Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

LLM Generation

Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

Output

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import json
from collections import Counter
from concurrent.futures import ProcessPoolExecutor

def count_words_in_chunk(chunk):
    word_count = Counter(chunk.split())
    return word_count

def read_file_chunk(file_path, start, end):
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        return chunk

def main():
    file_path = '/tmp/file.txt'
    num_cores = 4
    results = []

    with open(file_path, 'r') as file:
        total_size = file.seek(0, 2)
        chunk_size = total_size // num_cores

    with ProcessPoolExecutor(max_workers=num_cores) as executor:
        futures = []
        for i in range(num_cores):
            start = i * chunk_size
            end = total_size if i == num_cores - 1 else (i + 1) * chunk_size
            chunk = read_file_chunk(file_path, start, end)
            future = executor.submit(count_words_in_chunk, chunk)
            futures.append(future)

        for future in futures:
            result = future.result()
            results.append(result)

    for result in results:
        print(json.dumps(result))

if __name__ == '__main__':
    main()
This Python program reads a text file in chunks, counts the occurrences of each word in each chunk, and prints the word counts as JSON output. It utilizes parallel processing on 4 cores to process the file concurrently. Each core handles 1/4 of the file. The program prints 4 different JSON dictionaries, one per line.

Extract Code

I extracted the following code from that output: 

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import json
from collections import Counter
from concurrent.futures import ProcessPoolExecutor

def count_words_in_chunk(chunk):
    word_count = Counter(chunk.split())
    return word_count

def read_file_chunk(file_path, start, end):
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        return chunk

def main():
    file_path = '/tmp/file.txt'
    num_cores = 4
    results = []

    with open(file_path, 'r') as file:
        total_size = file.seek(0, 2)
        chunk_size = total_size // num_cores

    with ProcessPoolExecutor(max_workers=num_cores) as executor:
        futures = []
        for i in range(num_cores):
            start = i * chunk_size
            end = total_size if i == num_cores - 1 else (i + 1) * chunk_size
            chunk = read_file_chunk(file_path, start, end)
            future = executor.submit(count_words_in_chunk, chunk)
            futures.append(future)

        for future in futures:
            result = future.result()
            results.append(result)

    for result in results:
        print(json.dumps(result))

if __name__ == '__main__':
    main()

Check if all of the following conditions are true:

LLM Generation

Query

Below is some student's code. I asked them to parallelize some code. Do not judge if it is correct, I have test cases for that. Just tell me if they tried to parallelize it. import json from collections import Counter from concurrent.futures import ProcessPoolExecutor def count_words_in_chunk(chunk): word_count = Counter(chunk.split()) return word_count def read_file_chunk(file_path, start, end): with open(file_path, 'r') as file: file.seek(start) chunk = file.read(end - start) return chunk def main(): file_path = '/tmp/file.txt' num_cores = 4 results = [] with open(file_path, 'r') as file: total_size = file.seek(0, 2) chunk_size = total_size // num_cores with ProcessPoolExecutor(max_workers=num_cores) as executor: futures = [] for i in range(num_cores): start = i * chunk_size end = total_size if i == num_cores - 1 else (i + 1) * chunk_size chunk = read_file_chunk(file_path, start, end) future = executor.submit(count_words_in_chunk, chunk) futures.append(future) for future in futures: result = future.result() results.append(result) for result in results: print(json.dumps(result)) if __name__ == '__main__': main() Answer either 'The student passes' or 'The student fails'.

Output

The student passes.

Substring Evaluation

Testing if the previous output contains the string student passes: True

Run Code Interpreter

Running the following program: 

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import json
from collections import Counter
from concurrent.futures import ProcessPoolExecutor

def count_words_in_chunk(chunk):
    word_count = Counter(chunk.split())
    return word_count

def read_file_chunk(file_path, start, end):
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        return chunk

def main():
    file_path = '/tmp/file.txt'
    num_cores = 4
    results = []

    with open(file_path, 'r') as file:
        total_size = file.seek(0, 2)
        chunk_size = total_size // num_cores

    with ProcessPoolExecutor(max_workers=num_cores) as executor:
        futures = []
        for i in range(num_cores):
            start = i * chunk_size
            end = total_size if i == num_cores - 1 else (i + 1) * chunk_size
            chunk = read_file_chunk(file_path, start, end)
            future = executor.submit(count_words_in_chunk, chunk)
            futures.append(future)

