\n[\n�\n�\n=\n1\n]\n−\n∑\n�\n=\n1\n�\n�\n�\n⋅\n[\n�\n�\n=\n0\n]\n∣\n≤\n�\n�\n∣\n∣\n​\n \ni=1\n∑\nN\n​\n v \ni\n​\n ⋅[s \ni\n​\n =1]− \ni=1\n∑\nN\n​\n v \ni\n​\n ⋅[s \ni\n​\n =0] \n∣\n∣\n​\n ≤v \nN\n​\n \nwhere \n[\n�\n]\n[P] is \n1\n1 iff \n�\nP is true, and \n0\n0 otherwise.\n\nYou are given the binary string \n�\nS representing the distribution.\nPrint YES if the given distribution is fair, and NO otherwise.\n\nInput Format\nThe first line of input will contain a single integer \n�\nT, denoting the number of test cases.\nEach test case consists of two lines of input.\nThe first line of each test case contains a single integer \n�\nN, the number of toys.\nThe second line of each test case contains a binary string \n�\nS of length \n�\nN.\nOutput Format\nFor each test case, output on a new line the answer: YES or NO depending on whether \n�\nS represents a fair distribution or not.\n\nEach character of the output may be printed in either lowercase or uppercase, i.e, the strings NO, no, nO, and No will all be treated as equivalent.\n\nConstraints\n1\n≤\n�\n≤\n1\n0\n4\n1≤T≤10 \n4\n \n1\n≤\n�\n≤\n1\n0\n5\n1≤N≤10 \n5\n \nThe sum of \n�\nN over all test cases won't exceed \n3\n⋅\n1\n0\n5\n3⋅10 \n5\n .\n�\nS is a binary string of length \n�\nN.\nSample 1:\nInput\nOutput\n6\n1\n1\n2\n00\n4\n1010\n4\n1100\n6\n010101\n5\n00001\nYES\nNO\nYES\nNO\nYES\nNO\nExplanation:\nTest case \n1\n1: The given formula reduces to \n∣\n�\n1\n∣\n≤\n�\n1\n∣v \n1\n​\n ∣≤v \n1\n​\n , which is true since \n�\n1\n≥\n0\nv \n1\n​\n ≥0.\n\nTest case \n2\n2: The distribution is not fair for \n�\n1\n=\n�\n2\n=\n1\nv \n1\n​\n =v \n2\n​\n =1, hence the answer is NO.\nNote that the distribution is fair for \n�\n1\n=\n�\n2\n=\n0\nv \n1\n​\n =v \n2\n​\n =0, but we need to check if its fair for all possible \n�\nv satisfying the constraints.\n\nTest case \n3\n3: It can be proved that the distribution is always fair.\n\nTest case \n4\n4: The distribution is not fair for \n�\n=\n[\n1\n,\n2\n,\n4\n,\n8\n]\nv=[1,2,4,8].\n\naccepted\nAccepted\n28\ntotal-Submissions\nSubmissions\n580\naccuracy\nAccuracy\n5.17 give a short c program to it" } ]
dbff049f35b142249c18d8faebe84039
arena-hard-v0.1
Algorithms and Problem Solving
[ { "content": "Problem\nYou are hosting a chess tournament with \n2\n�\n2N people. Exactly \n�\nX of them are rated players, and the remaining \n2\n�\n−\n�\n2N−X are unrated players.\n\nYour job is to distribute the players into \n�\nN pairs, where every player plays against the person paired up with them.\n\nSince you want the rated players to have an advantage, you want to pair them with unrated players. Thus, you want to minimize the number of rated players whose opponent is also rated.\nPrint the minimum number of rated players whose opponents are also rated, among all possible pairings.\n\nInput Format\nThe first line of input will contain a single integer \n�\nT, denoting the number of test cases.\nEach test case consists of \n1\n1 line containing \n2\n2 space-separated integers \n�\nN and \n�\nX, meaning there are \n2\n�\n2N players, and \n�\nX of them are rated.\nOutput Format\nFor each test case, output on a new line the minimum number of rated players who will have rated opponents.\n\nConstraints\n1\n≤\n�\n≤\n2600\n1≤T≤2600\n1\n≤\n�\n≤\n50\n1≤N≤50\n0\n≤\n�\n≤\n2\n⋅\n�\n0≤X≤2⋅N\nSample 1:\nInput\nOutput\n6\n1 0\n1 1\n1 2\n4 4\n4 6\n10 20\n0\n0\n2\n0\n4\n20\nExplanation:\nTest case \n1\n1: There is no rated player and hence no rated player has a opponent who is also rated. Thus the answer is \n0\n0.\n\nTest case \n2\n2: There is only one match, which is between a rated player and an unrated player. Thus the answer is \n0\n0.\n\nTest case \n3\n3: There is only one match, which is between \n2\n2 rated players. Thus the answer is \n2\n2 as both contribute to the count of rated players whose opponents are also rated.\n\naccepted\nAccepted\n630\ntotal-Submissions\nSubmissions\n1656\naccuracy\nAccuracy\n45.65\nDid you like the problem statement?\n2 users found this helpful\nC\n​\n\n\n\n0:0\n give a c program to it" } ]
60856d87b3484a4db45a67ac560a2b06
arena-hard-v0.1
Android Development Challenges
[ { "content": "[CXX1429] error when building with ndkBuild using E:\\Dhruvin kheni\\Backup\\Backup\\Pancard_pe_loan\\Pancard_pe_loan\\app\\src\\main\\jni\\Android.mk: Android NDK: Your APP_BUILD_SCRIPT points to an unknown file: E:\\Dhruvin kheni\\Backup\\Backup\\Pancard_pe_loan\\Pancard_pe_loan\\app\\src\\main\\jni\\Android.mk \n\nC++ build system [configure] failed while executing:\n @echo off\n \"C:\\\\Users\\\\BMV3\\\\AppData\\\\Local\\\\Android\\\\Sdk\\\\ndk\\\\25.1.8937393\\\\ndk-build.cmd\" ^\n \"NDK_PROJECT_PATH=null\" ^\n \"APP_BUILD_SCRIPT=E:\\\\Dhruvin kheni\\\\Backup\\\\Backup\\\\Pancard_pe_loan\\\\Pancard_pe_loan\\\\app\\\\src\\\\main\\\\jni\\\\Android.mk\" ^\n \"NDK_APPLICATION_MK=E:\\\\Dhruvin kheni\\\\Backup\\\\Backup\\\\Pancard_pe_loan\\\\Pancard_pe_loan\\\\app\\\\src\\\\main\\\\jni\\\\Application.mk\" ^\n \"APP_ABI=arm64-v8a\" ^\n \"NDK_ALL_ABIS=arm64-v8a\" ^\n \"NDK_DEBUG=1\" ^\n \"APP_PLATFORM=android-26\" ^\n \"NDK_OUT=E:\\\\Dhruvin kheni\\\\Backup\\\\Backup\\\\Pancard_pe_loan\\\\Pancard_pe_loan\\\\app\\\\build\\\\intermediates\\\\cxx\\\\Debug\\\\6h295i67/obj\" ^\n \"NDK_LIBS_OUT=E:\\\\Dhruvin kheni\\\\Backup\\\\Backup\\\\Pancard_pe_loan\\\\Pancard_pe_loan\\\\app\\\\build\\\\intermediates\\\\cxx\\\\Debug\\\\6h295i67/lib\" ^\n \"APP_SHORT_COMMANDS=false\" ^\n \"LOCAL_SHORT_COMMANDS=false\" ^\n -B ^\n -n\n from E:\\Dhruvin kheni\\Backup\\Backup\\Pancard_pe_loan\\Pancard_pe_loan\\app\nC:/Users/BMV3/AppData/Local/Android/Sdk/ndk/25.1.8937393/build/../build/core/add-application.mk:88: *** Android NDK: Aborting... . Stop.\nAffected Modules: app\n" } ]
