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's a Python program that meets your requirements: 

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import os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(file_part):
    word_counts = Counter()
    with open('/tmp/file.txt', 'r') as f:
        for i, line in enumerate(f):
            if i % 4 == file_part:
                words = line.split()
                word_counts.update(words)
    return dict(word_counts)

if __name__ == '__main__':
    pool = Pool(processes=4)
    word_counts = pool.map(count_words, range(4))
    pool.close()
    pool.join()

    for word_count in word_counts:
        print(json.dumps(word_count))
Here's how the program works: 1. The `count_words` function takes a `file_part` argument, which is an integer between 0 and 3. It opens the `/tmp/file.txt` file and iterates over its lines. For each line, it checks if the line number modulo 4 is equal to `file_part`. If it is, it splits the line into words and updates the `word_counts` Counter with those words. 2. In the `if __name__ == '__main__'` block, the program creates a `Pool` of 4 processes using `multiprocessing.Pool(processes=4)`. 3. It then calls `pool.map(count_words, range(4))`, which applies the `count_words` function to each value in the `range(4)` iterable (i.e., 0, 1, 2, and 3). This effectively divides the file into 4 parts and processes each part in parallel using a separate process. 4. After the parallel processing is complete, the program closes and joins the pool using `pool.close()` and `pool.join()`. 5. Finally, the program iterates over the list of `word_counts` dictionaries (one per process) and prints each dictionary as a JSON string using `json.dumps`. To run the program, save it to a file (e.g., `word_count.py`) and run it with Python: 
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python word_count.py
This will print four JSON dictionaries to stdout, one per line, each containing the word counts for a quarter of the file. Note: This program assumes that the `/tmp/file.txt` file exists and is readable. If the file is large, you may need to adjust the memory usage or consider using a different approach, such as streaming the file line by line instead of loading the entire file into memory.

Extract Code

I extracted the following code from that output: 

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import os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(file_part):
    word_counts = Counter()
    with open('/tmp/file.txt', 'r') as f:
        for i, line in enumerate(f):
            if i % 4 == file_part:
                words = line.split()
                word_counts.update(words)
    return dict(word_counts)

if __name__ == '__main__':
    pool = Pool(processes=4)
    word_counts = pool.map(count_words, range(4))
    pool.close()
    pool.join()

    for word_count in word_counts:
        print(json.dumps(word_count))

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 os import json from collections import Counter from multiprocessing import Pool def count_words(file_part): word_counts = Counter() with open('/tmp/file.txt', 'r') as f: for i, line in enumerate(f): if i % 4 == file_part: words = line.split() word_counts.update(words) return dict(word_counts) if __name__ == '__main__': pool = Pool(processes=4) word_counts = pool.map(count_words, range(4)) pool.close() pool.join() for word_count in word_counts: print(json.dumps(word_count)) 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 os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(file_part):
    word_counts = Counter()
    with open('/tmp/file.txt', 'r') as f:
        for i, line in enumerate(f):
            if i % 4 == file_part:
                words = line.split()
                word_counts.update(words)
    return dict(word_counts)

if __name__ == '__main__':
    pool = Pool(processes=4)
    word_counts = pool.map(count_words, range(4))
    pool.close()
    pool.join()

    for word_count in word_counts:
        print(json.dumps(word_count))
And got the output: {"it": 10, "was": 10, "the": 11, "best": 1, "of": 10, "times,": 2, "worst": 1, "age": 2, "wisdom,": 1, "foolishness,": 1, "epoch": 2, "belief,": 1, "incredulity,": 1, "season": 2, "Light,": 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} {} {} {}

PyFunc

Resulting in output: {'it': 10, 'was': 10, 'the': 11, 'best': 1, 'of': 10, 'times,': 2, 'worst': 1, 'age': 2, 'wisdom,': 1, 'foolishness,': 1, 'epoch': 2, 'belief,': 1, 'incredulity,': 1, 'season': 2, 'Light,': 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}: True

Final Answer: True

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's a self-contained Python program that reads a text file located at `/tmp/file.txt`, counts the occurrences of each word, and prints four separate JSON dictionaries (one per line) representing the word counts for each quarter of the file. The program uses the `multiprocessing` module to split the file into four parts and process them in parallel on four separate cores. 