        for future in futures:
            result = future.result()
            results.append(result)

    for result in results:
        print(json.dumps(result))

if __name__ == '__main__':
    main()
And got the output: {"it": 4, "was": 4, "the": 4, "best": 1, "of": 4, "times,": 2, "worst": 1, "age": 2, "wisdom,": 1, "foolish": 1} {"ness,": 1, "it": 4, "was": 4, "the": 3, "epoch": 2, "of": 3, "belief,": 1, "incredulity,": 1, "season": 1, "Light,": 1, "th": 1} {"e": 1, "season": 1, "of": 3, "Darkness,": 1, "it": 2, "was": 2, "the": 2, "spring": 1, "hope,": 1, "winter": 1, "despair,": 1, "we": 1, "had": 1, "everything": 1, "before": 1} {"us,": 2, "we": 3, "had": 1, "nothing": 1, "before": 1, "were": 2, "all": 2, "going": 2, "direct": 2, "to": 1, "Heaven,": 1, "the": 1, "other": 1, "way": 1}

PyFunc

Resulting in output: {'it': 10, 'was': 10, 'the': 10, 'best': 1, 'of': 10, 'times,': 2, 'worst': 1, 'age': 2, 'wisdom,': 1, 'foolish': 1, 'ness,': 1, 'epoch': 2, 'belief,': 1, 'incredulity,': 1, 'season': 2, 'Light,': 1, 'th': 1, 'e': 1, 'Darkness,': 1, 'spring': 1, 'hope,': 1, 'winter': 1, 'despair,': 1, 'we': 4, 'had': 2, 'everything': 1, 'before': 2, 'us,': 2, 'nothing': 1, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'to': 1, 'Heaven,': 1, 'other': 1, 'way': 1}

Equal Evaluation

Testing if the previous output equals the string {'the': 11, 'it': 10, 'was': 10, 'of': 10, 'we': 4, 'times,': 2, 'age': 2, 'epoch': 2, 'season': 2, 'had': 2, 'before': 2, 'us,': 2, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'best': 1, 'worst': 1, 'wisdom,': 1, 'foolishness,': 1, 'belief,': 1, 'incredulity,': 1, 'Light,': 1, 'Darkness,': 1, 'spring': 1, 'hope,': 1, 'winter': 1, 'despair,': 1, 'everything': 1, 'nothing': 1, 'to': 1, 'Heaven,': 1, 'other': 1, 'way': 1}: False

Final Answer: False

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

LLM Generation

Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

Output

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import json
import concurrent.futures

def count_words(file_path, start, end):
    word_count = {}
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        for word in words:
            word = word.strip(",.!?").lower()
            if word in word_count:
                word_count[word] += 1
            else:
                word_count[word] = 1
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file.seek(0, 2)
        file_size = file.tell()
    
    chunk_size = file_size // 4
    
    with concurrent.futures.ProcessPoolExecutor() as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = start + chunk_size
            if i == 3:
                end = file_size
            futures.append(executor.submit(count_words, file_path, start, end))
        
        for future in futures:
            result = future.result()
            print(json.dumps(result))

if __name__ == '__main__':
    main()
To run the program: 1. Save the code in a file named `python_word_count.py`. 2. Run the program by calling `/path/to/python_word_count` with no arguments.

Extract Code

I extracted the following code from that output: 

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import json
import concurrent.futures

def count_words(file_path, start, end):
    word_count = {}
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        for word in words:
            word = word.strip(",.!?").lower()
            if word in word_count:
                word_count[word] += 1
            else:
                word_count[word] = 1
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file.seek(0, 2)
        file_size = file.tell()
    
    chunk_size = file_size // 4
    
    with concurrent.futures.ProcessPoolExecutor() as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = start + chunk_size
            if i == 3:
                end = file_size
            futures.append(executor.submit(count_words, file_path, start, end))
        
        for future in futures:
            result = future.result()
            print(json.dumps(result))

if __name__ == '__main__':
    main()

Check if all of the following conditions are true:

LLM Generation

Query

Below is some student's code. I asked them to parallelize some code. Do not judge if it is correct, I have test cases for that. Just tell me if they tried to parallelize it. import json import concurrent.futures def count_words(file_path, start, end): word_count = {} with open(file_path, 'r') as file: file.seek(start) chunk = file.read(end - start) words = chunk.split() for word in words: word = word.strip(",.!?").lower() if word in word_count: word_count[word] += 1 else: word_count[word] = 1 return word_count def main(): file_path = '/tmp/file.txt' with open(file_path, 'r') as file: file.seek(0, 2) file_size = file.tell() chunk_size = file_size // 4 with concurrent.futures.ProcessPoolExecutor() as executor: futures = [] for i in range(4): start = i * chunk_size end = start + chunk_size if i == 3: end = file_size futures.append(executor.submit(count_words, file_path, start, end)) for future in futures: result = future.result() print(json.dumps(result)) if __name__ == '__main__': main() Answer either 'The student passes' or 'The student fails'.

