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https://github.com/wassname/pytorch-lightning.git
synced 2026-09-09 11:32:07 +08:00
@@ -9,7 +9,7 @@ Notice a few things.
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1. It's the SAME code.
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2. The PyTorch code IS NOT abstracted - just organized.
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3. All the other code that didn't go in the LightningModule has been automated for you by the trainer
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3. All the other code that not in the LightningModule has been automated for you by the trainer
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.. code-block:: python
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net = Net()
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@@ -101,7 +101,7 @@ Which you can train by doing:
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trainer.fit(model)
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---
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----------
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Training loop structure
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-----------------------
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@@ -181,7 +181,7 @@ don't run your test data by accident. Instead you have to explicitly call:
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trainer = Trainer()
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trainer.test(model)
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---
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----------
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Training_step_end method
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------------------------
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@@ -211,7 +211,7 @@ which allows you to operate on the pieces of the batch
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# like calculate validation set accuracy or loss
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training_epoch_end(val_outs)
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---
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----------
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Remove cuda calls
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-----------------
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@@ -230,7 +230,7 @@ When you init a new tensor in your code, just use type_as
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z = sample_noise()
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z = z.type_as(x.type())
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---
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----------
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Data preparation
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----------------
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