gensim/sim_runner.py

import numpy as np
import os
import IPython
from cliport import tasks
from cliport.dataset import RavensDataset
from cliport.environments.environment import Environment

import imageio

from pygments import highlight
from pygments.lexers import PythonLexer
from pygments.formatters import HtmlFormatter, TerminalFormatter
import gradio
import time
import random
import json
import traceback
from gensim.utils import (
    mkdir_if_missing,
    save_text,
    save_stat,
    compute_diversity_score_from_assets,
    add_to_txt
)
import pybullet as p

class SimulationRunner:
    """ the main class that runs simulation loop """
    def __init__(self, cfg, agent, critic, memory):
        self.cfg = cfg
        self.agent = agent
        self.critic = critic
        self.memory = memory
        self.log = ""

        # statistics
        self.syntax_pass_rate = 0
        self.runtime_pass_rate = 0
        self.env_pass_rate = 0
        self.curr_trials = 0

        self.prompt_folder = f"prompts/{cfg['prompt_folder']}"
        self.chat_log = memory.chat_log
        self.task_asset_logs = []

        # All the generated tasks in this run.
        # Different from the ones in online buffer that can load from offline.
        self.generated_task_assets = []
        self.generated_task_programs = []
        self.generated_task_names = []
        self.generated_tasks = []
        self.passed_tasks = [] # accepted ones

    def print_current_stats(self):
        """ print the current statistics of the simulation design """
        print("=========================================================")
        print(f"{self.cfg['prompt_folder']} Trial {self.curr_trials} SYNTAX_PASS_RATE: {(self.syntax_pass_rate / (self.curr_trials)) * 100:.1f}% RUNTIME_PASS_RATE: {(self.runtime_pass_rate / (self.curr_trials)) * 100:.1f}% ENV_PASS_RATE: {(self.env_pass_rate / (self.curr_trials)) * 100:.1f}%")
        print("=========================================================")

    def save_stats(self):
        """ save the final simulation statistics """
        self.diversity_score = compute_diversity_score_from_assets(self.task_asset_logs, self.curr_trials)
        save_stat(self.cfg, self.cfg['model_output_dir'], self.generated_tasks, self.syntax_pass_rate / (self.curr_trials),
                self.runtime_pass_rate / (self.data_pathcurr_trials), self.env_pass_rate / (self.curr_trials), self.diversity_score)
        print("Model Folder: ", self.cfg['model_output_dir'])
        print(f"Total {len(self.generated_tasks)} New Tasks:", [task['task-name'] for task in self.generated_tasks])
        try:
            print(f"Added {len(self.passed_tasks)}  Tasks:", self.passed_tasks)
        except:
            pass

    def example_task_creation(self):
        """ create the task through interactions of agent and critic """
        self.task_creation_pass = True
        mkdir_if_missing(self.cfg['model_output_dir'])

        try:
            start_time = time.time()

            self.generated_task = {'task-name': 'TASK_NAME_TEMPLATE', 'task-description': 'TASK_STRING_TEMPLATE', 'assets-used': ['ASSET_1', 'ASSET_2', Ellipsis]}
            print("generated_task\n", self.generated_task)
            yield "Task Generated ==>", "", None, None
            self.generated_asset = self.agent.propose_assets()
            # self.generated_asset = {}
            print("generated_asset\n", self.generated_asset)
            yield "Task Generated ==> Asset Generated ==> ", "", None, None
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> ", "", None, None
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> ", "", None, None

            online_code_buffer = {}
            for task_file in json.load(open(os.path.join('prompts/data', "generated_task_codes.json"))):
                if os.path.exists("cliport/generated_tasks/" + task_file):
                    online_code_buffer[task_file] = open("cliport/generated_tasks/" + task_file).read()

            random_task_file = random.sample(list(online_code_buffer.keys()), 1)[0]
            class_def = [line for line in online_code_buffer[random_task_file].split("\n") if line.startswith('class')]
            task_name = class_def[0]
            task_name = task_name[task_name.find("class "): task_name.rfind("(Task)")][6:]
            self.curr_task_name = self.generated_task_name = task_name

            self.generated_code = online_code_buffer[random_task_file]
            print("generated_code\n", self.generated_code)
            print("curr_task_name\n", self.curr_task_name)
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> Code Generated ==> ", "", self.generated_code, None