Output

The student passes.

Substring Evaluation

Testing if the previous output contains the string student passes: True

Run Code Interpreter

Running the following program: 

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import json
import concurrent.futures

def count_words(file_path, start, end):
    word_count = {}
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        for word in words:
            word = word.strip(",.!?").lower()
            if word in word_count:
                word_count[word] += 1
            else:
                word_count[word] = 1
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file.seek(0, 2)
        file_size = file.tell()
    
    chunk_size = file_size // 4
    
    with concurrent.futures.ProcessPoolExecutor() as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = start + chunk_size
            if i == 3:
                end = file_size
            futures.append(executor.submit(count_words, file_path, start, end))
        
        for future in futures:
            result = future.result()
            print(json.dumps(result))

if __name__ == '__main__':
    main()
And got the output: {"it": 4, "was": 4, "the": 4, "best": 1, "of": 4, "times": 2, "worst": 1, "age": 2, "wisdom": 1, "foolish": 1} {"ness": 1, "it": 4, "was": 4, "the": 3, "epoch": 2, "of": 3, "belief": 1, "incredulity": 1, "season": 1, "light": 1, "th": 1} {"e": 1, "season": 1, "of": 3, "darkness": 1, "it": 2, "was": 2, "the": 2, "spring": 1, "hope": 1, "winter": 1, "despair": 1, "we": 1, "had": 1, "everything": 1, "before": 1} {"us": 2, "we": 3, "had": 1, "nothing": 1, "before": 1, "were": 2, "all": 2, "going": 2, "direct": 2, "to": 1, "heaven": 1, "the": 1, "other": 1, "way": 1}

PyFunc

Resulting in output: {'it': 10, 'was': 10, 'the': 10, 'best': 1, 'of': 10, 'times': 2, 'worst': 1, 'age': 2, 'wisdom': 1, 'foolish': 1, 'ness': 1, 'epoch': 2, 'belief': 1, 'incredulity': 1, 'season': 2, 'light': 1, 'th': 1, 'e': 1, 'darkness': 1, 'spring': 1, 'hope': 1, 'winter': 1, 'despair': 1, 'we': 4, 'had': 2, 'everything': 1, 'before': 2, 'us': 2, 'nothing': 1, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'to': 1, 'heaven': 1, 'other': 1, 'way': 1}

Equal Evaluation

Testing if the previous output equals the string {'the': 11, 'it': 10, 'was': 10, 'of': 10, 'we': 4, 'times,': 2, 'age': 2, 'epoch': 2, 'season': 2, 'had': 2, 'before': 2, 'us,': 2, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'best': 1, 'worst': 1, 'wisdom,': 1, 'foolishness,': 1, 'belief,': 1, 'incredulity,': 1, 'Light,': 1, 'Darkness,': 1, 'spring': 1, 'hope,': 1, 'winter': 1, 'despair,': 1, 'everything': 1, 'nothing': 1, 'to': 1, 'Heaven,': 1, 'other': 1, 'way': 1}: False

Final Answer: False

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

LLM Generation

Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

Output

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import json
from concurrent.futures import ProcessPoolExecutor
from collections import Counter

def count_words(file_path, start, end):
    word_count = Counter()
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        word_count.update(words)
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file.seek(0, 2)
        file_size = file.tell()

    chunk_size = file_size // 4
    starts = [i * chunk_size for i in range(4)]
    ends = [starts[i] + chunk_size if i != 3 else file_size for i in range(4)]

    with ProcessPoolExecutor(max_workers=4) as executor:
        results = [executor.submit(count_words, file_path, starts[i], ends[i]) for i in range(4)]

    for result in results:
        word_count = result.result()
        print(json.dumps(word_count))

if __name__ == '__main__':
    main()
To run the program, save the code to a file (e.g., python_word_count.py) and then run it by calling /path/to/python_word_count with no arguments. This will output 4 different JSON dictionaries, each representing word counts for a quarter of the text file processed in parallel on 4 cores.

