使用def add(variables_dict): result_dict = {} return result_dict格式定义一个简单加法函数，单测代码需符合pytest语法

以下是使用def add(variables_dict): result_dict = {} return result_dict语法定义一个简单加法函数的代码：

def add(variables_dict):
    result_dict = {}
    result_dict['result'] = variables_dict['num1'] + variables_dict['num2']
    return result_dict

以下是单测代码，符合pytest语法：

import pytest

def test_add():
    variables_dict = {'num1': 2, 'num2': 3}
    result_dict = add(variables_dict)
    assert result_dict == {'result': 5}

在此单测代码中，我们定义了一个test_add()函数，并使用pytest框架中的assert语句来断言add()函数返回的结果是否与我们预期的结果相同。如果结果相同，则测试通过。

相关问题

g_dict_layouts = {} g_dict_layouts_deep = {} g_dict_layouts_fn = {}

As an AI language model, I cannot determine the specific purpose of these variables without more context. However, I can explain some general concepts related to Python dictionaries.

In Python, a dictionary is a collection of key-value pairs. The "g_dict_layouts", "g_dict_layouts_deep", and "g_dict_layouts_fn" variables seem to be three separate dictionary objects.

The first one, "g_dict_layouts", could potentially store layout information for some kind of application or program. The second one, "g_dict_layouts_deep", may be a nested dictionary with deeper levels of nesting. The third one, "g_dict_layouts_fn", could potentially be a dictionary that maps function names to their respective layouts.

Without more information about the specific use case and context, it is difficult to provide a more accurate explanation.

RuntimeError: When eager execution is enabled, var_list must specify a list or dict of variables to save

这个错误通常出现在使用 TensorFlow 的时候，当启用了 Eager Execution 模式，同时在保存模型协同作战也面临着许多挑战，需要加强技术研发和创新，提高无人机的时候，未正确指定需要保存的变量列表。

解决方案是在保存模型的代码中明确指定需要保存的变量列表，例如：

saver = tf.train.Saver(var_list=your_variable_list)
s系统的智能化和自主化，保障无人机系统的安全和合法使用。