common.py

import sys
import os
import _current_dir_

# mark as root sources in pycharm
third_party_dir = os.path.dirname(os.path.realpath(__file__)) + '/third_party'
print('third_party_dir :', third_party_dir)
sys.path.append(third_party_dir)

from my_lib.other import *
from my_lib.draw import *
from my_lib.file import *

###################################################################################################3

import math
import numpy as np
import random
import time

import cv2

import pandas as pd
import json
import zipfile
from shutil import copyfile

from timeit import default_timer as timer
import itertools
import collections
from collections import OrderedDict
from collections import defaultdict
from glob import glob
from copy import deepcopy

import matplotlib
import matplotlib.pyplot as plt
matplotlib.use('TkAgg')
#matplotlib.use('WXAgg')
#matplotlib.use('Qt5Agg')
print('matplotlib.get_backend : ', matplotlib.get_backend())
#print(matplotlib.__version__)

from tqdm import tqdm
from print_dict import format_dict


## deep learning frame work #################################
if 1: # for pytorch
	import torch
	from torch.utils.data.dataset import Dataset
	from torch.utils.data import DataLoader
	from torch.utils.data.sampler import *
	import torch.nn as nn
	import torch.nn.functional as F
	import torch.optim as optim
	from torch.nn.parallel.data_parallel import data_parallel

def print_pytorch_env():
	text = ''
	text += '\tpytorch\n'
	text += '\t\ttorch.__version__              = %s\n' % torch.__version__
	text += '\t\ttorch.version.cuda             = %s\n' % torch.version.cuda
	text += '\t\ttorch.backends.cudnn.version() = %s\n' % torch.backends.cudnn.version()
	text += '\t\ttorch.cuda.device_count()      = %d\n' % torch.cuda.device_count()
	text += '\t\ttorch.cuda.get_device_properties() = %s\n' % str(torch.cuda.get_device_properties(0))[21:]
	text += '\n'
	print(text)

''' 
	pytorch
		torch.__version__              = 2.0.1+cu117
		torch.version.cuda             = 11.7
		torch.backends.cudnn.version() = 8500
		torch.cuda.device_count()      = 1
		torch.cuda.get_device_properties() = (name='NVIDIA TITAN X (Pascal)', major=6, minor=1, total_memory=12193MB, multi_processor_count=28)

	pytorch
		torch.__version__              = 2.3.0+cu121
		torch.version.cuda             = 12.1
		torch.backends.cudnn.version() = 8902
		torch.cuda.device_count()      = 2
		torch.cuda.get_device_properties() = (name='NVIDIA RTX 6000 Ada Generation', major=8, minor=9, total_memory=48622MB, multi_processor_count=142)

'''

'''
#https://stackoverflow.com/questions/31684375/automatically-create-file-requirements-txt
create requirements.txt

pip install pipreqs
pipreqs /path/to/project
'''
######################################################3


if __name__ == '__main__':
	print_pytorch_env()