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Merge pull request #38 from reginabarzilaygroup/v1.2.2_dev
V1.2.2 dev
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,72 @@ | ||
| import itertools | ||
| import os | ||
| from typing import Union | ||
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| import torch | ||
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| def get_default_device(): | ||
| if torch.cuda.is_available(): | ||
| return get_most_free_gpu() | ||
| elif torch.backends.mps.is_available(): | ||
| # Not all operations implemented in MPS yet | ||
| use_mps = os.environ.get("PYTORCH_ENABLE_MPS_FALLBACK", "0") == "1" | ||
| if use_mps: | ||
| return torch.device('mps') | ||
| else: | ||
| return torch.device('cpu') | ||
| else: | ||
| return torch.device('cpu') | ||
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| def get_available_devices(num_devices=None, max_devices=None): | ||
| device = get_default_device() | ||
| if device.type == "cuda": | ||
| num_gpus = torch.cuda.device_count() | ||
| if max_devices is not None: | ||
| num_gpus = min(num_gpus, max_devices) | ||
| gpu_list = [get_device(i) for i in range(num_gpus)] | ||
| if num_devices is not None: | ||
| cycle_gpu_list = itertools.cycle(gpu_list) | ||
| gpu_list = [next(cycle_gpu_list) for _ in range(num_devices)] | ||
| return gpu_list | ||
| else: | ||
| num_devices = num_devices if num_devices else torch.multiprocessing.cpu_count() | ||
| num_devices = min(num_devices, max_devices) if max_devices is not None else num_devices | ||
| return [device]*num_devices | ||
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| def get_device(gpu_id: int): | ||
| if gpu_id is not None and torch.cuda.is_available() and gpu_id < torch.cuda.device_count(): | ||
| return torch.device(f'cuda:{gpu_id}') | ||
| else: | ||
| return None | ||
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| def get_device_mem_info(device: Union[int, torch.device]): | ||
| if not torch.cuda.is_available(): | ||
| return None | ||
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| free_mem, total_mem = torch.cuda.mem_get_info(device=device) | ||
| return free_mem, total_mem | ||
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| def get_most_free_gpu(): | ||
| """ | ||
| Get the GPU with the most free memory | ||
| If system has no GPUs (or CUDA not available), return None | ||
| """ | ||
| if not torch.cuda.is_available(): | ||
| return None | ||
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| num_gpus = torch.cuda.device_count() | ||
| if num_gpus == 0: | ||
| return None | ||
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| most_free_idx, most_free_val = -1, -1 | ||
| for i in range(num_gpus): | ||
| free_mem, total_mem = get_device_mem_info(i) | ||
| if free_mem > most_free_val: | ||
| most_free_idx, most_free_val = i, free_mem | ||
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| return torch.device(f'cuda:{most_free_idx}') |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,68 @@ | ||
| import logging | ||
| import os | ||
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| LOGGER_NAME = "sybil" | ||
| LOGLEVEL_KEY = "LOG_LEVEL" | ||
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| def _get_formatter(loglevel="INFO"): | ||
| warn_fmt = "[%(asctime)s] %(levelname)s -%(message)s" | ||
| debug_fmt = "[%(asctime)s] [%(filename)s:%(lineno)d] %(levelname)s - %(message)s" | ||
| fmt = debug_fmt if loglevel.upper() in {"DEBUG"} else warn_fmt | ||
| return logging.Formatter( | ||
| fmt=fmt, | ||
| datefmt="%Y-%b-%d %H:%M:%S %Z", | ||
| ) | ||
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| def remove_all_handlers(logger): | ||
| while logger.hasHandlers(): | ||
| logger.removeHandler(logger.handlers[0]) | ||
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| def configure_logger(loglevel=None, logger_name=LOGGER_NAME, logfile=None): | ||
| """Do basic logger configuration and set our main logger""" | ||
|
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| # Set as environment variable so other processes can retrieve it | ||
| if loglevel is None: | ||
| loglevel = os.environ.get(LOGLEVEL_KEY, "WARNING") | ||
| else: | ||
| os.environ[LOGLEVEL_KEY] = loglevel | ||
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| logger = logging.getLogger(logger_name) | ||
| logger.setLevel(loglevel) | ||
| remove_all_handlers(logger) | ||
| logger.propagate = False | ||
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| formatter = _get_formatter(loglevel) | ||
| def _prep_handler(handler): | ||
| for ex_handler in logger.handlers: | ||
| if type(ex_handler) == type(handler): | ||
| # Remove old handler, don't want to double-handle | ||
| logger.removeHandler(ex_handler) | ||
| handler.setLevel(loglevel) | ||
| handler.setFormatter(formatter) | ||
| logger.addHandler(handler) | ||
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| sh = logging.StreamHandler() | ||
| _prep_handler(sh) | ||
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| if logfile is not None: | ||
| fh = logging.FileHandler(logfile, mode="a") | ||
| _prep_handler(fh) | ||
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| return logger | ||
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| def get_logger(base_name=LOGGER_NAME): | ||
| """ | ||
| Return a logger. | ||
| Use a different logger in each subprocess, though they should all have the same log level. | ||
| """ | ||
| pid = os.getpid() | ||
| logger_name = f"{base_name}-process-{pid}" | ||
| logger = logging.getLogger(logger_name) | ||
| if not logger.hasHandlers(): | ||
| configure_logger(logger_name=logger_name) | ||
| return logger |