7cbfd2a54982478e8228877fd89b4600
arena-hard-v0.1
Android Development Challenges
[ { "content": "User\nI am an Android developer. When running my ONNX runtime application, the CPU utilisation is ~40% . How can I increase the CPU usage for my app?" } ]
6a82bab747f644fb9c5d648114fb6597
arena-hard-v0.1
Approximate Vector Subset Selection
[ { "content": "Provide 15 attack vectors in Manufacturing sector and methods to mitigate the identied risks " } ]
f7c6dcee42e646abac890e3bb540d403
arena-hard-v0.1
Approximate Vector Subset Selection
[ { "content": "In what order should I learn Deep Learning from the foundations such as matrices and vectors all the way to transformers?" } ]
66de1a59fcb2421c978bd9bb4be8ea6c
arena-hard-v0.1
Archive Formats and Encryption
[ { "content": "Write a complete Python program to archive files in a specified folder into separate zip files on Linux." } ]
32e124cb2eae422ba5c33985b00cd8c0
arena-hard-v0.1
Archive Formats and Encryption
[ { "content": "I have a backup of my Linux Mint system from last month in a set of .gz (zipped tar) files. What arguments can I use with tar to update any files that have changed, without re-archiving unchanged files?" } ]
a3dfabb011e245e190a0147fef6ff14b
arena-hard-v0.1
Array Pair Sum Optimization
[ { "content": "Given a binary array 'nums', you are required to find the maximum length of a contiguous subarray that contains an equal number of 0s and 1s.\n\nExplanation:\n\nA binary array is an array that contains only 0s and 1s.\nA subarray is any subset of the indices of the original array.\nA contiguous subarray is a subarray in which all the elements are consecutive, i.e., any element between the first and last element of the subarray is also part of it.\nExamples:\nInput :nums = [0, 1]\nOutput : 2\nExplanation: The longest contiguous subarray with an equal number of 0s and 1s is [0, 1] with a length of 2.\nInput : nums = [0, 1, 0]\nOutput : 2\nExplanation: The longest contiguous subarray with an equal number of 0s and 1s is either [0, 1] or [1, 0], both with a length of 2.\nInput : nums = [0, 0, 0, 1, 1, 1]\nOutput : 6\nExplanation: The longest contiguous subarray with an equal number of 0s and 1s is [0, 0, 0, 1, 1, 1] with a length of 6.\nThe problem requires finding the maximum length of a contiguous subarray in the binary array 'nums' that contains an equal number of 0s and 1s." } ]
20c9d951035f4b778d201db3859786c9
arena-hard-v0.1
Array Pair Sum Optimization
[ { "content": "Help me solve the following qn. Please provide a intuitive easy to understand step by step solution:\n\nGiven two sorted arrays nums1 and nums2 of size m and n respectively, return the median of the two sorted arrays.\n\n" } ]
65e7230293c14227b2bf7fc8113e8378
arena-hard-v0.1
Array Positioning & SAT Solving
[ { "content": "In GAMS, assume I have s parameters which is indexed over two sets P1(A,B), and I have another one-to-one-mapping that maps exactly each element of B to each element of C. How can I create a new parameter P2(A,C) such that each value of P2 takes the mapped value from P1?" } ]
91e8fc5340fe4c21b697ec329bf62eb2
arena-hard-v0.1
Array Positioning & SAT Solving
[ { "content": "I have a set of examples (that is assignments of $n$ variables $x_1 ... x_n$ that are labeled as solution (+) or non-solution (-). The goal is to find the minimum subset of variables in $x_1 ... x_n$ such that it is possible to split between (+) and (-) by seeing only theses variables." } ]
4587e8a3798646af8f351685e6949788
arena-hard-v0.1
Aspiring Data Scientist Guidance
[ { "content": "You are a data scientist, output a Python script in OOP for a contextual multi armed bandit sampling from 3 models" } ]
2a6d0b92fbb5448bb2f7540db9645674
arena-hard-v0.1
Aspiring Data Scientist Guidance
[ { "content": "What is the most successful go to market strategy for a managed services business?" } ]
70dccc6c737b47ff842cbb50ed6b249a
arena-hard-v0.1
Audio Signal Direction Detection
[ { "content": "Hello, what do you think of this arduino code in regards to understandability, optimization and size?\nAny suggestions for improvements?\n\nvoid cycleLEDs(int interval) {\n const int nOutPins = sizeof(outPins) / sizeof(outPins[0]);\n static unsigned long lastChange = 0;\n static int currIndex = 0; // Use static to retain value between function calls\n int nextIndex = 0;\n \n if (millis() >= lastChange + abs(interval)) {\n\n // Determine direction\n int direction = interval < 0 ? -1 : 1;\n\n // Update secondary index\n nextIndex = currIndex + direction;\n if (nextIndex < 0) {\n nextIndex = nOutPins - 1;\n } else if (nextIndex >= nOutPins) {\n nextIndex = 0;\n }\n \n // Turn off all LEDs\n for (int i = 0; i < nOutPins; i++) {\n if (i == currIndex || i == nextIndex){\n digitalWrite(outPins[i], HIGH);\n } else {\n digitalWrite(outPins[i], LOW);\n } \n }\n\n // Update current index\n currIndex += direction;\n if (currIndex < 0) {\n currIndex = nOutPins - 1;\n } else if (currIndex >= nOutPins) {\n currIndex = 0;\n }\n\n // Update timer\n lastChange = millis();\n }\n}\n\nThank you for your help, i value your input." } ]
a3977c9da04d41a0bbdaea3cf66fd0a4
arena-hard-v0.1
Audio Signal Direction Detection
