How to use _track_progress method in lisa

Best Python code snippet using lisa_python

parser.py

Source:parser.py Github

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...29 self.progress = 030 self.network = []31 self.process_pool = Pool(processes=4)32 self._count_atoms()33 self._track_progress()34 def _count_atoms(self):35 with open(self.filename,'r') as infile:36 try:37 self._atoms_number = int(infile.readline())38 except:39 print("Could not read the number of atoms,please make sure the .xyz file has the correct format.")40 exit()41 def _make_last_movie_frame(self):42 os.system("rm last_frame.xyz")43 os.system("rm last.xyz")44 cmd = "tail -"+str(self._atoms_number)+" fibro.xyz >> last_frame.xyz "45 with open("last_frame.xyz",'w') as outfile:46 outfile.write("{}\nAtoms. Timestep: 0\n".format(self._atoms_number))47 os.system(cmd)48 cmd = "cat last_frame.xyz last_frame.xyz >> last.xyz"49 os.system(cmd)50 def _track_progress(self):51 if os.path.exists("log.lammps"):52 os.system("tail -1 log.lammps >> progress.txt")53 with open("progress.txt") as infile:54 try:55 self.progress = int(re.findall(r'\d+', infile.readline())[0])56 except:57 print("Could not find the last frame, run the simulation for longer!")58 os.system("rm progress.txt")59 else:60 print("Warning: Could not find the LAMMPS log file.")61 def go_through_frames(self,filename):62 frame_index = 063 types = []64 xs = []; ys = []; zs = []65 jobs = []66 fibril_analyser = FibrilAnalyser()67 with open(filename, 'r') as infile:68 for item in infile:69 if len(item.split()) == 1 and types:70 frame_index += 171 types = np.asarray(types);xs=np.asarray(xs);ys=np.asarray(ys);zs=np.asarray(zs)72 if args.verbose and not args.last_frame:73 print("Processing frame......{}".format(frame_index))74 self.process_pool.apply_async(fibril_analyser.analyse_fibril_distribution,75 args=(args.nematic_cutoff,args.radial_cutoff,types,xs,ys,zs))76 types=[];xs=[];ys=[];zs=[]77 if len(item.split()) > 3:78 atom_type,x,y,z=item.split()79 atom_type = str(atom_type)80 x, y, z = float(x), float(y), float(z)81 types.append(int(atom_type))82 xs.append(x);ys.append(y);zs.append(z)83 self.process_pool.close()84 self.process_pool.join()85if __name__ == "__main__":86 parser = Parser(args.movie_name)87 parser._count_atoms()88 parser._track_progress()89 if args.last_frame:90 print("analysing last frame")91 parser._make_last_movie_frame()92 parser.go_through_frames("last.xyz")93 else:94 parser.go_through_frames(args.movie_name)95 print("Successfully analysed all frames!")...

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rollout_saver.py

Source:rollout_saver.py Github

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1import shelve2import argparse3import json4import numpy as np5import os6import os.path as osp7import torch8from pathlib import Path9from typing import List, Optional, Tuple, Union, Dict10from collections import defaultdict11from grf_imitation.infrastructure.datas import Batch, convert_batch_to_dict12from grf_imitation.infrastructure.utils import utils13class RolloutSaver:14 """15 Utility class for storing rollouts.16 Each rollout is stored with a key based on the episode number (0-indexed),17 and the number of episodes is stored with the key "num_episodes",18 so to load the shelf file, use something like:19 with shelve.open('rollouts.pkl') as rollouts:20 for episode_id in range(rollouts["episodes"]):21 rollout = rollouts[str(episode_id)]22 If outfile is None, this class does nothing.23 """24 def __init__(25 self,26 exp_dir=None,27 num_steps=None,28 num_episodes=None,29 track_progress=False,30 save_info=False,31 ):32 self._exp_dir = exp_dir33 self._track_progress = track_progress34 self._outfile = None # exp_dir/rollouts/rollouts35 self._progressfile = None # exp_dir/rollouts/__progress_rollouts36 self._shelf = None37 self._episodes = 038 self._steps = 039 self._num_episodes = num_episodes40 self._num_steps = num_steps41 self._save_info = save_info42 if self._exp_dir:43 self._rollout_dir = osp.join(self._exp_dir, 'evaluation')44 os.makedirs(self._rollout_dir, exist_ok=True)45 self._outfile = osp.join(self._rollout_dir, 'rollouts') 46 def _get_tmp_progress_filename(self):47 outpath = Path(self._outfile)48 return outpath.parent / ("progress_" + outpath.name)49 @property50 def outfile(self):51 return self._outfile52 @property53 def is_invalid(self):54 return self._exp_dir is None55 def __enter__(self):56 if self._outfile:57 self._shelf = shelve.open(self._outfile)58 if self._track_progress:59 self._progressfile = self._get_tmp_progress_filename().open(mode='w')60 return self61 62 def __exit__(self, type, value, traceback):63 if self._shelf:64 # Close the shelf file, and store the number of episodes for ease65 self._shelf['episodes'] = self._episodes66 self._shelf.close()67 if self._track_progress:68 # Remove the temp progress file:69 # self._get_tmp_progress_filename().unlink()70 self._progressfile.close()71 def _get_progress(self):72 if self._num_episodes:73 return f"{self._episodes} / {self._num_episodes} episodes completed"74 elif self._num_steps:75 return f"{self._steps} / {self._num_steps} steps completed"76 else:77 return f"{self._episodes} episodes completed"78 def store(self, batch: Batch):79 if self._outfile:80 # don't save img_obs to save space81 self._shelf[str(self._episodes)] = convert_batch_to_dict(batch, ignore_keys=['img_obs'])82 self._episodes += 183 if self._progressfile:84 log_str = f"episode reward: {batch.rew[:, :4].sum() // 4}\t" + self._get_progress() + "\n"85 print(log_str)86 self._progressfile.write(log_str)87 self._progressfile.flush()88 @property89 def rollout_dir(self):...

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