为 Python 函数生成文档字符串和注释。
在对 Cloud 控制台使用不同参数值时,或通过直接调用 Vertex AI API,您可以直接查询模型,并测试返回的结果。
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提示自由格式Here are Python codes. Insert the document comment (docstring) for all functions, including the nested functions. def is_dag_dfs(graph): visited = set() on_stack = set() # Track nodes on recursion stack def dfs(node): if node in on_stack: return False # Back-edge found (cycle) if node in visited: return True on_stack.add(node) visited.add(node) for neighbor in graph.get(node, []): if not dfs(neighbor): return False on_stack.remove(node) return True return all(dfs(node) for node in graph) 响应```python def is_dag_dfs(graph): """ Determines if a directed graph is a Directed Acyclic Graph (DAG) using Depth-First Search (DFS). Args: graph (dict): A dictionary representing the graph, where keys are nodes and values are lists of adjacent nodes. Returns: bool: True if the graph is a DAG, False otherwise. """ visited = set() on_stack = set() # Track nodes on recursion stack def dfs(node): """ Performs DFS on the graph starting from the given node. Args: node: The node to start DFS from. Returns: bool: True if the graph is a DAG, False if a cycle is found. """ if node in on_stack: return False # Back-edge found (cycle) if node in visited: return True on_stack.add(node) visited.add(node) for neighbor in graph.get(node, []): if not dfs(neighbor): return False on_stack.remove(node) return True return all(dfs(node) for node in graph) ``` |
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