[ { "content": "find the issue: #include \"mbed.h\"\n#include <exception>\n\nDigitalOut ledYellow(D2);\nDigitalOut ledAmber(D3);\nDigitalOut ledRed(D4);\n\nThread thread2;\nThread thread3;\n\nint counter = 0;\n\n// Subroutine for any LEDs\nvoid ledAny (DigitalOut *ledA){\n while(true){\n *ledA = 1;\n ThisThread::sleep_for(500ms);\n *ledA =0;\n ThisThread::sleep_for(1500ms);\n printf(\"My pointer is %p\\n\", *ledA);\n }\n}\n\n\n// main() runs in its own thread in the OS\nint main(){\n\n thread2.start(callback(ledAny, &ledYellow));\n ThisThread::sleep_for(1000ms);\n thread3.start(callback(ledAny, &ledAmber));\n\n while (true) {\n counter = counter + 1;\n\n ledRed.write(true);\n ThisThread::sleep_for(500ms);\n ledRed.write(false);\n ThisThread::sleep_for(500ms);\n\n if (counter>20){\n thread2.terminate();\n }\n\n\n }\n}\n\n" } ]
4a60873735a64c2c95c0ba24cb441aaa
arena-hard-v0.1
Automated Testing & Tools
[ { "content": "Is there an early stop out method (to control for multiple testing problem in hypothesis tests) for a dataset with initial probabilities of passing. For example, I have a set of financial market strategies with initial probability of skill using the probabilistic sharpe ratio. I want to test these strategies for a different dataset but I also want to control for multiple testing. Testing all available strategies will lead to multiple testing problems. So, I only want to test a subset of my strategies. Is there an early stop-out method for this application?" } ]
e7e76d4bcf0342308ca6153634000a4a
arena-hard-v0.1
Automated Testing & Tools
[ { "content": "Can you write a service catalogue for a Microsoft M365 consultancy focusing on Data, Data Management, Automation and A.I. The focus should be on audits, roadmaps, advice and cutting edge technologies within the M365 ecosystem but not be its only focus" } ]
fd64e8bac19e4e56b194599b3ba17ec1
arena-hard-v0.1
Baking and Peanut Butter Recipes
[ { "content": "Give me a recipe for making 5L of strawberry and blackberry melomel. Use metric measurements." } ]
ec7f8d669ea8455a8e67fe860520352f
arena-hard-v0.1
Baking and Peanut Butter Recipes
[ { "content": "Consider the flavors of the ingredients. The ingredients are: tuna, salt, chocolate\nGenerate a contingency table for ingredient combinations. Each row represents an ingredient. Each column represents an ingredient. each cell has the flavor profile of the ingredient combination. " } ]
db60d25a509f454b878cc2c5371d5f6f
arena-hard-v0.1
Basic Assembly Operations
[ { "content": "i need to allocate some space on stack for my local variables (in x86-64 nasm assembly)" } ]
f0c7479e7bde4b9aa80dd79dad179755
arena-hard-v0.1
Basic Assembly Operations
[ { "content": "Write a function in PPC64 to load the GOT and call a function in the GOT" } ]
d6410be3847048f188e27568e4e9f0d1
arena-hard-v0.1
Batch Size in Deep Learning
[ { "content": "When training my neural network, I can get a loss below 4.5 at 10,000 iterations. The latest attempt includes trying batch sizes of 512, 1024, and 2048 while keeping the block size at a 4. All of this is done in the context of nanoGPT. It's worth noting that when I ran a batch size of 12 and a block size of 1024, I managed to get the loss down to 4.32 after 10,000 iterations. In your opinion and experience, what steps can I take in order to reduce the loss? Please keep in mind that my video card has 12GB of RAM and the vocabulary is made up of 20,000 words. Each sentence is made up of exactly four tokens. Do you have any suggestions how I could improve the neural network, please?" } ]
3971e3d0eb194b8c9344030bebd0c6aa
arena-hard-v0.1
Batch Size in Deep Learning
[ { "content": "Here are the top issues reported for a Scheduling system. Can you categorize them and report on counts for the most common issues:\n\nTitle\tShortResolution\nPlanner-Loadboard Sync Issue.\tReplicated job fixed issue.\nLoadboard-Planner Task Sync Issue.\tForecast indicator removed by renaming.\nWest Allis MLS HDSS Header Update.\tRenamed resource replicated next day.\n\"Daily Task Board Setup\"\tDuplex task run creation fixed.\n\"Cancelled jobs tasks remain in LB2\"\tCharacters issue fixed. OM updated.\nMissing Task for Press in 3 Hours\tData resent and planner updated.\nLoadboard job display error.\tReset Citrix connection.\nPresort error for Cafe Sheet batch.\tNew job number created.\nFilter not catching FSC MC.\tAdded 'contains' operator for search.\nAccess issues with LB2 & Finishing Toolset shortcuts at PEI-111.\tLB2 deployment successful.\nAccess issues with LB2 workstation.\tResolved LB2 deployment issue.\nLoadboard crashes and login issues.\tCitrix server resolved, login fix in progress.\nLB2 Loadboard Tool Error.\tLB2 error resolved, no action taken.\nDeployment delays causing downtime\tProblem not solved. Presses deploy requested.\nLoadboard server error.\tBroker switch resolved LB2 issue.\nLoadboard Malfunction - Urgent!\tInk jet data corrected; schedule loaded." } ]
4c2a6d7d4a4243e0ab0a633c348444e8
arena-hard-v0.1
Binance USDT Historical Data
[ { "content": "write a python code to get daily stocks data from yfinance and plot" } ]
68ab3fd2a31c473b97c416ddb1ccffb4
arena-hard-v0.1
Binance USDT Historical Data
[ { "content": "Using pandas-ta, I have forex data and an 'EMA50' column. I want to detect where the close price crosses over the 'EMA50' value." } ]
f4c8b624448a40dc82757a8801093c1b
arena-hard-v0.1
Bob, Alice, Relationships & Interactions