            self.generated_tasks.append(self.generated_task)
            self.generated_task_assets.append(self.generated_asset)
            self.generated_task_programs.append(self.generated_code)
            self.generated_task_names.append(self.generated_task_name)
        except:
            to_print = highlight(f"{str(traceback.format_exc())}", PythonLexer(), HtmlFormatter())
            print("Task Creation Exception:", highlight(f"{str(traceback.format_exc())}", PythonLexer(), TerminalFormatter()))
            self.log = to_print
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> Code Generation Failed", self.log, "", None
            self.task_creation_pass = False
            return

        # self.curr_task_name = self.generated_task['task-name']
        print("task creation time {:.3f}".format(time.time() - start_time))

    def task_creation(self):
        """ create the task through interactions of agent and critic """
        self.task_creation_pass = True
        mkdir_if_missing(self.cfg['model_output_dir'])

        try:
            start_time = time.time()
            self.generated_task = self.agent.propose_task(self.generated_task_names)

            # self.generated_task = {'task-name': 'TASK_NAME_TEMPLATE', 'task-description': 'TASK_STRING_TEMPLATE', 'assets-used': ['ASSET_1', 'ASSET_2', Ellipsis]}
            print("generated_task\n", self.generated_task)
            yield "Task Generated ==>", "", None, None
            self.generated_asset = self.agent.propose_assets()
            print("generated_asset\n", self.generated_asset)
            yield "Task Generated ==> Asset Generated ==> ", "", None, None
            self.agent.api_review()
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> ", "", None, None
            self.critic.error_review(self.generated_task)
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> ", "", None, None
            self.generated_code, self.curr_task_name = self.agent.implement_task()
            self.task_asset_logs.append(self.generated_task["assets-used"])
            self.generated_task_name = self.generated_task["task-name"]
            print("generated_code\n", self.generated_code)
            print("curr_task_name\n", self.curr_task_name)
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> Code Generated ==> ", self.log, self.generated_code, None

            self.generated_tasks.append(self.generated_task)
            self.generated_task_assets.append(self.generated_asset)
            self.generated_task_programs.append(self.generated_code)
            self.generated_task_names.append(self.generated_task_name)
        except:
            to_print = highlight(f"{str(traceback.format_exc())}", PythonLexer(), HtmlFormatter())
            print("Task Creation Exception:", highlight(f"{str(traceback.format_exc())}", PythonLexer(), TerminalFormatter()))
            self.log = to_print
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> Code Generation Failed", self.log, "", None
            self.task_creation_pass = False
            return

        # self.curr_task_name = self.generated_task['task-name']
        print("task creation time {:.3f}".format(time.time() - start_time))


    def setup_env(self):
        """ build the new task"""
        env = Environment(
                self.cfg['assets_root'],
                disp=self.cfg['disp'],
                shared_memory=self.cfg['shared_memory'],
                hz=480,
                record_cfg=self.cfg['record']
            )

        task = eval(self.curr_task_name)()
        task.mode = self.cfg['mode']
        record = self.cfg['record']['save_video']
        save_data = self.cfg['save_data']

        # Initialize scripted oracle agent and dataset.
        expert = task.oracle(env)
        self.cfg['task'] = self.generated_task["task-name"]
        data_path = os.path.join(self.cfg['data_dir'], "{}-{}".format(self.generated_task["task-name"], task.mode))
        dataset = RavensDataset(data_path, self.cfg, n_demos=0, augment=False)
        print(f"Saving to: {data_path}")
        print(f"Mode: {task.mode}")