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import os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    word_counts = Counter()
    for line in chunk:
        words = line.split()
        word_counts.update(words)
    return dict(word_counts)

def read_chunk(start, end, filename):
    with open(filename, 'r') as f:
        f.seek(start)
        lines = []
        offset = start
        while offset < end:
            line = f.readline()
            if not line:
                break
            lines.append(line.rstrip('\n'))
            offset += len(line)
    return lines

def main():
    filename = "/tmp/file.txt"
    if os.path.isfile(filename):
        file_size = os.path.getsize(filename)
        chunk_size = file_size // 4

        with Pool(processes=4) as pool:
            chunks = [
                pool.apply_async(read_chunk, args=(start, start + chunk_size, filename))
                for start in range(0, file_size, chunk_size)
            ]

            results = [pool.apply_async(count_words, args=(chunk.get(),)) for chunk in chunks]

            for result in results:
                print(json.dumps(result.get()))
    else:
        print(f"Error: File '{filename}' not found.")

if __name__ == "__main__":
    main()
To run the program, save it to a file (e.g., `word_count.py`) and execute it with Python: 
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python word_count.py
The program will print four separate JSON dictionaries (one per line) representing the word counts for each quarter of the file `/tmp/file.txt`. Here's how the program works: 1. The `count_words` function takes a list of lines (a chunk of the file) and counts the occurrences of each word using the `collections.Counter` class. 2. The `read_chunk` function reads a quarter of the file by seeking to the appropriate offset and reading lines until the end of the chunk is reached. 3. The `main` function checks if the file `/tmp/file.txt` exists. If it does, it calculates the file size and the size of each chunk (quarter of the file). 4. The `multiprocessing.Pool` is used to create four worker processes. Each worker reads a quarter of the file using the `read_chunk` function and counts the words using the `count_words` function. 5. The `pool.apply_async` method is used to schedule the tasks asynchronously, and the results are collected using the `get` method. 6. The final word counts for each chunk are printed as separate JSON dictionaries (one per line). Note that this program assumes that the file `/tmp/file.txt` exists and is readable. If the file is not found, an error message will be printed.

Extract Code

I extracted the following code from that output: 

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import os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    word_counts = Counter()
    for line in chunk:
        words = line.split()
        word_counts.update(words)
    return dict(word_counts)

def read_chunk(start, end, filename):
    with open(filename, 'r') as f:
        f.seek(start)
        lines = []
        offset = start
        while offset < end:
            line = f.readline()
            if not line:
                break
            lines.append(line.rstrip('\n'))
            offset += len(line)
    return lines

def main():
    filename = "/tmp/file.txt"
    if os.path.isfile(filename):
        file_size = os.path.getsize(filename)
        chunk_size = file_size // 4

        with Pool(processes=4) as pool:
            chunks = [
                pool.apply_async(read_chunk, args=(start, start + chunk_size, filename))
                for start in range(0, file_size, chunk_size)
            ]

            results = [pool.apply_async(count_words, args=(chunk.get(),)) for chunk in chunks]

            for result in results:
                print(json.dumps(result.get()))
    else:
        print(f"Error: File '{filename}' not found.")

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 os import json from collections import Counter from multiprocessing import Pool def count_words(chunk): word_counts = Counter() for line in chunk: words = line.split() word_counts.update(words) return dict(word_counts) def read_chunk(start, end, filename): with open(filename, 'r') as f: f.seek(start) lines = [] offset = start while offset < end: line = f.readline() if not line: break lines.append(line.rstrip('\n')) offset += len(line) return lines def main(): filename = "/tmp/file.txt" if os.path.isfile(filename): file_size = os.path.getsize(filename) chunk_size = file_size // 4 with Pool(processes=4) as pool: chunks = [ pool.apply_async(read_chunk, args=(start, start + chunk_size, filename)) for start in range(0, file_size, chunk_size) ] results = [pool.apply_async(count_words, args=(chunk.get(),)) for chunk in chunks] for result in results: print(json.dumps(result.get())) else: print(f"Error: File '{filename}' not found.") 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 os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    word_counts = Counter()
    for line in chunk:
        words = line.split()
        word_counts.update(words)
    return dict(word_counts)

