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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
class SanitizingFileHandler(logging.FileHandler):
def __init__(self, filename, mode='a', encoding=None, delay=False):
super().__init__(filename, mode, encoding, delay)
def emit(self, record):
try:
record.msg = record.msg.encode('utf-8', 'replace').decode('utf-8')
except Exception as e:
record.msg = f'[Error encoding text: {e}]'
super().emit(record)
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 custom sanitizing file handler and set level to debug
sanitizing_fh = SanitizingFileHandler(path_log, encoding='utf-8')
sanitizing_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
sanitizing_fh.setFormatter(formatter)
ch.setFormatter(formatter)
# add handlers to logger
logger.addHandler(sanitizing_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 |