        # Start video recording
        if record:
            env.start_rec(f'{dataset.n_episodes+1:06d}')

        return task, dataset, env, expert

    def run_one_episode(self, dataset, expert, env, task, episode, seed):
        """ run the new task for one episode """
        add_to_txt(
                self.chat_log, f"================= TRIAL: {self.curr_trials}", with_print=True)
        record = self.cfg['record']['save_video']
        np.random.seed(seed)
        random.seed(seed)
        print('Oracle demo: {}/{} | Seed: {}'.format(dataset.n_episodes + 1, self.cfg['n'], seed))
        env.set_task(task)
        obs = env.reset()

        info = env.info
        reward = 0
        total_reward = 0

        # Rollout expert policy
        for _ in range(task.max_steps):
            act = expert.act(obs, info)
            episode.append((obs, act, reward, info))
            lang_goal = info['lang_goal']
            obs, reward, done, info = env.step(act)
            total_reward += reward
            print(f'Total Reward: {total_reward:.3f} | Done: {done} | Goal: {lang_goal}')
            if done:
                break

        episode.append((obs, None, reward, info))
        return total_reward

    def simulate_task(self):
        """ simulate the created task and save demonstrations """
        total_cnt = 0.
        reset_success_cnt = 0.
        env_success_cnt = 0.
        seed = 123
        self.curr_trials += 1
        
        if p.isConnected():
            p.disconnect()
        
        if not self.task_creation_pass:
            print("task creation failure => count as syntax exceptions.")
            return

        # Check syntax and compilation-time error
        try:
            exec(self.generated_code, globals())
            task, dataset, env, expert = self.setup_env()
            self.syntax_pass_rate += 1

        except:
            to_print = highlight(f"{str(traceback.format_exc())}", PythonLexer(), HtmlFormatter())
            save_text(self.cfg['model_output_dir'], self.generated_task_name + '_error', str(traceback.format_exc()))
            print("========================================================")
            print("Syntax Exception:", highlight(f"{str(traceback.format_exc())}", PythonLexer(), TerminalFormatter()))
            self.log = to_print

            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> Code Generated ==> Code Syntax Parse Failed", self.log, self.generated_code, None
            return

        try:
            # Collect environment and collect data from oracle demonstrations.
            env.generated_code = self.generated_code
            # Set seeds.
            episode = []


            """ run the new task for one episode """
            add_to_txt(
                self.chat_log, f"================= TRIAL: {self.curr_trials}", with_print=True)
            np.random.seed(seed)
            random.seed(seed)
            print('Oracle demo: {}/{} | Seed: {}'.format(dataset.n_episodes + 1, self.cfg['n'], seed))
            env.set_task(task)
            obs = env.reset()

            info = env.info
            reward = 0
            total_reward = 0
            # Rollout expert policy

            start_time = time.time()
            print("start sim")
            for i in range(task.max_steps):
                act = expert.act(obs, info)
                episode.append((obs, act, reward, info))
                lang_goal = info['lang_goal']

                env.step(act)

                obs, reward, done, info = env.cur_obs, env.cur_reward, env.cur_done, env.cur_info
                total_reward += reward
                print(f'Total Reward: {total_reward:.3f} | Done: {done} | Goal: {lang_goal}')

                if done:
                    break

            end_time = time.time()
            print("end sim, time used = ", end_time - start_time)

            if not os.path.exists(env.record_cfg['save_video_path']):
                os.mkdir(env.record_cfg['save_video_path'])
            self.video_path = os.path.join(env.record_cfg['save_video_path'], "123.mp4")
            video_writer = imageio.get_writer(self.video_path,
                                              fps=env.record_cfg['fps'],
                                              format='FFMPEG',
                                              codec='h264', )
            print(f"has {len(env.curr_video)} frames to save")
            for color in env.curr_video:
                video_writer.append_data(color)
            video_writer.close()
            print("save video to ", self.video_path)

            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> Code Generated ==> Simulation Running completed", self.log, self.generated_code, self.video_path
            episode.append((obs, None, reward, info))


            # reset_success_cnt += 1
            # env_success_cnt += total_reward > 0.99
            #
            # self.runtime_pass_rate += 1
            print("Runtime Test Pass!")
        except:
            to_print = highlight(f"{str(traceback.format_exc())}", PythonLexer(), HtmlFormatter())
            save_text(self.cfg['model_output_dir'], self.generated_task_name + '_error', str(traceback.format_exc()))
            print("========================================================")
            print("Runtime Exception:", highlight(f"{str(traceback.format_exc())}", PythonLexer(), TerminalFormatter()))
            self.log = to_print
            yield "Task Generated ==> Asset Generated ==> API Reviewed ==> Error Reviewed ==> Code Generated ==> Simulation Running Failed", self.log, self.generated_code, None
        self.memory.save_run(self.generated_task)