def read_chunk(start, end, filename):
    with open(filename, 'r') as f:
        f.seek(start)
        lines = []
        offset = start
        while offset < end:
            line = f.readline()
            if not line:
                break
            lines.append(line.rstrip('\n'))
            offset += len(line)
    return lines

def main():
    filename = "/tmp/file.txt"
    if os.path.isfile(filename):
        file_size = os.path.getsize(filename)
        chunk_size = file_size // 4

        with Pool(processes=4) as pool:
            chunks = [
                pool.apply_async(read_chunk, args=(start, start + chunk_size, filename))
                for start in range(0, file_size, chunk_size)
            ]

            results = [pool.apply_async(count_words, args=(chunk.get(),)) for chunk in chunks]

            for result in results:
                print(json.dumps(result.get()))
    else:
        print(f"Error: File '{filename}' not found.")

if __name__ == "__main__":
    main()
And got the output: {"it": 10, "was": 10, "the": 11, "best": 1, "of": 10, "times,": 2, "worst": 1, "age": 2, "wisdom,": 1, "foolishness,": 1, "epoch": 2, "belief,": 1, "incredulity,": 1, "season": 2, "Light,": 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} {"ness,": 1, "it": 6, "was": 6, "the": 7, "epoch": 2, "of": 6, "belief,": 1, "incredulity,": 1, "season": 2, "Light,": 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} {"e": 1, "season": 1, "of": 3, "Darkness,": 1, "it": 2, "was": 2, "the": 3, "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} {"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': 18, 'was': 18, 'the': 22, 'best': 1, 'of': 19, 'times,': 2, 'worst': 1, 'age': 2, 'wisdom,': 1, 'foolishness,': 1, 'epoch': 4, 'belief,': 2, 'incredulity,': 2, 'season': 5, 'Light,': 2, 'Darkness,': 3, 'spring': 3, 'hope,': 3, 'winter': 3, 'despair,': 3, 'we': 15, 'had': 7, 'everything': 3, 'before': 7, 'us,': 8, 'nothing': 4, 'were': 8, 'all': 8, 'going': 8, 'direct': 8, 'to': 4, 'Heaven,': 4, 'other': 4, 'way': 4, 'ness,': 1, 'e': 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's a self-contained Python program that prints a JSON output of word counts for a text file located at `/tmp/file.txt`. The program runs in parallel on 4 cores, each taking 1/4 of the file, and prints out 4 different JSON dicts, one per line: 

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import os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    word_counts = Counter()
    for line in chunk:
        words = line.split()
        word_counts.update(words)
    return dict(word_counts)

def read_file_chunk(start, end, filename):
    with open(filename, "r") as f:
        f.seek(start)
        lines = f.readlines(end - start)
    return lines

def main():
    filename = "/tmp/file.txt"
    filesize = os.path.getsize(filename)
    chunk_size = filesize // 4

    chunks = [
        (0, chunk_size),
        (chunk_size, chunk_size * 2),
        (chunk_size * 2, chunk_size * 3),
        (chunk_size * 3, filesize)
    ]

    pool = Pool(processes=4)
    results = pool.starmap(count_words, [(read_file_chunk(start, end, filename)) for start, end in chunks])
    pool.close()
    pool.join()

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

if __name__ == "__main__":
    main()
This program uses the `multiprocessing` module to create 4 worker processes, each responsible for counting words in a different quarter of the file. The `read_file_chunk` function reads a specific range of bytes from the file, and the `count_words` function counts the words in the given chunk of lines. The `main` function calculates the file size and divides it into 4 equal chunks. It then creates a `Pool` object with 4 worker processes and uses `starmap` to apply the `count_words` function to each chunk of lines. The resulting word counts are printed as JSON dicts, one per line. To run the program, save it to a file (e.g., `word_count.py`) and execute it with Python: 
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/path/to/python word_count.py
This will print 4 different JSON dicts, one per line, representing the word counts for each quarter of the file. Note: Ensure that the `/tmp/file.txt` file exists and is readable by the program.