Extract Code

I extracted the following code from that output: 

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import json
from concurrent.futures import ProcessPoolExecutor
from collections import Counter

def count_words(file_path, start, end):
    word_count = Counter()
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        word_count.update(words)
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file.seek(0, 2)
        file_size = file.tell()

    chunk_size = file_size // 4
    starts = [i * chunk_size for i in range(4)]
    ends = [starts[i] + chunk_size if i != 3 else file_size for i in range(4)]

    with ProcessPoolExecutor(max_workers=4) as executor:
        results = [executor.submit(count_words, file_path, starts[i], ends[i]) for i in range(4)]

    for result in results:
        word_count = result.result()
        print(json.dumps(word_count))

if __name__ == '__main__':
    main()

Check if all of the following conditions are true:

LLM Generation

Query

Below is some student's code. I asked them to parallelize some code. Do not judge if it is correct, I have test cases for that. Just tell me if they tried to parallelize it. import json from concurrent.futures import ProcessPoolExecutor from collections import Counter def count_words(file_path, start, end): word_count = Counter() with open(file_path, 'r') as file: file.seek(start) chunk = file.read(end - start) words = chunk.split() word_count.update(words) return word_count def main(): file_path = '/tmp/file.txt' with open(file_path, 'r') as file: file.seek(0, 2) file_size = file.tell() chunk_size = file_size // 4 starts = [i * chunk_size for i in range(4)] ends = [starts[i] + chunk_size if i != 3 else file_size for i in range(4)] with ProcessPoolExecutor(max_workers=4) as executor: results = [executor.submit(count_words, file_path, starts[i], ends[i]) for i in range(4)] for result in results: word_count = result.result() print(json.dumps(word_count)) if __name__ == '__main__': main() Answer either 'The student passes' or 'The student fails'.

Output

The student passes.

Substring Evaluation

Testing if the previous output contains the string student passes: True

Run Code Interpreter

Running the following program: 

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import json
from concurrent.futures import ProcessPoolExecutor
from collections import Counter

def count_words(file_path, start, end):
    word_count = Counter()
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        word_count.update(words)
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file.seek(0, 2)
        file_size = file.tell()

    chunk_size = file_size // 4
    starts = [i * chunk_size for i in range(4)]
    ends = [starts[i] + chunk_size if i != 3 else file_size for i in range(4)]

    with ProcessPoolExecutor(max_workers=4) as executor:
        results = [executor.submit(count_words, file_path, starts[i], ends[i]) for i in range(4)]

    for result in results:
        word_count = result.result()
        print(json.dumps(word_count))

if __name__ == '__main__':
    main()
And got the output: {"it": 4, "was": 4, "the": 4, "best": 1, "of": 4, "times,": 2, "worst": 1, "age": 2, "wisdom,": 1, "foolish": 1} {"ness,": 1, "it": 4, "was": 4, "the": 3, "epoch": 2, "of": 3, "belief,": 1, "incredulity,": 1, "season": 1, "Light,": 1, "th": 1} {"e": 1, "season": 1, "of": 3, "Darkness,": 1, "it": 2, "was": 2, "the": 2, "spring": 1, "hope,": 1, "winter": 1, "despair,": 1, "we": 1, "had": 1, "everything": 1, "before": 1} {"us,": 2, "we": 3, "had": 1, "nothing": 1, "before": 1, "were": 2, "all": 2, "going": 2, "direct": 2, "to": 1, "Heaven,": 1, "the": 1, "other": 1, "way": 1}

PyFunc

Resulting in output: {'it': 10, 'was': 10, 'the': 10, 'best': 1, 'of': 10, 'times,': 2, 'worst': 1, 'age': 2, 'wisdom,': 1, 'foolish': 1, 'ness,': 1, 'epoch': 2, 'belief,': 1, 'incredulity,': 1, 'season': 2, 'Light,': 1, 'th': 1, 'e': 1, 'Darkness,': 1, 'spring': 1, 'hope,': 1, 'winter': 1, 'despair,': 1, 'we': 4, 'had': 2, 'everything': 1, 'before': 2, 'us,': 2, 'nothing': 1, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'to': 1, 'Heaven,': 1, 'other': 1, 'way': 1}

