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fix changelog (#1864)
* fix chlog * test for #1729 * hist * update * Document use case of passing test dataloaders to Trainer.test() (#1992) * Issue 1990 Doc patch. * Codeblock directive. * Update to reflect current state of pytorch-lightning * Final grammar cleaning. I hope these commits are squashed. * Apply suggestions from code review * Apply suggestions from code review Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> Co-authored-by: authman <uapatira@gmail.com> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
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@@ -1,6 +1,6 @@
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Test set
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========
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Lightning forces the user to run the test set separately to make sure it isn't evaluated by mistake
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Lightning forces the user to run the test set separately to make sure it isn't evaluated by mistake.
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Test after fit
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@@ -15,6 +15,7 @@ To run the test set after training completes, use this method
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# run test set
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trainer.test()
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Test pre-trained model
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----------------------
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To run the test set on a pre-trained model, use this method.
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@@ -34,4 +35,22 @@ To run the test set on a pre-trained model, use this method.
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trainer.test(model)
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In this case, the options you pass to trainer will be used when
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running the test set (ie: 16-bit, dp, ddp, etc...)
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running the test set (ie: 16-bit, dp, ddp, etc...)
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Test with additional data loaders
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---------------------------------
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You can still run inference on a test set even if the `test_dataloader` method hasn't been
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defined within your :class:`~pytorch_lightning.core.LightningModule` instance. This would be the case when your test data
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is not available at the time your model was declared.
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.. code-block:: python
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# setup your data loader
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test = DataLoader(...)
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# test (pass in the loader)
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trainer.test(test_dataloaders=test)
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You can either pass in a single dataloader or a list of them. This optional named
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parameter can be used in conjunction with any of the above use cases.
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