Extract Code

I extracted the following code from that output: 

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import os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    word_counts = Counter()
    for line in chunk:
        words = line.split()
        word_counts.update(words)
    return dict(word_counts)

def read_file_chunk(start, end, filename):
    with open(filename, "r") as f:
        f.seek(start)
        lines = f.readlines(end - start)
    return lines

def main():
    filename = "/tmp/file.txt"
    filesize = os.path.getsize(filename)
    chunk_size = filesize // 4

    chunks = [
        (0, chunk_size),
        (chunk_size, chunk_size * 2),
        (chunk_size * 2, chunk_size * 3),
        (chunk_size * 3, filesize)
    ]

    pool = Pool(processes=4)
    results = pool.starmap(count_words, [(read_file_chunk(start, end, filename)) for start, end in chunks])
    pool.close()
    pool.join()

    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 os import json from collections import Counter from multiprocessing import Pool def count_words(chunk): word_counts = Counter() for line in chunk: words = line.split() word_counts.update(words) return dict(word_counts) def read_file_chunk(start, end, filename): with open(filename, "r") as f: f.seek(start) lines = f.readlines(end - start) return lines def main(): filename = "/tmp/file.txt" filesize = os.path.getsize(filename) chunk_size = filesize // 4 chunks = [ (0, chunk_size), (chunk_size, chunk_size * 2), (chunk_size * 2, chunk_size * 3), (chunk_size * 3, filesize) ] pool = Pool(processes=4) results = pool.starmap(count_words, [(read_file_chunk(start, end, filename)) for start, end in chunks]) pool.close() pool.join() 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 os
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    word_counts = Counter()
    for line in chunk:
        words = line.split()
        word_counts.update(words)
    return dict(word_counts)

def read_file_chunk(start, end, filename):
    with open(filename, "r") as f:
        f.seek(start)
        lines = f.readlines(end - start)
    return lines

def main():
    filename = "/tmp/file.txt"
    filesize = os.path.getsize(filename)
    chunk_size = filesize // 4

    chunks = [
        (0, chunk_size),
        (chunk_size, chunk_size * 2),
        (chunk_size * 2, chunk_size * 3),
        (chunk_size * 3, filesize)
    ]

    pool = Pool(processes=4)
    results = pool.starmap(count_words, [(read_file_chunk(start, end, filename)) for start, end in chunks])
    pool.close()
    pool.join()

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

if __name__ == "__main__":
    main()
And got the output: {"i": 27, "t": 34, "w": 20, "a": 22, "s": 28, "h": 21, "e": 47, "b": 4, "o": 26, "f": 14, "m": 3, ",": 13, "r": 14, "g": 10, "d": 7, "l": 7, "n": 13, "p": 5, "c": 5, "u": 3, "y": 3, "L": 1, "D": 1, "k": 1, "v": 2, "H": 1} {"n": 13, "e": 38, "s": 18, ",": 10, "i": 19, "t": 22, "w": 14, "a": 16, "h": 16, "p": 5, "o": 18, "c": 5, "f": 9, "b": 3, "l": 6, "r": 13, "d": 6, "u": 3, "y": 3, "L": 1, "g": 8, "D": 1, "k": 1, "v": 2, "H": 1} {"e": 28, "s": 10, "a": 11, "o": 12, "n": 10, "f": 5, "D": 1, "r": 12, "k": 1, ",": 6, "i": 11, "t": 12, "w": 10, "h": 9, "p": 3, "g": 7, "d": 5, "v": 2, "y": 2, "b": 2, "u": 2, "l": 4, "c": 2, "H": 1} {"u": 2, "s": 2, ",": 3, "w": 6, "e": 15, "h": 4, "a": 5, "d": 3, "n": 5, "o": 6, "t": 6, "i": 5, "g": 5, "b": 1, "f": 1, "r": 6, "l": 4, "c": 2, "H": 1, "v": 1, "y": 1}

PyFunc

Resulting in output: {'i': 62, 't': 74, 'w': 50, 'a': 54, 's': 58, 'h': 50, 'e': 128, 'b': 10, 'o': 62, 'f': 29, 'm': 3, ',': 32, 'r': 45, 'g': 30, 'd': 21, 'l': 21, 'n': 41, 'p': 13, 'c': 14, 'u': 10, 'y': 9, 'L': 2, 'D': 3, 'k': 3, 'v': 7, 'H': 4}

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's a self-contained Python program that meets your requirements: 

