金声玉亮2.0模型评测报告

问题

You are an expert Python programmer, and here is your task: Write a function to find the similar elements from the given two tuple lists. Your code should pass these tests:

assert similar_elements((3, 4, 5, 6),(5, 7, 4, 10)) == (4, 5)
assert similar_elements((1, 2, 3, 4),(5, 4, 3, 7)) == (3, 4)
assert similar_elements((11, 12, 14, 13),(17, 15, 14, 13)) == (13, 14)

[BEGIN]
'def similar_elements(test_tup1, test_tup2):
res = tuple(set(test_tup1) & set(test_tup2))
return (res)'
[DONE]

You are an expert Python programmer, and here is your task: Write a python function to identify non-prime numbers. Your code should pass these tests:

assert is_not_prime(2) == False
assert is_not_prime(10) == True
assert is_not_prime(35) == True

[BEGIN]
'import math
def is_not_prime(n):
result = False
for i in range(2,int(math.sqrt(n)) + 1):
if n % i == 0:
result = True
return result'
[DONE]

You are an expert Python programmer, and here is your task: Write a function to find the largest integers from a given list of numbers using heap queue algorithm. Your code should pass these tests:

assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],3)==[85, 75, 65]
assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],2)==[85, 75]
assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[85, 75, 65, 58, 35]

[BEGIN]
'import heapq as hq
def heap_queue_largest(nums,n):
largest_nums = hq.nlargest(n, nums)
return largest_nums'
[DONE]

You are an expert Python programmer, and here is your task: Write a function to find the smallest integers from a given list of numbers using heap queue algorithm. Your code should pass these tests:

assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25]
assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22]
assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]

[BEGIN]

答案

模型	模型答案	测试结果
金声玉亮2.0	```python import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums ``` [DONE]	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
deepseekr1	To solve this problem, we need to find the smallest integers from a given list of numbers using the heap queue algorithm. The solution should efficiently determine the smallest elements without sorting the entire list, which can be particularly useful for large datasets. ### Approach The approach leverages Python's `heapq` module, which provides efficient heap-based operations. Specifically, we use the `nsmallest` function from this module. This function retrieves the n smallest elements from an iterable in an efficient manner, using a heap structure. The `nsmallest` function is optimal for this task as it avoids the overhead of sorting the entire list, which would be less efficient for large datasets. ### Solution Code ```python import heapq as hq def heap_queue_smallest(nums, n): return hq.nsmallest(n, nums) ``` ### Explanation 1. Importing the Module: We import the `heapq` module and alias it as `hq` for convenience. 2. Defining the Function: The function `heap_queue_smallest` takes two parameters: `nums` (the list of numbers) and `n` (the number of smallest elements to retrieve). 3. Using `nsmallest`: The `hq.nsmallest(n, nums)` function call efficiently retrieves the n smallest elements from the list `nums`. This function internally uses a heap structure to find the elements without fully sorting the list, making it more efficient for large datasets. This approach ensures that we efficiently and correctly retrieve the smallest n elements from the list, including handling duplicates as required by the problem constraints.	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
gpto1	[BEGIN] 'import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums' [DONE]	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
GPT-4o	```python import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums ``` This function uses the `heapq.nsmallest` method from the heap queue algorithm to find the smallest integers from the given list of numbers. Here are the tests that the function should pass: ```python assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 3) == [14, 22, 25] assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 2) == [14, 22] assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [14, 22, 22, 25, 35] ```	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
llama3.1-70B-Instruct	import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
llama3.1-405B-Instruct	import heapq as hq def heap_queue_smallest(nums,n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
DeepSeek-Coder-V2	```python import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums ``` [DONE]	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
Qwen2-72B-Instruct	'import heapq as hq def heap_queue_smallest(nums,n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums' [DONE]	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
baichuan4	To find the smallest integers from a given list of numbers using the heap queue algorithm, you can use the `heapq.nsmallest()` function from the Python standard library. Here's the implementation of the `heap_queue_smallest` function: ```python import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums ``` This function takes a list of numbers `nums` and an integer `n`, and returns a list containing the `n` smallest elements from `nums`. The `heapq.nsmallest()` function uses a min-heap internally to efficiently find the smallest elements. Let's test the function with the provided test cases: ```python assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 3) == [14, 22, 25] assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 2) == [14, 22] assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [14, 22, 22, 25, 35] ``` These tests should pass, indicating that the function is working correctly.	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
doubao	'import heapq as hq def heap_queue_smallest(nums,n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums' [DONE]	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
minimax	```python import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums ``` This function uses the `heapq.nsmallest` method to find the `n` smallest elements in the list `nums` and returns them as a list.	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
kimi	```python import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums ``` This function uses the `heapq` module to find the `n` smallest elements in a list. The `nsmallest` function returns a list of the `n` smallest elements from the input iterable. The tests provided should pass if the function is implemented correctly.	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
wenxinyiyan	`import heapq as hq def heap_queue_smallest(nums,n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums` [DONE] Explanation: The `heapq` module in Python provides an implementation of the heap queue algorithm, which is commonly used to find the largest or smallest elements in a dataset. In this case, we are interested in finding the smallest integers from a given list of numbers. The `heapq.nsmallest()` function takes two arguments: the first argument `n` specifies the number of smallest elements to retrieve, and the second argument `nums` is the input list of numbers. The function returns a list containing the `n` smallest elements from the input list. In the provided code, we define a function `heap_queue_smallest()` that takes two arguments: `nums` (the input list of numbers) and `n` (the number of smallest elements to find). Inside the function, we call `hq.nsmallest()` with the appropriate arguments and store the result in the variable `smallest_nums`. Finally, we return `smallest_nums` as the output of the function. Note that the code assumes that the `heapq` module has been imported with the alias `hq` for brevity. This allows us to use `hq.nsmallest()` instead of `heapq.nsmallest()` in the function call.	failed 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
zhipu	To achieve this task, we can use the `heapq` module in Python, which provides an efficient way to find the smallest elements in a list using a heap queue algorithm. The `heapq.nsmallest` function is particularly useful for this purpose. Here is the function `heap_queue_smallest` that meets the requirements: ```python import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums ``` Let's verify the function with the provided test cases: ```python assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 3) == [14, 22, 25] assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 2) == [14, 22] assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [14, 22, 22, 25, 35] print("All tests passed!") ``` When you run this code, it should output "All tests passed!" indicating that the function works correctly for the given test cases. ### Explanation: 1. Importing the `heapq` module: This module provides functions for implementing heaps based on regular lists. 2. Defining the `heap_queue_smallest` function: - `nums`: The list of numbers from which we need to find the smallest elements. - `n`: The number of smallest elements to find. - `smallest_nums`: This variable stores the result of `heapq.nsmallest(n, nums)`, which returns a list of the `n` smallest elements from `nums`. 3. Returning the result: The function returns the list of the smallest elements. This approach ensures that the function is both efficient and easy to understand, leveraging the built-in capabilities of the `heapq` module.	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
gpto1	[BEGIN] 'import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums' [DONE]	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]
deepseekv3	```python import heapq as hq def heap_queue_smallest(nums, n): smallest_nums = hq.nsmallest(n, nums) return smallest_nums ``` ### Explanation: - heapq.nsmallest(n, nums): This function from the `heapq` module returns the `n` smallest elements from the list `nums`. It uses a heap queue algorithm internally to efficiently find the smallest elements. - Return Value: The function returns a list containing the `n` smallest elements from the input list `nums`. ### Example Usage: ```python assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 3) == [14, 22, 25] assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 2) == [14, 22] assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [14, 22, 22, 25, 35] ``` These assertions confirm that the function correctly identifies the smallest integers in the list using the heap queue algorithm.	pass 测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22] assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]

