replace train_percent_check with limit_train_batches (#2220)

* drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * drop train_percent_check * chlog * deprecated * deprecated * deprecated * tests * tests * Apply suggestions from code review * tests * hydra support * tests * hydra support * hydra support * hydra support * tests * typo * typo * Update test_dataloaders.py * docs * docs * docs * docs Co-authored-by: Jirka <jirka@pytorchlightning.ai> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Lightning-AI · Jun 17, 2020 · 2411c3b · 2411c3b
1 parent 9945e87
commit 2411c3b
Show file tree

Hide file tree

Showing 32 changed files with 416 additions and 247 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -21,10 +21,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Added
 
-- Added overfit_batches, limit_xxx_batches flags (overfit now uses training set for all three) ([#2213](https://github.com/PyTorchLightning/pytorch-lightning/pull/2213))
-- Added metric Base classes ([#1326](https://github.com/PyTorchLightning/pytorch-lightning/pull/1326), [#1877](https://github.com/PyTorchLightning/pytorch-lightning/pull/1877))
-- Added Sklearn metrics classes ([#1327](https://github.com/PyTorchLightning/pytorch-lightning/pull/1327))
-- Added Native torch metrics ([#1488](https://github.com/PyTorchLightning/pytorch-lightning/pull/1488))
+- Added `overfit_batches`, `limit_{val|test}_batches` flags (overfit now uses training set for all three) ([#2213](https://github.com/PyTorchLightning/pytorch-lightning/pull/2213))
 - Added metrics 
   * Base classes ([#1326](https://github.com/PyTorchLightning/pytorch-lightning/pull/1326), [#1877](https://github.com/PyTorchLightning/pytorch-lightning/pull/1877))
   * Sklearn metrics classes ([#1327](https://github.com/PyTorchLightning/pytorch-lightning/pull/1327))
@@ -58,7 +55,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Deprecated
 
-- Deprecated `overfit_pct`, `val_percent_check`, `test_percent_check` ([#2213](https://github.com/PyTorchLightning/pytorch-lightning/pull/2213))
+- Deprecated flags: ([#2213](https://github.com/PyTorchLightning/pytorch-lightning/pull/2213))
+  * `overfit_pct` >> `overfit_batches`
+  * `val_percent_check` >> `limit_val_batches`
+  * `test_percent_check` >> `limit_test_batches`
 - Deprecated `ModelCheckpoint`'s attributes `best` and `kth_best_model` ([#1799](https://github.com/PyTorchLightning/pytorch-lightning/pull/1799))
 - Dropped official support/testing for older PyTorch versions <1.3 ([#1917](https://github.com/PyTorchLightning/pytorch-lightning/pull/1917))
 

diff --git a/docs/source/callbacks.rst b/docs/source/callbacks.rst
@@ -46,7 +46,7 @@ Example:
 We successfully extended functionality without polluting our super clean
 :class:`~pytorch_lightning.core.LightningModule` research code.
 
----------
+---
 
 .. automodule:: pytorch_lightning.callbacks.base
    :noindex:
@@ -56,7 +56,7 @@ We successfully extended functionality without polluting our super clean
         _abc_impl,
         check_monitor_top_k,
 
----------
+---
 
 .. automodule:: pytorch_lightning.callbacks.early_stopping
    :noindex:
@@ -66,36 +66,36 @@ We successfully extended functionality without polluting our super clean
         _abc_impl,
         check_monitor_top_k,
 
----------
+---
 
-.. automodule:: pytorch_lightning.callbacks.model_checkpoint
+.. automodule:: pytorch_lightning.callbacks.gradient_accumulation_scheduler
    :noindex:
    :exclude-members:
         _del_model,
         _save_model,
         _abc_impl,
         check_monitor_top_k,
 
----------
+---
 
-.. automodule:: pytorch_lightning.callbacks.gradient_accumulation_scheduler
+.. automodule:: pytorch_lightning.callbacks.lr_logger
+    :noindex:
+    :exclude-members:
+        _extract_lr,
+        _find_names
+
+---
+
+.. automodule:: pytorch_lightning.callbacks.model_checkpoint
    :noindex:
    :exclude-members:
         _del_model,
         _save_model,
         _abc_impl,
         check_monitor_top_k,
 
----------
+---
 
 .. automodule:: pytorch_lightning.callbacks.progress
    :noindex:
    :exclude-members:
-
----------
-
-.. automodule:: pytorch_lightning.callbacks.lr_logger
-    :noindex:
-    :exclude-members:
-        _extract_lr,
-        _find_names
diff --git a/docs/source/fast_training.rst b/docs/source/fast_training.rst
@@ -8,6 +8,8 @@ Fast Training
 There are multiple options to speed up different parts of the training by choosing to train
 on a subset of data. This could be done for speed or debugging purposes.
 
