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Deprecate/compute on step #792
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Codecov Report
@@ Coverage Diff @@
## master #792 +/- ##
=====================================
- Coverage 95% 95% -0%
=====================================
Files 166 166
Lines 6795 6796 +1
=====================================
- Hits 6469 6460 -9
- Misses 326 336 +10 |
…hLightning/metrics into deprecate/compute_on_step
@SkafteNicki mind checking the last two failing tests? |
|
@SkafteNicki why was Thanks |
Agree with @Alec-Stashevsky 's comment. If I am reading the code correctly: def forward(self, *args: Any, **kwargs: Any) -> Any:
"""Automatically calls ``update()``.
Returns the metric value over inputs if ``compute_on_step`` is True.
"""
# add current step
if self._is_synced:
raise TorchMetricsUserError(
"The Metric shouldn't be synced when performing ``update``. "
"HINT: Did you forget to call ``unsync`` ?."
)
# global accumulation
self.update(*args, **kwargs)
if self.compute_on_step:
self._to_sync = self.dist_sync_on_step
# skip restore cache operation from compute as cache is stored below.
self._should_unsync = False
# save context before switch
cache = {attr: getattr(self, attr) for attr in self._defaults}
# call reset, update, compute, on single batch
self._enable_grad = True # allow grads for batch computation
self.reset()
self.update(*args, **kwargs)
self._forward_cache = self.compute()
# restore context
for attr, val in cache.items():
setattr(self, attr, val)
self._is_synced = False
self._should_unsync = True
self._to_sync = True
self._computed = None
self._enable_grad = False
return self._forward_cache This used to be the |
Hi @Alec-Stashevsky metric = Metric(compute_on_step=False)
metric(input) you should instead just do metric = Metric()
metric.update(input) @fierval the change in 0.8 just have the effect that |
What does this PR do?
Fixes #789
Deprecates
compute_on_step
argument.Before submitting
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