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58 lines
1.5 KiB
58 lines
1.5 KiB
5 months ago
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import itertools
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import logging
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from torch.hub import _Faketqdm, tqdm
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# Disable progress bar by default, not in dynamo config because otherwise get a circular import
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disable_progress = True
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# Return all loggers that torchdynamo/torchinductor is responsible for
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def get_loggers():
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return [
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logging.getLogger("torch.fx.experimental.symbolic_shapes"),
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logging.getLogger("torch._dynamo"),
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logging.getLogger("torch._inductor"),
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]
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# Creates a logging function that logs a message with a step # prepended.
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# get_step_logger should be lazily called (i.e. at runtime, not at module-load time)
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# so that step numbers are initialized properly. e.g.:
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# @functools.lru_cache(None)
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# def _step_logger():
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# return get_step_logger(logging.getLogger(...))
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# def fn():
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# _step_logger()(logging.INFO, "msg")
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_step_counter = itertools.count(1)
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# Update num_steps if more phases are added: Dynamo, AOT, Backend
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# This is very inductor centric
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# _inductor.utils.has_triton() gives a circular import error here
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if not disable_progress:
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try:
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import triton # noqa: F401
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num_steps = 3
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except ImportError:
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num_steps = 2
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pbar = tqdm(total=num_steps, desc="torch.compile()", delay=0)
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def get_step_logger(logger):
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if not disable_progress:
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pbar.update(1)
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if not isinstance(pbar, _Faketqdm):
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pbar.set_postfix_str(f"{logger.name}")
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step = next(_step_counter)
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def log(level, msg, **kwargs):
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logger.log(level, "Step %s: %s", step, msg, **kwargs)
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return log
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