+----------------------
+
 Check validation every n epochs
 -------------------------------
 If you have a small dataset you might want to check validation every n epochs
@@ -17,6 +19,8 @@ If you have a small dataset you might want to check validation every n epochs
     # DEFAULT
     trainer = Trainer(check_val_every_n_epoch=1)
 
+----------------------
+
 Force training for min or max epochs
 ------------------------------------
 It can be useful to force training for a minimum number of epochs or limit to a max number.
@@ -29,6 +33,7 @@ It can be useful to force training for a minimum number of epochs or limit to a
     # DEFAULT
     trainer = Trainer(min_epochs=1, max_epochs=1000)
 
+----------------------
 
 Set validation check frequency within 1 training epoch
 ------------------------------------------------------
@@ -47,6 +52,8 @@ Must use an int if using an IterableDataset.
     # check every 100 train batches (ie: for IterableDatasets or fixed frequency)
     trainer = Trainer(val_check_interval=100)
 
+----------------------
+
 Use data subset for training, validation and test
 -------------------------------------------------
 If you don't want to check 100% of the training/validation/test set (for debugging or if it's huge), set these flags.
@@ -55,18 +62,18 @@ If you don't want to check 100% of the training/validation/test set (for debuggi
 
     # DEFAULT
     trainer = Trainer(
-        train_percent_check=1.0,
+        limit_train_batches=1.0,
         limit_val_batches=1.0,
         limit_test_batches=1.0
     )
 
     # check 10%, 20%, 30% only, respectively for training, validation and test set
     trainer = Trainer(
-        train_percent_check=0.1,
+        limit_train_batches=0.1,
         limit_val_batches=0.2,
         limit_test_batches=0.3
     )
 
-.. note:: ``train_percent_check``, ``limit_val_batches`` and ``limit_test_batches`` will be overwritten by ``overfit_batches`` if ``overfit_batches`` > 0. ``limit_val_batches`` will be ignored if ``fast_dev_run=True``.
+.. note:: ``limit_train_batches``, ``limit_val_batches`` and ``limit_test_batches`` will be overwritten by ``overfit_batches`` if ``overfit_batches`` > 0. ``limit_val_batches`` will be ignored if ``fast_dev_run=True``.
 
 .. note:: If you set ``limit_val_batches=0``, validation will be disabled.
diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -21,10 +21,10 @@ PyTorch Lightning Documentation
    :caption: Python API
 
    callbacks
-   hooks
    lightning-module
    loggers
    metrics
+   hooks
    trainer
 
 .. toctree::

diff --git a/docs/source/new-project.rst b/docs/source/new-project.rst
@@ -239,7 +239,7 @@ Without changing a SINGLE line of your code, you can now do the following with t
         tpu_cores=8,
         precision=16,
         early_stop_checkpoint=True,
-        train_percent_check=0.5,
+        limit_train_batches=0.5,
         val_check_interval=0.25
     )
 

diff --git a/docs/source/weights_loading.rst b/docs/source/weights_loading.rst
@@ -35,7 +35,7 @@ To change the checkpoint path pass in:
 
 To modify the behavior of checkpointing pass in your own callback.
 
-.. testcode::
+.. code-block:: python
 
     from pytorch_lightning.callbacks import ModelCheckpoint
 

diff --git a/pytorch_lightning/__init__.py b/pytorch_lightning/__init__.py
@@ -52,7 +52,7 @@
 else:
     from pytorch_lightning.core import LightningModule
     from pytorch_lightning.trainer import Trainer
-    from pytorch_lightning.trainer.seed import seed_everything
+    from pytorch_lightning.utilities.seed import seed_everything
     from pytorch_lightning.callbacks import Callback
     from pytorch_lightning.core import data_loader
 

diff --git a/pytorch_lightning/callbacks/lr_logger.py b/pytorch_lightning/callbacks/lr_logger.py
@@ -1,7 +1,7 @@
 r"""
 
-Logging of learning rates
-=========================
+Learning Rate Logger
+====================
 
 Log learning rate for lr schedulers during training