模型

模型答案

测试结果

金声玉亮2.0

```python
import heapq as hq

def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums
```
[DONE]

pass
测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25]
assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22]
assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]

deepseekr1

To solve this problem, we need to find the smallest integers from a given list of numbers using the heap queue algorithm. The solution should efficiently determine the smallest elements without sorting the entire list, which can be particularly useful for large datasets.

### Approach
The approach leverages Python's `heapq` module, which provides efficient heap-based operations. Specifically, we use the `nsmallest` function from this module. This function retrieves the n smallest elements from an iterable in an efficient manner, using a heap structure. The `nsmallest` function is optimal for this task as it avoids the overhead of sorting the entire list, which would be less efficient for large datasets.

### Solution Code
```python
import heapq as hq

def heap_queue_smallest(nums, n):
return hq.nsmallest(n, nums)
```

### Explanation
1. **Importing the Module**: We import the `heapq` module and alias it as `hq` for convenience.
2. **Defining the Function**: The function `heap_queue_smallest` takes two parameters: `nums` (the list of numbers) and `n` (the number of smallest elements to retrieve).
3. **Using `nsmallest`**: The `hq.nsmallest(n, nums)` function call efficiently retrieves the n smallest elements from the list `nums`. This function internally uses a heap structure to find the elements without fully sorting the list, making it more efficient for large datasets.