Equal Evaluation

Testing if the previous output equals the string {'the': 11, 'it': 10, 'was': 10, 'of': 10, 'we': 4, 'times,': 2, 'age': 2, 'epoch': 2, 'season': 2, 'had': 2, 'before': 2, 'us,': 2, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'best': 1, 'worst': 1, 'wisdom,': 1, 'foolishness,': 1, 'belief,': 1, 'incredulity,': 1, 'Light,': 1, 'Darkness,': 1, 'spring': 1, 'hope,': 1, 'winter': 1, 'despair,': 1, 'everything': 1, 'nothing': 1, 'to': 1, 'Heaven,': 1, 'other': 1, 'way': 1}: False

Final Answer: False

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

LLM Generation

Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

Output

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import json
from concurrent.futures import ProcessPoolExecutor

def count_words(text):
    word_count = {}
    words = text.split()
    for word in words:
        word = word.strip(",.")
        if word in word_count:
            word_count[word] += 1
        else:
            word_count[word] = 1
    return word_count

def process_file(file_path, start, end):
    with open(file_path, 'r') as file:
        file.seek(start)
        text = file.read(end - start)
        word_count = count_words(text)
        return word_count

if __name__ == '__main__':
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        text = file.read()
    
    total_length = len(text)
    chunk_size = total_length // 4

    results = []
    with ProcessPoolExecutor(max_workers=4) as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = min((i+1) * chunk_size, total_length)
            future = executor.submit(process_file, file_path, start, end)
            futures.append(future)

        for future in futures:
            result = future.result()
            print(json.dumps(result))
To run the program, save it to a file named `python_word_count.py` and run the following command: 
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/path/to/python python_word_count.py

Extract Code

I extracted the following code from that output: 

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import json
from concurrent.futures import ProcessPoolExecutor

def count_words(text):
    word_count = {}
    words = text.split()
    for word in words:
        word = word.strip(",.")
        if word in word_count:
            word_count[word] += 1
        else:
            word_count[word] = 1
    return word_count

def process_file(file_path, start, end):
    with open(file_path, 'r') as file:
        file.seek(start)
        text = file.read(end - start)
        word_count = count_words(text)
        return word_count

if __name__ == '__main__':
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        text = file.read()
    
    total_length = len(text)
    chunk_size = total_length // 4

    results = []
    with ProcessPoolExecutor(max_workers=4) as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = min((i+1) * chunk_size, total_length)
            future = executor.submit(process_file, file_path, start, end)
            futures.append(future)

        for future in futures:
            result = future.result()
            print(json.dumps(result))

Check if all of the following conditions are true:

LLM Generation

Query

Below is some student's code. I asked them to parallelize some code. Do not judge if it is correct, I have test cases for that. Just tell me if they tried to parallelize it. import json from concurrent.futures import ProcessPoolExecutor def count_words(text): word_count = {} words = text.split() for word in words: word = word.strip(",.") if word in word_count: word_count[word] += 1 else: word_count[word] = 1 return word_count def process_file(file_path, start, end): with open(file_path, 'r') as file: file.seek(start) text = file.read(end - start) word_count = count_words(text) return word_count if __name__ == '__main__': file_path = '/tmp/file.txt' with open(file_path, 'r') as file: text = file.read() total_length = len(text) chunk_size = total_length // 4 results = [] with ProcessPoolExecutor(max_workers=4) as executor: futures = [] for i in range(4): start = i * chunk_size end = min((i+1) * chunk_size, total_length) future = executor.submit(process_file, file_path, start, end) futures.append(future) for future in futures: result = future.result() print(json.dumps(result)) Answer either 'The student passes' or 'The student fails'.

Output

The student passes

Substring Evaluation

Testing if the previous output contains the string student passes: True

Run Code Interpreter

Running the following program: 