[ { "content": "Write a song about catfish in the style of Bob Dylan." } ]
bc75023ee4bc4b9b8e01865429907014
arena-hard-v0.1
Bob, Alice, Relationships & Interactions
[ { "content": "Write a php project to open a MySQL database called Bob, and receive fields field1, field2 via http post and store in database" } ]
2c53e72874844987b48588106c705039
arena-hard-v0.1
Browser Extensions Development
[ { "content": "Write a chrome plugin that saves the contents of the current page" } ]
bd49bd3cc95843f9addca45abe0b27a7
arena-hard-v0.1
Browser Extensions Development
[ { "content": "I am migrating from MacOS Mojave running Safari 14 to a new Mac running Safari 17 under MacOS Sonoma. I want Safari on my new Mac to automatically open with all the tabs open on my old Mac. Note that Safari 14 does not support iCloud tabs, and that I do *not* want to have to manually open each tab as I have hundreds of them!" } ]
984787b1d5c64bb7b6dcd485ff8a70e6
arena-hard-v0.1
Bug-Related German Translation
[ { "content": "A bug got into the computer case causing the software to bug out which was really starting to bug me but at least we discovered that no one had bugged the room. \nWhat does each instance of the word bug mean in the above sentence. " } ]
c63a6be043534eda89675bdc0310bc43
arena-hard-v0.1
Bug-Related German Translation
[ { "content": "Find a fix for this bug : \n```This model maximum context length is 2048 tokens. However, your messages resulted in over 2364 tokens.```" } ]
a89e93c61470449389c17d1f0fcb8469
arena-hard-v0.1
Bulk Ticket Pricing Mathematics
[ { "content": "I want you to act as an experienced software developer. I will provide information about a web app requirements. It will be your job to come up with a system connection architecture, a specific list of helper code libraries, a clear list of 5 sprint tickets from the project setup, and a detailed list of tasks for each of such tickets to develop an scalable and secure app with NodeJS, SQL and React. My request is this: 'I desire a system that allow users to register and save information related to mechanical devices inventory (name, reference, quantity, etc) according to their roles. There will be user, staff and admin roles. Users should be able to read all and to update individual records. Staff could also add new records and submit bulk updates. Admin also should create and eliminate entities like ddbb fields and users'. Implement the best practices on your proposal" } ]
74c4255dd61d41d68ea69e4469a63fce
arena-hard-v0.1
Bulk Ticket Pricing Mathematics
[ { "content": "I need to connect a list of FBIDs found in support tickets (the dim_tier1_job_final table) to a list of page IDs found in a target list. Unfortunately, our support tickets typically don't include a page ID. How can I connect these two lists of data in Daiquery?" } ]
ab10af348f7f49e6813728282ade2ca9
arena-hard-v0.1
Business Operations Analysis
[ { "content": "A company is having transhipment problems where they need to ship all the goods from the plants to all of the destinations at the minimum possible transportation cost.\n\n \n\nThe plantations, which are the origin of the network, have the following details:\n\nArea\tProduction \nDenver\t600\nAtlanta\t400\nHouston\t500\n \n\nThe Retail Outlets, which are the destination of the network, have the following details: \n\nRetail Outlets\tDemand\nDetriot\t 300\nMiami\t 250\nDallas\t 450\nNew Orleans\t 500\n \n\nTransportation costs from Plants to Warehouses (intermediate destination)\n\nPlant/Warehouse\tKansas City\tLousville\nDenver\t3\t2\nAtlanta\t2\t1\nHouston\t4\t3\n \n\nTransportation costs from Warehouses to Retail Outlets\n\nDetriot\tMiami\tDallas\tNew Orleans\nKansas City\t2\t6\t3\t5\nLousville\t4\t4\t6\t5\n \n\n\nWhat is the minimum cost that can be achieved for this transhipment problem? \n[ Select ]\n\n\n\nWhat will be the effect on the total cost of the optimal solution if Denver can also directly ship to all the Retail Outlets at $6 cost? \n[ Select ]\n\nWhat would happen if there is a maximum capacity of 350 units on all flows? \n[ Select ]\n\nWhat is the total netflow of the network? \n[ Select ]\n\nIn a situation where there is a maximum capacity of 350 units on all flows and all plants can directly ship to all retail outlets at $5, which of the following statements is true? \n[ Select ]\n\n\nStatement 1: The total cost of the optimal solution would decrease.\nStatement 2: There would be no flows in Lousville.\nStatement 3: To achieve the optimal solution, all plants will have to ship their products directly to the retail outlets." } ]
33166da9898f40b6aff3fa8d988dae7a
arena-hard-v0.1
Business Operations Analysis
[ { "content": "Joe the trainer has two solo workout plans that he offers his clients: Plan A and Plan B. Each client does either one or the other (not both). On Monday there were 9 clients who did Plan A and 7 who did Plan B. On Tuesday there were 3 clients who did Plan A and 5 who did Plan B. Joe trained his Monday clients for a total of 12 hours and his Tuesday clients for a total of 6 hours. How long does each of the workout plans last? length of each plan A workout? length of each plan B workout" } ]
2b9b644162d741b3a0f27c5d91752dd4
arena-hard-v0.1
C++ Code Conversion Challenge
[ { "content": "Write functionality to print the rxdataF variable in c:\nru->common.rxdataF = (int32_t**)malloc16(ru->nb_rx*sizeof(int32_t*) );\nru->common.rxdataF[i] = (int32_t*)malloc16_clear(sizeof(int32_t)*(NUMBER_RX_BUFFERS*fp->symbols_per_slot*fp->ofdm_symbol_size) ); " } ]
