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1. Rewrite logger message

Browse source 
2. fix import
This commit is contained in:
Yizhou Chi 2024-09-02 10:21:30 +08:00
parent 16d1bf0da0
commit 27bbc927b0
3 changed files with 25 additions and 29 deletions
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50
expo/MCTS.py
View file

@ -3,7 +3,7 @@ import math
import os
import pandas as pd
from expo.research_assistant import ResearchAssistant
from exp_optimizer.expo.insights.instruction_generator import InstructionGenerator
from expo.insights.instruction_generator import InstructionGenerator
from expo.dataset import get_split_dataset_path, generate_task_requirement
from expo.evaluation.evaluation import evaluate_score
from expo.utils import mcts_logger, load_execute_notebook, get_exp_pool_path
@ -135,13 +135,13 @@ class Node():
role.start_task_id = self.state['start_task_id']
role.state_saved = False
role.change_next_instruction(self.action)
mcts_logger.log("MCTS", f"保存新的role: {role.node_id}")
mcts_logger.log("MCTS", f"Saving new role: {role.node_id}")
role.save_state(static_save=True)
async def expand(self, max_children):
if self.is_fully_expanded():
return
insight_geneartor = InsightGenerator()
insight_geneartor = InstructionGenerator()
role = self.load_role()
original_instruction = role.get_next_instruction()
insights = await insight_geneartor.generate_new_instructions(task_id=role.start_task_id + 1,
@ -224,7 +224,7 @@ class MCTS():
def select(self, node: Node):
node = self.best_child()
mcts_logger.log("MCTS", f"选择的叶子节点id: {node.id}")
mcts_logger.log("MCTS", f"Selected node id: {node.id}")
return node
def best_child(self):
@ -245,9 +245,11 @@ class MCTS():
async def simulate(self, node : Node, role=None):
"Returns the reward for a random simulation (to completion) of `node`"
mcts_logger.log("MCTS", f"Start simulating node {node.id}:")
while node.children:
node = random.choice(node.children)
reward = await node.run_node(role)
reward = await node.run_node(role)
mcts_logger.log("MCTS", f"Simulated node's reward: {reward}")
return reward
@ -292,7 +294,7 @@ class MCTS():
if load_tree:
tree_loaded = self.load_tree()
mcts_logger.log("MCTS", f"Number of simulations: {self.get_num_simulations()}")
mcts_logger.log("MCTS", f"Tree loaded: {tree_loaded}")
if not tree_loaded:
rollouts -= 2
@ -301,41 +303,36 @@ class MCTS():
self.children[root] = []
reward = await self.simulate(root, role)
self.backpropagate(root, reward)
mcts_logger.log("MCTS", f"Root node's value: {reward}")
children = await self.expand(root)
#目前是随机选择1个，后续可以改成多个
first_leaf = random.choice(children)
mcts_logger.log("MCTS", f"随机选择的叶子节点id: {first_leaf.id}")
reward = await self.simulate(first_leaf)
mcts_logger.log("MCTS", f"模拟完毕的叶子节点的Normalized score: {reward}")
self.backpropagate(first_leaf, reward)
else:
root = self.root_node
# 后续迭代：使用UCT进行选择，expand并模拟和反向传播
for _ in range(rollouts): # 迭代次数
mcts_logger.log("MCTS", f"开始第{_+1}次迭代")
leaf = self.select(root)
if leaf.is_terminal():
if leaf.raw_value == 0:
reward = await self.simulate(leaf)
for _ in range(rollouts): # number of rollouts
mcts_logger.log("MCTS", f"Start the next rollout {_+1}")
node = self.select(root)
if node.is_terminal():
if node.raw_value == 0:
reward = await self.simulate(node)
else:
reward = {"test_score": leaf.raw_value, "score": leaf.value}
mcts_logger.log("MCTS", f"终止节点的得分为: {reward}")
self.backpropagate(leaf, reward)
reward = {"test_score": node.raw_value, "score": node.value}
mcts_logger.log("MCTS", f"Terminal node's reward: {reward}")
self.backpropagate(node, reward)
else:
if leaf.visited > 0:
children = await self.expand(leaf)
leaf = random.choice(children)
mcts_logger.log("MCTS", f"随机选择的叶子节点id: {leaf.id}")
reward = await self.simulate(leaf)
mcts_logger.log("MCTS", f"模拟完毕的叶子节点{leaf.id}的Normalized score: {reward}")
self.backpropagate(leaf, reward)
if node.visited > 0:
children = await self.expand(node)
node = random.choice(children)
reward = await self.simulate(node)
self.backpropagate(node, reward)
return self.best_path(root)
def load_tree(self):
def load_children_node(node):
mcts_logger.log("MCTS", f"加载节点{node.id}的子节点：{node.children}")
mcts_logger.log("MCTS", f"Load node {node.id}'s child: {node.children}")
if node.is_terminal() or not node.children:
return
for child in node.children:
@ -351,6 +348,5 @@ class MCTS():
self.children[self.root_node] = self.root_node.children
load_children_node(self.root_node)
if self.children:
mcts_logger.log("MCTS", "成功加载树")
return True
return False

2
expo/experimenter/aug.py
View file

@ -2,7 +2,7 @@ from experimenter import Experimenter
from expo.MCTS import create_initial_state
from expo.dataset import generate_task_requirement
from expo.utils import mcts_logger, load_execute_notebook, get_exp_pool_path
from exp_optimizer.expo.insights.instruction_generator import InstructionGenerator
from expo.insights.instruction_generator import InstructionGenerator
from expo.research_assistant import ResearchAssistant
EXPS_PROMPT = """

2
expo/run_exp_augmentation.py
View file

@ -3,7 +3,7 @@ from expo.research_assistant import ResearchAssistant
import asyncio
from expo.utils import DATA_CONFIG, get_exp_pool_path
from expo.dataset import generate_task_requirement
from exp_optimizer.expo.insights.instruction_generator import InstructionGenerator
from expo.insights.instruction_generator import InstructionGenerator
from expo.MCTS import create_initial_state
from expo.evaluation.evaluation import evaluate_score
import json