This approach ensures that we efficiently and correctly retrieve the smallest n elements from the list, including handling duplicates as required by the problem constraints.

gpto1

[BEGIN]
'import heapq as hq
def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums'
[DONE]

GPT-4o

```python
import heapq as hq

def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums
```

This function uses the `heapq.nsmallest` method from the heap queue algorithm to find the smallest integers from the given list of numbers. Here are the tests that the function should pass:

```python
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 3) == [14, 22, 25]
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 2) == [14, 22]
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [14, 22, 22, 25, 35]
```

llama3.1-70B-Instruct

import heapq as hq

def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums

llama3.1-405B-Instruct

import heapq as hq
def heap_queue_smallest(nums,n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums

DeepSeek-Coder-V2

```python
import heapq as hq

def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums
```
[DONE]

Qwen2-72B-Instruct

'import heapq as hq
def heap_queue_smallest(nums,n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums'
[DONE]

baichuan4

To find the smallest integers from a given list of numbers using the heap queue algorithm, you can use the `heapq.nsmallest()` function from the Python standard library. Here's the implementation of the `heap_queue_smallest` function:

```python
import heapq as hq

def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums
```

This function takes a list of numbers `nums` and an integer `n`, and returns a list containing the `n` smallest elements from `nums`. The `heapq.nsmallest()` function uses a min-heap internally to efficiently find the smallest elements.

Let's test the function with the provided test cases:

```python
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 3) == [14, 22, 25]
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 2) == [14, 22]
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [14, 22, 22, 25, 35]
```

These tests should pass, indicating that the function is working correctly.

doubao

'import heapq as hq
def heap_queue_smallest(nums,n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums'
[DONE]

minimax

kimi

```python
import heapq as hq

def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums
```

This function uses the `heapq` module to find the `n` smallest elements in a list. The `nsmallest` function returns a list of the `n` smallest elements from the input iterable. The tests provided should pass if the function is implemented correctly.

wenxinyiyan

`import heapq as hq
def heap_queue_smallest(nums,n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums`
[DONE]

Explanation:
The `heapq` module in Python provides an implementation of the heap queue algorithm, which is commonly used to find the largest or smallest elements in a dataset. In this case, we are interested in finding the smallest integers from a given list of numbers.

The `heapq.nsmallest()` function takes two arguments: the first argument `n` specifies the number of smallest elements to retrieve, and the second argument `nums` is the input list of numbers. The function returns a list containing the `n` smallest elements from the input list.

In the provided code, we define a function `heap_queue_smallest()` that takes two arguments: `nums` (the input list of numbers) and `n` (the number of smallest elements to find). Inside the function, we call `hq.nsmallest()` with the appropriate arguments and store the result in the variable `smallest_nums`. Finally, we return `smallest_nums` as the output of the function.

Note that the code assumes that the `heapq` module has been imported with the alias `hq` for brevity. This allows us to use `hq.nsmallest()` instead of `heapq.nsmallest()` in the function call.

failed
测试用例：assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],3)==[14, 22, 25]
assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 25, 58],2)==[14, 22]
assert heap_queue_smallest( [25, 35, 22, 85, 14, 65, 75, 22, 58],5)==[14, 22, 22, 25, 35]

zhipu

To achieve this task, we can use the `heapq` module in Python, which provides an efficient way to find the smallest elements in a list using a heap queue algorithm. The `heapq.nsmallest` function is particularly useful for this purpose.

Here is the function `heap_queue_smallest` that meets the requirements:

```python
import heapq as hq

def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums
```

Let's verify the function with the provided test cases:

```python
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 3) == [14, 22, 25]
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 2) == [14, 22]
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [14, 22, 22, 25, 35]

print("All tests passed!")
```

When you run this code, it should output "All tests passed!" indicating that the function works correctly for the given test cases.

### Explanation:
1. **Importing the `heapq` module**: This module provides functions for implementing heaps based on regular lists.
2. **Defining the `heap_queue_smallest` function**:
- `nums`: The list of numbers from which we need to find the smallest elements.
- `n`: The number of smallest elements to find.
- `smallest_nums`: This variable stores the result of `heapq.nsmallest(n, nums)`, which returns a list of the `n` smallest elements from `nums`.
3. **Returning the result**: The function returns the list of the smallest elements.

This approach ensures that the function is both efficient and easy to understand, leveraging the built-in capabilities of the `heapq` module.

gpto1

[BEGIN]
'import heapq as hq
def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums'
[DONE]

deepseekv3

```python
import heapq as hq

def heap_queue_smallest(nums, n):
smallest_nums = hq.nsmallest(n, nums)
return smallest_nums
```

### Explanation:
- **heapq.nsmallest(n, nums)**: This function from the `heapq` module returns the `n` smallest elements from the list `nums`. It uses a heap queue algorithm internally to efficiently find the smallest elements.
- **Return Value**: The function returns a list containing the `n` smallest elements from the input list `nums`.

### Example Usage:
```python
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 3) == [14, 22, 25]
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 25, 58], 2) == [14, 22]
assert heap_queue_smallest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [14, 22, 22, 25, 35]
```

These assertions confirm that the function correctly identifies the smallest integers in the list using the heap queue algorithm.