6462f12cc6c64d66aa2dcae61d6ec7c2
arena-hard-v0.1
C++ Code Conversion Challenge
[ { "content": "Please rewrite the following pseudo C code as an equivalent code that is easier to read (assume that every variable works, even if it's not defined):\n\n```\nhandleCmdLineArgs(char *param_1)\n{\n uint uVar2;\n uint uVar3;\n int iVar4;\n char *pcVar5;\n char cVar1;\n \n uVar3 = 0xffffffff;\n uVar2 = 0;\n iVar4 = 0;\n pcVar5 = param_1;\n do {\n if (uVar3 == 0) break;\n uVar3 = uVar3 - 1;\n cVar1 = *pcVar5;\n pcVar5 = pcVar5 + 1;\n } while (cVar1 != '\\0');\n if (0 < (int)(~uVar3 - 2)) {\n do {\n uVar2 = RK_CheckSJIS(uVar2 & 0xffffff00 | (uint)(byte)param_1[iVar4]);\n if (uVar2 == 1) {\n iVar4 = iVar4 + 1;\n }\n else if (param_1[iVar4] == '/') {\n uVar2 = uVar2 & 0xffffff00 | (uint)(byte)param_1[iVar4 + 1] | 0x20;\n if ((char)uVar2 == 'w') {\n IsWindowedMode = 1;\n }\n else if ((char)uVar2 == 'f') {\n IsWindowedMode = 0;\n }\n }\n iVar4 = iVar4 + 1;\n } while (iVar4 < (int)(~uVar3 - 2));\n }\n}\n```" } ]
7ea271ef49474854a73d16a627d3f0c9
arena-hard-v0.1
CAD Tax Invoice Analysis
[ { "content": "show me the steps to build an invoice app using phython" } ]
5b2976a6c57f4bbca86176abb5993575
arena-hard-v0.1
CAD Tax Invoice Analysis
[ { "content": "I am expensing airfare costs with my employer, and the reporting software asks me to specify the GST/HST portion of the expense. Reading the invoice for my flight from Toronto, through Montreal, to Las Vegas, I see a base fare (CAD) of 164.99, Total V.A.T/G.S.T/H.S.T. of $15, and Other Taxes of 132.12. The total invoice then sums to 312.11 CAD. I have never seen a bill with 2 tax categories like this and am not sure how the $15 and 132.12 were calculated, and which I should report as GST/HST in my company's expense report. Can you help me better understand how to correctly report the HST on my airfare?" } ]
b253dc64bdd74f5c84882ae51e009ca6
arena-hard-v0.1
CIO Biotech IT Strategy
[ { "content": "Act as Chief Information Officer and write 3 S.M.A.R.T. goals on creating an IT Incident response plan with detailed table top exercises over the next 6 months. " } ]
26a29141be254ce0a7710e45face31f4
arena-hard-v0.1
CIO Biotech IT Strategy
[ { "content": "You are Chief Information Officer and act like one. Write a weekly activity report in the form of titles and bullet statements. Summarize and include the following information: Key Updates from IT (strategic iniatives)\n\no\tSecurity/Communications with Madison Industries\no\tThe internal/external Pentesting is continuing this week and is planned to end this Friday. We should get an outbrief and report early next week. Greenpages has been extremely thorough and have a more extensive approach than our previous Evolve Pentests. \no\tTracking Pentest remediation priorities 1 of 10 remain. Upgrading exchange servers for Dev.\no\tMonth Security call with Ken Holmes on Tuesday, June 20. Conducted a review of cyber risk compared to all of Madison companies. \n\tStreck is ranked 7 of 39 companies for overall readiness score (1 Red, 5 Yellow, 3 Green)\n\tDiscussed our rating on KnowBe4 Security training being Yellow with 63 account not completing training. The list of 63 included group accounts and accounts that needed deleted. The real number is 4 people that need to complete training. We are following up with those 4 individuals today.\no\tKen and I also discussed Strecks plans for AI and Incident response. Ken has added me to the Madison committees for both topics. \no\tKen stated that Madison will have the IT Leaders meeting at the GreenPages conference in OCTober. He has asked me to attend. I had budgeted for 2-3 IT attendees.\nOn-Prem Exchange Retirement\n\tMadison has determined ASAP \n\tInfrastructure has stood up and is testing replacement solution\n\tDave S, Doug V, Will J, Justin B, Molly M and Scott M met on 6/9/2023 \n\t10 of 18 applications remain\n\no\tArtificial Intelligence Planning\no\tPriya and I had a followup meeting with Troy Bothwell to view 4 AI FY24 proposal projects that we can look at using off the shelf or home grown AI solutions. Troy/I are building a justification and business case for a Weather AI app and a warehouse Slotting app to be presented to John for priority projects for CY24. I am coordinating with other Omaha leaders in IT and Manufacturing to get use case best practices and suggestions for Off the shelf solutions. If home grown solutions will need to be considered, It will have to look at a consulting solution as our team does not have that skillset currently. \no\tI met with John S and Chris from R&D on 2 separate projects.\n\tCapstone project of automating multiple instrument pdf’s. the instruments generate 100’s of pdf files that need to be manually replicated and then printed. An app can be created to b" } ]
3d3e0087ee5c4f6eb620799e2267cb7a
arena-hard-v0.1
CSS Flexbox & Bootstrap Layouts
[ { "content": "how can i use css flexbox to put an image on the same line as a paragraph and have the paragraph automatically format itself around the top and bottom of the picture" } ]
0d1aeaf2b7624246be2e899054622c87
arena-hard-v0.1
CSS Flexbox & Bootstrap Layouts
[ { "content": "I'm having trouble with css. I have two buttons in a parent container and I want one to be left aligned and the other right aligned but using flex for responsive reasons." } ]
ee9ae71956724d4591d4d9bc457d598d