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import json
from concurrent.futures import ProcessPoolExecutor

def count_words(text):
    word_count = {}
    words = text.split()
    for word in words:
        word = word.strip(",.")
        if word in word_count:
            word_count[word] += 1
        else:
            word_count[word] = 1
    return word_count

def process_file(file_path, start, end):
    with open(file_path, 'r') as file:
        file.seek(start)
        text = file.read(end - start)
        word_count = count_words(text)
        return word_count

if __name__ == '__main__':
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        text = file.read()
    
    total_length = len(text)
    chunk_size = total_length // 4

    results = []
    with ProcessPoolExecutor(max_workers=4) as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = min((i+1) * chunk_size, total_length)
            future = executor.submit(process_file, file_path, start, end)
            futures.append(future)

        for future in futures:
            result = future.result()
            print(json.dumps(result))
And got the output: {"it": 4, "was": 4, "the": 4, "best": 1, "of": 4, "times": 2, "worst": 1, "age": 2, "wisdom": 1, "foolish": 1} {"ness": 1, "it": 4, "was": 4, "the": 3, "epoch": 2, "of": 3, "belief": 1, "incredulity": 1, "season": 1, "Light": 1, "th": 1} {"e": 1, "season": 1, "of": 3, "Darkness": 1, "it": 2, "was": 2, "the": 2, "spring": 1, "hope": 1, "winter": 1, "despair": 1, "we": 1, "had": 1, "everything": 1, "before": 1} {"us": 2, "we": 3, "had": 1, "nothing": 1, "before": 1, "were": 2, "all": 2, "going": 2, "direct": 2, "to": 1, "Heaven": 1, "the": 1, "other": 1, "way": 1}

PyFunc

Resulting in output: {'it': 10, 'was': 10, 'the': 10, 'best': 1, 'of': 10, 'times': 2, 'worst': 1, 'age': 2, 'wisdom': 1, 'foolish': 1, 'ness': 1, 'epoch': 2, 'belief': 1, 'incredulity': 1, 'season': 2, 'Light': 1, 'th': 1, 'e': 1, 'Darkness': 1, 'spring': 1, 'hope': 1, 'winter': 1, 'despair': 1, 'we': 4, 'had': 2, 'everything': 1, 'before': 2, 'us': 2, 'nothing': 1, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'to': 1, 'Heaven': 1, 'other': 1, 'way': 1}

Equal Evaluation

Testing if the previous output equals the string {'the': 11, 'it': 10, 'was': 10, 'of': 10, 'we': 4, 'times,': 2, 'age': 2, 'epoch': 2, 'season': 2, 'had': 2, 'before': 2, 'us,': 2, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'best': 1, 'worst': 1, 'wisdom,': 1, 'foolishness,': 1, 'belief,': 1, 'incredulity,': 1, 'Light,': 1, 'Darkness,': 1, 'spring': 1, 'hope,': 1, 'winter': 1, 'despair,': 1, 'everything': 1, 'nothing': 1, 'to': 1, 'Heaven,': 1, 'other': 1, 'way': 1}: False

Final Answer: False

Docker Setup

I have setup the docker container to run the model evaluation.

Initial Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

LLM Generation

Query

Write a self-contained Python program that prints a JSON output of how often each word appears in a text file located in /tmp/file.txt. So if the file contains "This is is is, an example" then the program should print to stdout. {"This": 1, "is": 2, "is,":1, "an":1, "example":1} The program should be run by calling /path/to/python_word_count with no arguments. Make it run in parallel on 4 cores at the same time, each taking 1/4 of the file. Print out 4 differnt json dicts, one per line. I'll do the merging.

Output

Here is a Python program that achieves the specified functionality: 

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import json
from concurrent.futures import ProcessPoolExecutor
from collections import Counter

def count_words(file_path, start, end):
    word_count = Counter()
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        word_count.update(words)
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file_size = file.seek(0, 2)
    
    chunk_size = file_size // 4

    with ProcessPoolExecutor(max_workers=4) as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = start + chunk_size
            futures.append(executor.submit(count_words, file_path, start, end))

        results = [future.result() for future in futures]

    for result in results:
        print(json.dumps(result))

if __name__ == '__main__':
    main()
This program reads a text file located at `/tmp/file.txt`, divides the file into 4 equal chunks, and counts the occurrences of each word in each chunk using multiprocessing on 4 cores. It then prints out 4 different JSON dictionaries, each containing the word counts for a specific chunk of the file.