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import os
import sys
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    words = chunk.split()
    return Counter(words)

def process_chunk(start, end, file_path):
    with open(file_path, "r") as f:
        f.seek(start)
        chunk = f.read(end - start)
        word_counts = count_words(chunk)
        return dict(word_counts)

def main():
    if len(sys.argv) != 2:
        print("Usage: python word_count.py /path/to/file.txt")
        sys.exit(1)

    file_path = sys.argv[1]
    file_size = os.path.getsize(file_path)
    chunk_size = file_size // 4

    pool = Pool(processes=4)
    results = []
    for i in range(4):
        start = i * chunk_size
        end = start + chunk_size if i < 3 else file_size
        result = pool.apply_async(process_chunk, args=(start, end, file_path))
        results.append(result)

    pool.close()
    pool.join()

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

if __name__ == "__main__":
    main()
To run the program, save it as a file (e.g., `word_count.py`) and run the following command: 
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python word_count.py /tmp/file.txt
This program uses the `multiprocessing` module to split the file into four chunks and process each chunk in parallel using four worker processes. Each worker process reads its assigned chunk of the file, counts the words in the chunk, and returns a dictionary of word counts. The main process then prints each dictionary as a JSON string to stdout. Note that this program assumes that the `/tmp/file.txt` file exists and is readable. If the file path is not provided as an argument, the program will exit with an error message.

Extract Code

I extracted the following code from that output: 

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import os
import sys
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    words = chunk.split()
    return Counter(words)

def process_chunk(start, end, file_path):
    with open(file_path, "r") as f:
        f.seek(start)
        chunk = f.read(end - start)
        word_counts = count_words(chunk)
        return dict(word_counts)

def main():
    if len(sys.argv) != 2:
        print("Usage: python word_count.py /path/to/file.txt")
        sys.exit(1)

    file_path = sys.argv[1]
    file_size = os.path.getsize(file_path)
    chunk_size = file_size // 4

    pool = Pool(processes=4)
    results = []
    for i in range(4):
        start = i * chunk_size
        end = start + chunk_size if i < 3 else file_size
        result = pool.apply_async(process_chunk, args=(start, end, file_path))
        results.append(result)

    pool.close()
    pool.join()

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

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 os import sys import json from collections import Counter from multiprocessing import Pool def count_words(chunk): words = chunk.split() return Counter(words) def process_chunk(start, end, file_path): with open(file_path, "r") as f: f.seek(start) chunk = f.read(end - start) word_counts = count_words(chunk) return dict(word_counts) def main(): if len(sys.argv) != 2: print("Usage: python word_count.py /path/to/file.txt") sys.exit(1) file_path = sys.argv[1] file_size = os.path.getsize(file_path) chunk_size = file_size // 4 pool = Pool(processes=4) results = [] for i in range(4): start = i * chunk_size end = start + chunk_size if i < 3 else file_size result = pool.apply_async(process_chunk, args=(start, end, file_path)) results.append(result) pool.close() pool.join() for result in results: print(json.dumps(result.get())) 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 os
import sys
import json
from collections import Counter
from multiprocessing import Pool

def count_words(chunk):
    words = chunk.split()
    return Counter(words)

def process_chunk(start, end, file_path):
    with open(file_path, "r") as f:
        f.seek(start)
        chunk = f.read(end - start)
        word_counts = count_words(chunk)
        return dict(word_counts)

def main():
    if len(sys.argv) != 2:
        print("Usage: python word_count.py /path/to/file.txt")
        sys.exit(1)

    file_path = sys.argv[1]
    file_size = os.path.getsize(file_path)
    chunk_size = file_size // 4

    pool = Pool(processes=4)
    results = []
    for i in range(4):
        start = i * chunk_size
        end = start + chunk_size if i < 3 else file_size
        result = pool.apply_async(process_chunk, args=(start, end, file_path))
        results.append(result)

    pool.close()
    pool.join()

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

if __name__ == "__main__":
    main()
And got the output: Usage: python word_count.py /path/to/file.txt

PyFunc

Resulting in output: {}

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's 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`. It runs in parallel on 4 cores, with each core taking 1/4 of the file. The program prints out 4 different JSON dicts, one per line. 

