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import logging, os, psutil, torch, platform, cpuinfo, yaml #py-cpuinfo | |
from vouchervision.general_utils import get_datetime, print_main_warn, print_main_info | |
def start_logging(Dirs, cfg): | |
run_name = cfg['leafmachine']['project']['run_name'] | |
path_log = os.path.join(Dirs.path_log, '__'.join(['LM2-log',str(get_datetime()), run_name])+'.log') | |
# Disable default StreamHandler | |
logging.getLogger().handlers = [] | |
# create logger | |
logger = logging.getLogger('Hardware Components') | |
logger.setLevel(logging.DEBUG) | |
# create file handler and set level to debug | |
fh = logging.FileHandler(path_log) | |
fh.setLevel(logging.DEBUG) | |
# create console handler and set level to debug | |
ch = logging.StreamHandler() | |
ch.setLevel(logging.DEBUG) | |
# create formatter | |
formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(name)s - %(message)s') | |
# add formatter to handlers | |
fh.setFormatter(formatter) | |
ch.setFormatter(formatter) | |
# add handlers to logger | |
logger.addHandler(fh) | |
logger.addHandler(ch) | |
# Create a logger for the file handler | |
file_logger = logging.getLogger('file_logger') | |
file_logger.setLevel(logging.DEBUG) | |
file_formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s') | |
file_handler = logging.FileHandler(path_log) | |
file_handler.setLevel(logging.DEBUG) | |
file_handler.setFormatter(file_formatter) | |
file_logger.addHandler(file_handler) | |
# Disable propagation of log messages to the root logger | |
file_logger.propagate = False | |
# 'application' code | |
# logger.debug('debug message') | |
# logger.info('info message') | |
# logger.warning('warn message') | |
# logger.error('error message') | |
# logger.critical('critical message') | |
# Get CPU information | |
logger.info(f"CPU: {find_cpu_info()}") | |
# Get GPU information (using PyTorch) | |
if torch.cuda.is_available(): | |
num_gpus = torch.cuda.device_count() | |
if num_gpus == 1: | |
gpu = torch.cuda.get_device_properties(0) | |
logger.info(f"GPU: {gpu.name} ({gpu.total_memory // (1024 * 1024)} MB)") | |
else: | |
for i in range(num_gpus): | |
gpu = torch.cuda.get_device_properties(i) | |
logger.info(f"GPU {i}: {gpu.name} ({gpu.total_memory // (1024 * 1024)} MB)") | |
else: | |
logger.info("No GPU found") | |
logger.info("LeafMachine2 image cropping and embedding search will be extremely slow or not possible.") | |
print_main_info("No GPU found!") | |
print_main_info("LeafMachine2 image cropping and embedding search will be extremely slow or not possible.") | |
# Get memory information | |
mem_info = psutil.virtual_memory() | |
logger.info(f"Memory: {mem_info.total // (1024 * 1024)} MB") | |
logger.info(LM2_banner()) | |
logger.info(f"Config added to log file") | |
file_logger.info('Config:\n{}'.format(yaml.dump(cfg))) | |
return logger | |
def find_cpu_info(): | |
cpu_info = [] | |
cpu_info.append(platform.processor()) | |
try: | |
with open('/proc/cpuinfo') as f: | |
for line in f: | |
if line.startswith('model name'): | |
cpu_info.append(line.split(':')[1].strip()) | |
break | |
return ' / '.join(cpu_info) | |
except: | |
try: | |
info = cpuinfo.get_cpu_info() | |
cpu_info = [] | |
cpu_info.append(info['brand_raw']) | |
cpu_info.append(f"{info['hz_actual_friendly']}") | |
return ' / '.join(cpu_info) | |
except: | |
return "CPU: UNKNOWN" | |
def LM2_banner(): | |
logo = """ | |
_ __ __ __ _ _ ___ | |
| | / _| \/ | | | (_) |__ \ | |
| | ___ __ _| |_| \ / | __ _ ___| |__ _ _ __ ___ ) | | |
| | / _ \/ _` | _| |\/| |/ _` |/ __| '_ \| | '_ \ / _ \ / / | |
| |___| __/ (_| | | | | | | (_| | (__| | | | | | | | __// /_ | |
|______\___|\__,_|_| |_| |_|\__,_|\___|_| |_|_|_| |_|\___|____| | |
__ __ _ _| |_ __ ___ _ | |
\ \ / / | | |_ _| \ \ / (_) (_) | |
\ \ / /__ _ _ ___| |__ |_|_ _ _\ \ / / _ ___ _ ___ _ __ | |
\ \/ / _ \| | | |/ __| '_ \ / _ \ '__\ \/ / | / __| |/ _ \| '_ \ | |
\ / (_) | |_| | (__| | | | __/ | \ / | \__ \ | (_) | | | | | |
\/ \___/ \__,_|\___|_| |_|\___|_| \/ |_|___/_|\___/|_| |_|""" | |
return logo |