mirror of
https://github.com/wassname/pytorch-lightning.git
synced 2026-09-21 13:20:08 +08:00
472f394788
* remove unnecessary pass statements * use isinstance for type checks * remove unnecessary else/elif after return * remove unnecessary return statements * move doc string to top * merge isinstance calls * remove unnecessary else/elif after raise * use list comprehension * do not use len without comparison * add missing shebang * revert isinstance check back to type broke tests, because bool is actually subclass of int * add missing period to doc string * remove unnecessary pass statements * use isinstance for type checks * remove unnecessary else/elif after return * remove unnecessary return statements * move doc string to top * merge isinstance calls * remove unnecessary else/elif after raise * use list comprehension * do not use len without comparison * add missing shebang * revert isinstance check back to type broke tests, because bool is actually subclass of int * add missing period to doc string * Fix default ckpt path when logger exists (#771) * rename logging -> loggers (#767) * move logging >> loggers * add warning * fix tests * logging alias * formatting * formatting * use isinstance for type checks * revert isinstance check back to type broke tests, because bool is actually subclass of int * add more detail to tbptt example (#755) * add more detail to tbptt example * warn user about new arg in training_step Co-authored-by: Vadim Bereznyuk <kuynzereb@gmail.com> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: Jeremy Jordan <13970565+jeremyjordan@users.noreply.github.com>
75 lines
1.9 KiB
Python
75 lines
1.9 KiB
Python
from abc import ABC
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from functools import wraps
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def rank_zero_only(fn):
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"""Decorate a logger method to run it only on the process with rank 0.
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:param fn: Function to decorate
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"""
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@wraps(fn)
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def wrapped_fn(self, *args, **kwargs):
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if self.rank == 0:
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fn(self, *args, **kwargs)
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return wrapped_fn
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class LightningLoggerBase(ABC):
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"""Base class for experiment loggers."""
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def __init__(self):
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self._rank = 0
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@property
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def experiment(self):
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raise NotImplementedError()
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def log_metrics(self, metrics, step):
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"""Record metrics.
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:param float metric: Dictionary with metric names as keys and measured quanties as values
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:param int|None step: Step number at which the metrics should be recorded
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"""
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raise NotImplementedError()
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def log_hyperparams(self, params):
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"""Record hyperparameters.
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:param params: argparse.Namespace containing the hyperparameters
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"""
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raise NotImplementedError()
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def save(self):
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"""Save log data."""
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def finalize(self, status):
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"""Do any processing that is necessary to finalize an experiment.
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:param status: Status that the experiment finished with (e.g. success, failed, aborted)
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"""
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def close(self):
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"""Do any cleanup that is necessary to close an experiment."""
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@property
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def rank(self):
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"""Process rank. In general, metrics should only be logged by the process with rank 0."""
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return self._rank
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@rank.setter
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def rank(self, value):
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"""Set the process rank."""
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self._rank = value
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@property
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def name(self):
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"""Return the experiment name."""
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raise NotImplementedError("Sub-classes must provide a name property")
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@property
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def version(self):
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"""Return the experiment version."""
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raise NotImplementedError("Sub-classes must provide a version property")
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