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import json
import multiprocessing
import os

def count_words(start, end, file_path):
    word_count = {}
    with open(file_path, 'r') as file:
        file.seek(start)
        lines = file.read(end - start).split()
        for word in lines:
            word_count[word] = word_count.get(word, 0) + 1
    return word_count

def main():
    file_path = '/tmp/file.txt'
    if not os.path.exists(file_path):
        print(f"Error: File {file_path} does not exist.")
        return

    file_size = os.path.getsize(file_path)
    chunk_size = file_size // 4

    processes = []
    for i in range(4):
        start = i * chunk_size
        end = start + chunk_size if i < 3 else file_size
        p = multiprocessing.Process(target=count_words, args=(start, end, file_path))
        processes.append(p)
        p.start()

    for process in processes:
        word_count = process.join()
        print(json.dumps(word_count))

if __name__ == "__main__":
    main()
To run the program, save it as a file (e.g., `word_count.py`) and execute it with Python: 
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python word_count.py
Here's how the program works: 1. The `count_words` function takes three arguments: `start` (the starting position in the file), `end` (the ending position in the file), and `file_path` (the path to the text file). It reads the portion of the file between `start` and `end`, splits the text into words, and counts the occurrences of each word. It returns a dictionary with the word counts. 2. The `main` function first checks if the file `/tmp/file.txt` exists. If not, it prints an error message and returns. 3. The size of the file is determined using `os.path.getsize`, and the file is divided into four equal chunks (`chunk_size`). 4. Four separate processes are created using `multiprocessing.Process`, each running the `count_words` function with the appropriate start and end positions for its chunk of the file. 5. Each process starts, and the `main` function waits for all processes to finish using `process.join()`. 6. As each process finishes, its word count dictionary is printed as a JSON string using `json.dumps`. Note that this program assumes that words are separated by whitespace characters (spaces, tabs, newlines). If you need a different word separation strategy, you'll need to modify the `count_words` function accordingly.

Extract Code

I extracted the following code from that output: 

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import json
import multiprocessing
import os

def count_words(start, end, file_path):
    word_count = {}
    with open(file_path, 'r') as file:
        file.seek(start)
        lines = file.read(end - start).split()
        for word in lines:
            word_count[word] = word_count.get(word, 0) + 1
    return word_count

def main():
    file_path = '/tmp/file.txt'
    if not os.path.exists(file_path):
        print(f"Error: File {file_path} does not exist.")
        return

    file_size = os.path.getsize(file_path)
    chunk_size = file_size // 4

    processes = []
    for i in range(4):
        start = i * chunk_size
        end = start + chunk_size if i < 3 else file_size
        p = multiprocessing.Process(target=count_words, args=(start, end, file_path))
        processes.append(p)
        p.start()

    for process in processes:
        word_count = process.join()
        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 import multiprocessing import os def count_words(start, end, file_path): word_count = {} with open(file_path, 'r') as file: file.seek(start) lines = file.read(end - start).split() for word in lines: word_count[word] = word_count.get(word, 0) + 1 return word_count def main(): file_path = '/tmp/file.txt' if not os.path.exists(file_path): print(f"Error: File {file_path} does not exist.") return file_size = os.path.getsize(file_path) chunk_size = file_size // 4 processes = [] for i in range(4): start = i * chunk_size end = start + chunk_size if i < 3 else file_size p = multiprocessing.Process(target=count_words, args=(start, end, file_path)) processes.append(p) p.start() for process in processes: word_count = process.join() print(json.dumps(word_count)) if __name__ == "__main__": main() Answer either 'The student passes' or 'The student fails'.

Output

The student fails.

Substring Evaluation

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

Run Code Interpreter

Running the following program: 

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import json
import multiprocessing
import os

def count_words(start, end, file_path):
    word_count = {}
    with open(file_path, 'r') as file:
        file.seek(start)
        lines = file.read(end - start).split()
        for word in lines:
            word_count[word] = word_count.get(word, 0) + 1
    return word_count

def main():
    file_path = '/tmp/file.txt'
    if not os.path.exists(file_path):
        print(f"Error: File {file_path} does not exist.")
        return

    file_size = os.path.getsize(file_path)
    chunk_size = file_size // 4

    processes = []
    for i in range(4):
        start = i * chunk_size
        end = start + chunk_size if i < 3 else file_size
        p = multiprocessing.Process(target=count_words, args=(start, end, file_path))
        processes.append(p)
        p.start()

    for process in processes:
        word_count = process.join()
        print(json.dumps(word_count))

if __name__ == "__main__":
    main()
And got the output: null null null null

PyFunc

Resulting in output: {}

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