I’m trying to compare GPU vs. CPU resource consumption for different operations, and I’ve written this generic function. The issue is that memory is coming back negative from this. Some investigation and GPTing indicate that some memory was freed up during the operation, potentially due to garbage collection or other system activities. Is there any alternative to this or any fix?

def measure_execution_time_and_cpu_usage(func, *args, dataset_size=None, **kwargs):
    try:
        # Start the timer
        start_time = time.time()

        # Before execution (CPU)
        cpu_util_before = psutil.cpu_percent(interval=None)
        cpu_memory_before = psutil.virtual_memory().used

        # Execute the function
        result = func(*args, **kwargs)

        # After execution (CPU)
        cpu_memory_after = psutil.virtual_memory().used
        cpu_util_after = psutil.cpu_percent(interval=None)

        # Calculate metrics
        cpu_memory_used = cpu_memory_after - cpu_memory_before
        execution_time = time.time() - start_time
        cpu_utilization = cpu_util_after - cpu_util_before

        # Calculate throughput and latency if dataset_size is provided
        throughput = latency = None
        if dataset_size:
            throughput = dataset_size / execution_time
            latency = execution_time / dataset_size

        # Print metrics
        print(f"CPU Memory Usage: {cpu_memory_used} bytes")
        print(f"Execution Time: {execution_time} seconds")
        print(f"CPU Utilization: {cpu_utilization}%")
        if throughput:
            print(f"Throughput: {throughput} rows/second")
            print(f"Latency: {latency} seconds/row")

        return result, execution_time, cpu_memory_used, throughput, latency, cpu_utilization
    
    except Exception as e:
        print(f"An error occurred: {e}")
        return None, None, None, None, None, None