arena-hard-v0.1
CSV Data Manipulation in Pandas
[ { "content": "%%writefile app.py\nimport streamlit as st\nimport pandas as pd\nimport io\nimport joblib\nimport base64\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nimport datetime\nfrom sklearn import tree\nfrom sklearn.tree import _tree\nimport numpy as np\n\n# Function to upload and generate predictions\ndef upload_and_generate_predictions():\n # File upload and prediction code\n def get_base64(bin_file):\n with open(bin_file, \"rb\") as f:\n data = f.read()\n return base64.b64encode(data).decode()\n\n def set_background(png_file):\n bin_str = get_base64(png_file)\n page_bg_img = (\n \"\"\"\n <style>\n .stApp {\n background-image: url(\"data:image/png;base64,%s\");\n background-size: cover;\n }\n </style>\n \"\"\"\n % bin_str\n )\n st.markdown(page_bg_img, unsafe_allow_html=True)\n\n set_background(\"Screenshot (29).png\")\n red_title = '<h1 style=\"color: white;\">Equipment Failure Prediction</h1>'\n\n # Display the red title using st.markdown\n st.markdown(red_title, unsafe_allow_html=True)\n # Display the custom CSS style\n uploaded_file = st.file_uploader(\n \"Upload an Excel or CSV file\", type=[\"xlsx\", \"csv\"]\n )\n if uploaded_file is not None:\n # Read the file into a DataFrame\n if (\n uploaded_file.type\n == \"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet\"\n ): # Excel file\n df = pd.read_excel(uploaded_file, engine=\"openpyxl\")\n else: # CSV file\n df = pd.read_csv(uploaded_file)\n # st.session_state.predictions_df = df\n # st.session_state.uploaded_file=uploaded_file\n\n # Display the first screen\n\n if st.button(\"Generate predictions\"):\n model = joblib.load(\"des_tree_clss.joblib\")\n prediction = \"\"\n if \"machine_status\" in df.columns.to_list():\n prediction = model.predict(df.drop(columns=[\"machine_status\"]))\n else:\n prediction = model.predict(df)\n df[\"Predicted_Status\"] = prediction\n st.success(\"Predictions made successfully!\")\n st.session_state.predictions_df = df\n st.session_state.uploaded_file = uploaded_file\n # Display the modified DataFrame with predictions\n # Save the DataFrame with predictions to st.session_state\n # Move to the second screen (graph display)\ndef display_graph(predictions_df, uploaded_file):\n def get_base64(bin_file):\n with open(bin_file, \"rb\") as f:\n data = f.read()\n return base64.b64encode(data).decode()\n\n def set_background(png_file):\n bin_str = get_base64(png_file)\n page_bg_img = (\n \"\"\"\n <style>\n .stApp {\n background-image: url(\"data:image/png;base64,%s\");\n background-size: cover;\n }\n </style>\n \"\"\"\n % bin_str\n )\n st.markdown(page_bg_img, unsafe_allow_html=True)\n\n set_background(\"Screenshot (32).png\")\n st.markdown('<div style=\"margin-top: 50px;\"></div>', unsafe_allow_html=True)\n st.subheader(\"Early warning Signal:\")\n # Create a DataFrame with the first 10 records with prediction status 1\n df_status_1 = predictions_df[predictions_df[\"Predicted_Status\"] == 1].head(10)\n # Create a DataFrame with all records with prediction status 0\n df_status_0 = predictions_df[predictions_df[\"Predicted_Status\"] == 0].head(10)\n # Combine the DataFrames\n df_combined = pd.concat([df_status_0, df_status_1])\n start_timestamp = datetime.datetime(2023, 1, 1)\n df_combined[\"Synthetic_Timestamp\"] = pd.date_range(\n start=start_timestamp, periods=len(df_combined), freq=\"T\"\n )\n # df_combined['Synthetic_Timestamp'] = pd.date_range(start='2023-01-01', periods=len(df_combined), freq='T')\n plt.figure(figsize=(10, 3))\n sns.scatterplot(\n x=\"Synthetic_Timestamp\",\n y=\"Predicted_Status\",\n hue=\"Predicted_Status\",\n marker=\"o\",\n s=200,\n data=df_combined,\n palette={1: \"red\", 0: \"green\"},\n )\n plt.xticks(rotation=45, ha=\"right\")\n # plt.title(\"Machine Status Prediction - Combined\")\n plt.xlabel(\"Timestamp\")\n plt.ylabel(\"Value\")\n st.pyplot()\n # Create a download link\n st.subheader(\"Download the File with Predictions:\")\n st.write(\"Download the File with Predictions:\")\n # st.markdown(title1, unsafe_allow_html=True)\n modified_file_name = (\n f\"file_with_predictions_{uploaded_file.name}\"\n if uploaded_file.name\n else \"file_with_predictions.xlsx\"\n )\n\n # Convert DataFrame to binary stream\n modified_file = io.BytesIO()\n if (\n uploaded_file.type\n == \"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet\"\n ): # Excel file\n predictions_df.to_excel(modified_file, index=False, engine=\"xlsxwriter\")\n else: # CSV file\n predictions_df.to_csv(modified_file, index=False)\n modified_file.seek(0)\n # Create a download link\n st.download_button(\n label=\"Download File with Predictions\",\n data=modified_file,\n file_name=modified_file_name,\n key=\"download_file_with_predictions\",\n )\n # Rules functions\n def get_rules(tree, feature_names, class_names):\n tree_ = tree.tree_\n feature_name = [\n feature_names[i] if i != _tree.TREE_UNDEFINED else \"undefined!