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import functools |
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import logging |
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import os |
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from .state import PartialState |
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class MultiProcessAdapter(logging.LoggerAdapter): |
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""" |
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An adapter to assist with logging in multiprocess. |
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`log` takes in an additional `main_process_only` kwarg, which dictates whether it should be called on all processes |
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or only the main executed one. Default is `main_process_only=True`. |
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Does not require an `Accelerator` object to be created first. |
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""" |
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@staticmethod |
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def _should_log(main_process_only): |
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"Check if log should be performed" |
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state = PartialState() |
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return not main_process_only or (main_process_only and state.is_main_process) |
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def log(self, level, msg, *args, **kwargs): |
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""" |
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Delegates logger call after checking if we should log. |
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Accepts a new kwarg of `main_process_only`, which will dictate whether it will be logged across all processes |
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or only the main executed one. Default is `True` if not passed |
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Also accepts "in_order", which if `True` makes the processes log one by one, in order. This is much easier to |
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read, but comes at the cost of sometimes needing to wait for the other processes. Default is `False` to not |
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break with the previous behavior. |
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`in_order` is ignored if `main_process_only` is passed. |
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""" |
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if PartialState._shared_state == {}: |
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raise RuntimeError( |
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"You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility." |
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) |
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main_process_only = kwargs.pop("main_process_only", True) |
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in_order = kwargs.pop("in_order", False) |
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if self.isEnabledFor(level): |
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if self._should_log(main_process_only): |
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msg, kwargs = self.process(msg, kwargs) |
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self.logger.log(level, msg, *args, **kwargs) |
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elif in_order: |
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state = PartialState() |
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for i in range(state.num_processes): |
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if i == state.process_index: |
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msg, kwargs = self.process(msg, kwargs) |
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self.logger.log(level, msg, *args, **kwargs) |
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state.wait_for_everyone() |
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@functools.lru_cache(None) |
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def warning_once(self, *args, **kwargs): |
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""" |
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This method is identical to `logger.warning()`, but will emit the warning with the same message only once |
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Note: The cache is for the function arguments, so 2 different callers using the same arguments will hit the |
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cache. The assumption here is that all warning messages are unique across the code. If they aren't then need to |
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switch to another type of cache that includes the caller frame information in the hashing function. |
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""" |
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self.warning(*args, **kwargs) |
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def get_logger(name: str, log_level: str = None): |
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""" |
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Returns a `logging.Logger` for `name` that can handle multiprocessing. |
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If a log should be called on all processes, pass `main_process_only=False` If a log should be called on all |
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processes and in order, also pass `in_order=True` |
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Args: |
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name (`str`): |
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The name for the logger, such as `__file__` |
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log_level (`str`, *optional*): |
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The log level to use. If not passed, will default to the `LOG_LEVEL` environment variable, or `INFO` if not |
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Example: |
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```python |
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>>> from accelerate.logging import get_logger |
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>>> from accelerate import Accelerator |
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>>> logger = get_logger(__name__) |
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>>> accelerator = Accelerator() |
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>>> logger.info("My log", main_process_only=False) |
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>>> logger.debug("My log", main_process_only=True) |
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>>> logger = get_logger(__name__, log_level="DEBUG") |
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>>> logger.info("My log") |
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>>> logger.debug("My second log") |
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>>> array = ["a", "b", "c", "d"] |
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>>> letter_at_rank = array[accelerator.process_index] |
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>>> logger.info(letter_at_rank, in_order=True) |
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``` |
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""" |
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if log_level is None: |
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log_level = os.environ.get("ACCELERATE_LOG_LEVEL", None) |
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logger = logging.getLogger(name) |
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if log_level is not None: |
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logger.setLevel(log_level.upper()) |
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logger.root.setLevel(log_level.upper()) |
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return MultiProcessAdapter(logger, {}) |
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