Extract Code

I extracted the following code from that output: 

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import json
from concurrent.futures import ProcessPoolExecutor
from collections import Counter

def count_words(file_path, start, end):
    word_count = Counter()
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        word_count.update(words)
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file_size = file.seek(0, 2)
    
    chunk_size = file_size // 4

    with ProcessPoolExecutor(max_workers=4) as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = start + chunk_size
            futures.append(executor.submit(count_words, file_path, start, end))

        results = [future.result() for future in futures]

    for result in results:
        print(json.dumps(result))

if __name__ == '__main__':
    main()

Check if all of the following conditions are true:

LLM Generation

Query

Below is some student's code. I asked them to parallelize some code. Do not judge if it is correct, I have test cases for that. Just tell me if they tried to parallelize it. import json from concurrent.futures import ProcessPoolExecutor from collections import Counter def count_words(file_path, start, end): word_count = Counter() with open(file_path, 'r') as file: file.seek(start) chunk = file.read(end - start) words = chunk.split() word_count.update(words) return word_count def main(): file_path = '/tmp/file.txt' with open(file_path, 'r') as file: file_size = file.seek(0, 2) chunk_size = file_size // 4 with ProcessPoolExecutor(max_workers=4) as executor: futures = [] for i in range(4): start = i * chunk_size end = start + chunk_size futures.append(executor.submit(count_words, file_path, start, end)) results = [future.result() for future in futures] for result in results: print(json.dumps(result)) if __name__ == '__main__': main() Answer either 'The student passes' or 'The student fails'.

Output

The student passes.

Substring Evaluation

Testing if the previous output contains the string student passes: True

Run Code Interpreter

Running the following program: 

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import json
from concurrent.futures import ProcessPoolExecutor
from collections import Counter

def count_words(file_path, start, end):
    word_count = Counter()
    with open(file_path, 'r') as file:
        file.seek(start)
        chunk = file.read(end - start)
        words = chunk.split()
        word_count.update(words)
    return word_count

def main():
    file_path = '/tmp/file.txt'
    with open(file_path, 'r') as file:
        file_size = file.seek(0, 2)
    
    chunk_size = file_size // 4

    with ProcessPoolExecutor(max_workers=4) as executor:
        futures = []
        for i in range(4):
            start = i * chunk_size
            end = start + chunk_size
            futures.append(executor.submit(count_words, file_path, start, end))

        results = [future.result() for future in futures]

    for result in results:
        print(json.dumps(result))

if __name__ == '__main__':
    main()
And got the output: {"it": 4, "was": 4, "the": 4, "best": 1, "of": 4, "times,": 2, "worst": 1, "age": 2, "wisdom,": 1, "foolish": 1} {"ness,": 1, "it": 4, "was": 4, "the": 3, "epoch": 2, "of": 3, "belief,": 1, "incredulity,": 1, "season": 1, "Light,": 1, "th": 1} {"e": 1, "season": 1, "of": 3, "Darkness,": 1, "it": 2, "was": 2, "the": 2, "spring": 1, "hope,": 1, "winter": 1, "despair,": 1, "we": 1, "had": 1, "everything": 1, "before": 1} {"us,": 2, "we": 3, "had": 1, "nothing": 1, "before": 1, "were": 2, "all": 2, "going": 2, "direct": 2, "to": 1, "Heaven,": 1, "the": 1, "other": 1, "way": 1}

PyFunc

Resulting in output: {'it': 10, 'was': 10, 'the': 10, 'best': 1, 'of': 10, 'times,': 2, 'worst': 1, 'age': 2, 'wisdom,': 1, 'foolish': 1, 'ness,': 1, 'epoch': 2, 'belief,': 1, 'incredulity,': 1, 'season': 2, 'Light,': 1, 'th': 1, 'e': 1, 'Darkness,': 1, 'spring': 1, 'hope,': 1, 'winter': 1, 'despair,': 1, 'we': 4, 'had': 2, 'everything': 1, 'before': 2, 'us,': 2, 'nothing': 1, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'to': 1, 'Heaven,': 1, 'other': 1, 'way': 1}

Equal Evaluation

Testing if the previous output equals the string {'the': 11, 'it': 10, 'was': 10, 'of': 10, 'we': 4, 'times,': 2, 'age': 2, 'epoch': 2, 'season': 2, 'had': 2, 'before': 2, 'us,': 2, 'were': 2, 'all': 2, 'going': 2, 'direct': 2, 'best': 1, 'worst': 1, 'wisdom,': 1, 'foolishness,': 1, 'belief,': 1, 'incredulity,': 1, 'Light,': 1, 'Darkness,': 1, 'spring': 1, 'hope,': 1, 'winter': 1, 'despair,': 1, 'everything': 1, 'nothing': 1, 'to': 1, 'Heaven,': 1, 'other': 1, 'way': 1}: False

Final Answer: False