\"\n for i in tree_.feature\n ]\n\n paths = []\n path = []\n\n def recurse(node, path, paths):\n\n if tree_.feature[node] != _tree.TREE_UNDEFINED:\n name = feature_name[node]\n threshold = tree_.threshold[node]\n p1, p2 = list(path), list(path)\n p1 += [f\"({name} <= {np.round(threshold, 3)})\"]\n recurse(tree_.children_left[node], p1, paths)\n p2 += [f\"({name} > {np.round(threshold, 3)})\"]\n recurse(tree_.children_right[node], p2, paths)\n else:\n path += [(tree_.value[node], tree_.n_node_samples[node])]\n paths += [path]\n\n recurse(0, path, paths)\n\n # sort by samples count\n samples_count = [p[-1][1] for p in paths]\n ii = list(np.argsort(samples_count))\n paths = [paths[i] for i in reversed(ii)]\n\n rules = []\n for path in paths:\n rule = \"if \"\n\n for p in path[:-1]:\n if rule != \"if \":\n rule += \" and \"\n rule += str(p)\n rule += \" then \"\n if class_names is None:\n rule += \"response: \" + str(np.round(path[-1][0][0][0], 3))\n else:\n classes = path[-1][0][0]\n l = np.argmax(classes)\n rule += f\"class: {class_names[l]} (proba: {np.round(100.0*classes[l]/np.sum(classes),2)}%)\"\n rule += f\" | based on {path[-1][1]:,} samples\"\n rules += [rule]\n\n return rules\n st.subheader(\"Model Explainability:\")\n model = joblib.load(\"des_tree_clss.joblib\")\n rules = get_rules(model, predictions_df.columns, range(2))\n table_list = []\n for r in rules:\n colon_split = r.split(\":\")\n col_1 = colon_split[0]\n pipe_split = str(colon_split[1] + colon_split[2]).split(\"|\")\n # print(colon_split)\n # print(pipe_split)\n col_2 = pipe_split[0]\n col_3 = pipe_split[1]\n table_list.append([col_1, col_2, col_3])\n table_df = pd.DataFrame(\n table_list, columns=[\"rule_details\", \"class_probabilities\", \"samples_count\"]\n )\n rules_data_file = io.BytesIO()\n table_df.to_csv(rules_data_file, index=False)\n rules_data_file.seek(0)\n\n # Create a download link\n st.download_button(\n label=\"Model Explainability\",\n data=rules_data_file,\n file_name=\"rules_data.csv\",\n key=\"download_rules_data\",\n )\n# Run the app\nif __name__ == \"__main__\":\n st.set_option(\"deprecation.showPyplotGlobalUse\", False)\n st.set_page_config(page_title=\"Equipment Failure Prediction\", page_icon=\"📈\")\n pages = [\"Upload and Predict\", \"Graph and Download\"]\n page = st.sidebar.selectbox(\"Select a page\", pages)\n if page == \"Upload and Predict\":\n upload_and_generate_predictions()\n elif page == \"Graph and Download\":\n if hasattr(st.session_state, \"predictions_df\"):\n display_graph(\n st.session_state.predictions_df, st.session_state.uploaded_file\n )\n else:\n st.warning(\"Please upload a file on the 'Upload and Predict' page first.\")\nthis is mu code inthis i have a scatterplot graph i want to modify the code in a way that draw ploltly graph usw click events of ploltly when i click the instance of the circle it should give descion rule for the instance using lime.after graph if i click one circle or instance lime table and rule list should print there it self you can add download predictions and model explananbility in new side bar" } ]
c30665aaed7e481cb5f244c04058c34e
arena-hard-v0.1
CSV Data Manipulation in Pandas
[ { "content": "Devise a way to parse the dataframe in python using a bytestream without actually downloading the whole code " } ]
cd99a56b4d01417291e65ff5bbd531eb
arena-hard-v0.1
Calculating Pi in Python
[ { "content": "How to write a program in Python to calculate flight path " } ]
15f390071b5846bf9efa59780468c253
arena-hard-v0.1
Calculating Pi in Python
[ { "content": "Provide python code to calculate pie infinitely " } ]
4daa77667fb943d78113ebcd73762c66
arena-hard-v0.1
Calculating Pi with Code
[ { "content": "give me JavaScript code to calculate pi" } ]
ba51d695050d4c2fb9de4961b70eea97
arena-hard-v0.1
Calculating Pi with Code
[ { "content": "Write a C# program that calculates the pi up to 5 decimals and then XOR's the result twice." } ]
639d4faf0b7348a5bf3ee4be37199218
arena-hard-v0.1
Calculation Styles Exploration
[ { "content": "how can I index large codebase so I can traverse on output variable to get all the intermediate variables used to calculate that specific output variable" } ]
be6f4edf7f7041e4b5d5b65934856ae6
arena-hard-v0.1
Calculation Styles Exploration
[ { "content": "What is a good way to calculate the nucleation rate for a cosmological phase transition?" } ]
c542b6d5782b45efb294e945117387fc
arena-hard-v0.1
Calculator Usage Steps
[ { "content": "write me a python script that will make a DVD screen saver logo bounce around and every time it touches the corner of the screen it will tally a point and display the points on screen" } ]
1b73387238e94e28a29c846bd9593a9d
arena-hard-v0.1
Calculator Usage Steps
[ { "content": "How can i run a gui application on linux when i do not have a screen. I need to test application but it would not start" } ]
ccda5d99a99f4720bfb28e9882b67775
arena-hard-v0.1
Character Indexing and Counting
[ { "content": "what database schema can be used for store social graph links" } ]
f6bf04c1e96c4726a4d32e839e2a0719
arena-hard-v0.1
Character Indexing and Counting
[ { "content": "I have a scale of 1 to 7. 1 being the best and 7 the worst. How do I create an index between 0 an 1 where 1 is the best. Can you write a python function that takes in the number and returns the index?" } ]
946c6e48081e4be695cd876172ce4219
arena-hard-v0.1
Chatbot Development & Integration
[ { "content": "write python code for fastchat to listen on a port and answer a typed question as well as follow up questions" } ]
5aa9896e5bbe4ef0a158fbc803d4f37e
arena-hard-v0.1
Chatbot Development & Integration
[ { "content": "please write me a python matrix bot that can respond to mentions" } ]
0b70bc948cda4825b0a18438020fe1db
arena-hard-v0.1
Chatbot Development and Customization
[ { "content": "How can I create chat app using transformers.js with facebook/blenderbot-400m-distill javascript in pure vanilla javascript" } ]
