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132 lines
4.1 KiB
Python
132 lines
4.1 KiB
Python
#!/usr/bin/env python3
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# -*- coding:utf-8 -*-
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import torch
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import datetime
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import logging
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import logging.handlers
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import os
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import sys
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import requests
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from pilot.configs.model_config import LOGDIR
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server_error_msg = "**NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.**"
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handler = None
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def get_gpu_memory(max_gpus=None):
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gpu_memory = []
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num_gpus = (
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torch.cuda.device_count()
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if max_gpus is None
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else min(max_gpus, torch.cuda.device_count())
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)
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for gpu_id in range(num_gpus):
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with torch.cuda.device(gpu_id):
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device = torch.cuda.current_device()
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gpu_properties = torch.cuda.get_device_properties(device)
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total_memory = gpu_properties.total_memory / (1024 ** 3)
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allocated_memory = torch.cuda.memory_allocated() / (1024 ** 3)
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available_memory = total_memory - allocated_memory
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gpu_memory.append(available_memory)
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return gpu_memory
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def build_logger(logger_name, logger_filename):
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global handler
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formatter = logging.Formatter(
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fmt="%(asctime)s | %(levelname)s | %(name)s | %(message)s",
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datefmt="%Y-%m-%d %H:%M:%S",
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)
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# Set the format of root handlers
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if not logging.getLogger().handlers:
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logging.basicConfig(level=logging.INFO, encoding='utf-8')
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logging.getLogger().handlers[0].setFormatter(formatter)
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# Redirect stdout and stderr to loggers
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stdout_logger = logging.getLogger("stdout")
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stdout_logger.setLevel(logging.INFO)
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sl = StreamToLogger(stdout_logger, logging.INFO)
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sys.stdout = sl
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stderr_logger = logging.getLogger("stderr")
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stderr_logger.setLevel(logging.ERROR)
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sl = StreamToLogger(stderr_logger, logging.ERROR)
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sys.stderr = sl
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# Get logger
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logger = logging.getLogger(logger_name)
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logger.setLevel(logging.INFO)
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# Add a file handler for all loggers
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if handler is None:
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os.makedirs(LOGDIR, exist_ok=True)
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filename = os.path.join(LOGDIR, logger_filename)
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handler = logging.handlers.TimedRotatingFileHandler(
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filename, when='D', utc=True)
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handler.setFormatter(formatter)
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for name, item in logging.root.manager.loggerDict.items():
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if isinstance(item, logging.Logger):
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item.addHandler(handler)
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return logger
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class StreamToLogger(object):
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"""
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Fake file-like stream object that redirects writes to a logger instance.
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"""
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def __init__(self, logger, log_level=logging.INFO):
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self.terminal = sys.stdout
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self.logger = logger
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self.log_level = log_level
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self.linebuf = ''
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def __getattr__(self, attr):
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return getattr(self.terminal, attr)
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def write(self, buf):
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temp_linebuf = self.linebuf + buf
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self.linebuf = ''
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for line in temp_linebuf.splitlines(True):
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# From the io.TextIOWrapper docs:
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# On output, if newline is None, any '\n' characters written
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# are translated to the system default line separator.
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# By default sys.stdout.write() expects '\n' newlines and then
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# translates them so this is still cross platform.
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if line[-1] == '\n':
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encoded_message = line.encode('utf-8', 'ignore').decode('utf-8')
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self.logger.log(self.log_level, encoded_message.rstrip())
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else:
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self.linebuf += line
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def flush(self):
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if self.linebuf != '':
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encoded_message = self.linebuf.encode('utf-8', 'ignore').decode('utf-8')
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self.logger.log(self.log_level, encoded_message.rstrip())
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self.linebuf = ''
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def disable_torch_init():
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"""
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Disable the redundant torch default initialization to accelerate model creation.
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"""
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import torch
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setattr(torch.nn.Linear, "reset_parameters", lambda self: None)
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setattr(torch.nn.LayerNorm, "reset_parameters", lambda self: None)
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def pretty_print_semaphore(semaphore):
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if semaphore is None:
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return "None"
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return f"Semaphore(value={semaphore._value}, locked={semaphore.locked()})"
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