548610d9ad9f477faf5a6d6028525c8a
arena-hard-v0.1
Chatbot Development and Customization
[ { "content": "how can I run an ai chatbot model using python on very low resource systems, show me some code" } ]
1ea6c1c2bc984f11b63201fbc63c85bb
arena-hard-v0.1
Chess Strategy and Gameplay
[ { "content": "I'm making a chess mistake explanation teaching software tool, is it corrrect and useful to say all chess mistakes are either allowing something or missing something? How can this be used as a algorithm base structure?" } ]
5601c90549f04bb09adbce4a2df4a062
arena-hard-v0.1
Chess Strategy and Gameplay
[ { "content": "I am a Ptyhon programmer. I would like you to give me the code for a chess program. I only need to be able to play against myself." } ]
4ef42cc8be63492eae57dfae54949cbe
arena-hard-v0.1
Circular Motion and Revolutions
[ { "content": "I want to create a slider for a website. unlike the traditional linear slider, the user increases or decreases the radius of a circle. there will be concentric circle markers to let the user know how big the circle they have selected is" } ]
40b8576cb60b42619b0c5530c20ea457
arena-hard-v0.1
Circular Motion and Revolutions
[ { "content": "Write a python class \"Circle\" that inherits from class \"Shape\"" } ]
52b9f9d3ee4b4731bb0e82233fb7a68b
arena-hard-v0.1
Climate Change Skepticism
[ { "content": "how would you solve the climate change problem. Provide a detailed strategy for the next 20 years" } ]
8630c94637ac4d9fa5b2c1e734473c7b
arena-hard-v0.1
Climate Change Skepticism
[ { "content": "Help me draft a research introduction of this topic \"Data-Driven Insights into the Impact of Climate and Soil Conditions on Durian Floral Induction\"" } ]
0c74645c3386490e9d26bb12ab068826
arena-hard-v0.1
Code Deobfuscation Techniques
[ { "content": "Can you generate a flowchart for the following code : switch (currentState) {\n case IDLE:\n\n break;\n case START:\n\n break;\n\t \n case CHANGE_SPEED:\n\n break;\t \n\t \n case STOP:\n\n break;\n}" } ]
3801e82e67a34ee3aaab0227342bcc2b
arena-hard-v0.1
Code Deobfuscation Techniques
[ { "content": "obfuscate this funtion for me:\n\nfunction minion\n{ \n $ooo = '16:3'\n $hr = $null\n while ($hr -lt $ooo +\"\"+ $ran) {\n $wsh = New-Object -ComObject WScript.shell\n $wsh.sendkeys('+{F15}')\n $hr = (Get-Date).ToString('HH:mm') \n $ran = (Get-Random -Minimum 1 -Maximum 9)\n Clear-Host\n write-host Checking Ratio: $ran\":\"$hr\":\"$ran\n Start-Sleep -Seconds 58\n }\n}" } ]
fd86dff7ac084b99889d294e135f82a4
arena-hard-v0.1
Computers and Comparative Truths
[ { "content": "Generate codes of a script that sync all types of content of two separate shared folders on two network computers on a domain " } ]
dd61037efa054b6fb3e2beed72a472aa
arena-hard-v0.1
Computers and Comparative Truths
[ { "content": "Your goal is to come up with a plan to synthesize HCl! What are the steps?" } ]
2c41e83c1cc743e3ab6966940c1aafe7
arena-hard-v0.1
Computing Standard Deviation
[ { "content": "I've trained a predictor using GluonTS on multiple related datasets. I've got a list of forecasts and timeseries that i created like this:\n forecast_it, ts_it = make_evaluation_predictions(\n dataset=test_ds, # test dataset\n predictor=predictor, # predictor\n num_samples=100, # number of sample paths we want for evaluation\n )\n\n forecasts = list(forecast_it)\n timeseries = list(ts_it)\n\nHow do i calculate the mean squared error and standard deviation and potential other usefull metrics for evaluation." } ]
f881bfef29af4f138672d9ef8656c334
arena-hard-v0.1
Computing Standard Deviation
[ { "content": "Suppose we have a job monitoring software and we want to implement a module that sends email alerts if a job takes too long to executie. The module should determine what is \"too long\" autonomously, based on the execution history.\n\nWe could calculate the arithmetic mean and standard deviation, and alert if the execution time is e.g. in the high 1%, but:\n1) the execution time may depend on e.g. day of week (e.g. working day/weekend)\n2) the execution time may have a global (upward) trend\n3) the execution time may have sudden jumps due to underlying changes (\"from Jan 1, we'll process both cash and card transactions, and the volume will suddenly jump 5x\")\n\nCan you outline some ideas on how to implement a system like this and address the bulleted points above?" } ]

Arena-Hard-Auto

Arena-Hard-Auto-v0.1 (See Paper) is an automatic evaluation tool for instruction-tuned LLMs. It contains 500 challenging user queries sourced from Chatbot Arena. We prompt GPT-4-Turbo as judge to compare the models' responses against a baseline model (default: GPT-4-0314). Notably, Arena-Hard-Auto has the highest correlation and separability to Chatbot Arena among popular open-ended LLM benchmarks (See Paper). If you are curious to see how well your model might perform on Chatbot Arena, we recommend trying Arena-Hard-Auto.

Please checkout our GitHub repo on how to evaluate models using Arena-Hard-Auto and more information about the benchmark.

If you find this dataset useful, feel free to cite us!

@article{li2024crowdsourced,
  title={From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline},
  author={Li, Tianle and Chiang, Wei-Lin and Frick, Evan and Dunlap, Lisa and Wu, Tianhao and Zhu, Banghua and Gonzalez, Joseph E and Stoica, Ion},
  journal={arXiv preprint arXiv:2406.11939},
  year={2024}
}
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