Revert "Remove deprecated device attributes from Trainer (#14829)"

This reverts commit 1d3e971.

Author: awaelchli

src/pytorch_lightning/CHANGELOG.md

@@ -257,16 +257,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Removed the deprecated device attributes `Trainer.{devices,gpus,num_gpus,ipus,tpu_cores}` in favor of the accelerator-agnostic `Trainer.num_devices` ([#14829](https://github.com/Lightning-AI/lightning/pull/14829))
 
-
-- Removed the deprecated `LightningIPUModule` ([#14830](https://github.com/Lightning-AI/lightning/pull/14830))
-
-
-- Removed the deprecated `Logger.agg_and_log_metrics` hook in favour of `Logger.log_metrics` and the `agg_key_funcs` and `agg_default_func` arguments. ([#14840](https://github.com/Lightning-AI/lightning/pull/14840))
-
-
-- Removed the deprecated precision plugin checkpoint hooks `PrecisionPlugin.on_load_checkpoint` and `PrecisionPlugin.on_save_checkpoint` ([#14833](https://github.com/Lightning-AI/lightning/pull/14833))
-
-
 - Removed the deprecated `Trainer.root_gpu` attribute in favor of `Trainer.strategy.root_device` ([#14829](https://github.com/Lightning-AI/lightning/pull/14829))
 
 
@@ -275,6 +265,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed the deprecated callback hooks `Callback.on_init_start` and `Callback.on_init_end` ([#14867](https://github.com/Lightning-AI/lightning/pull/14867))
 
 
+### Fixed
+
 - Removed the deprecated `Trainer.run_stage` in favor of `Trainer.{fit,validate,test,predict}` ([#14870](https://github.com/Lightning-AI/lightning/pull/14870))
 
 

src/pytorch_lightning/trainer/trainer.py

@@ -1710,6 +1710,46 @@ def num_devices(self) -> int:
         """Number of devices the trainer uses per node."""
         return len(self.device_ids)
 
+    @property
+    def root_gpu(self) -> Optional[int]:
+        rank_zero_deprecation(
+            "`Trainer.root_gpu` is deprecated in v1.6 and will be removed in v1.8. "
+            "Please use `Trainer.strategy.root_device.index` instead."
+        )
+        return self.strategy.root_device.index if isinstance(self.accelerator, CUDAAccelerator) else None
+
+    @property
+    def tpu_cores(self) -> int:
+        rank_zero_deprecation(
+            "`Trainer.tpu_cores` is deprecated in v1.6 and will be removed in v1.8. "
+            "Please use `Trainer.num_devices` instead."
+        )
+        return self.num_devices if isinstance(self.accelerator, TPUAccelerator) else 0
+
+    @property
+    def ipus(self) -> int:
+        rank_zero_deprecation(
+            "`Trainer.ipus` was deprecated in v1.6 and will be removed in v1.8."
+            " Please use `Trainer.num_devices` instead."
+        )
+        return self.num_devices if isinstance(self.accelerator, IPUAccelerator) else 0
+
+    @property
+    def num_gpus(self) -> int:
+        rank_zero_deprecation(
+            "`Trainer.num_gpus` was deprecated in v1.6 and will be removed in v1.8."
+            " Please use `Trainer.num_devices` instead."
+        )
+        return self.num_devices if isinstance(self.accelerator, CUDAAccelerator) else 0
+
+    @property
+    def devices(self) -> int:
+        rank_zero_deprecation(
+            "`Trainer.devices` was deprecated in v1.6 and will be removed in v1.8."
+            " Please use `Trainer.num_devices` or `Trainer.device_ids` to get device information instead."
+        )
+        return self.num_devices
+
     @property
     def lightning_module(self) -> "pl.LightningModule":
         # TODO: this is actually an optional return
@@ -1752,7 +1792,15 @@ def scaler(self) -> Optional[Any]:
         return getattr(self.precision_plugin, "scaler", None)
 
     @property
-    def model(self) -> Optional[torch.nn.Module]:
+    def gpus(self) -> Optional[Union[List[int], str, int]]:
+        rank_zero_deprecation(
+            "`Trainer.gpus` was deprecated in v1.6 and will be removed in v1.8."
+            " Please use `Trainer.num_devices` or `Trainer.device_ids` to get device information instead."
+        )
+        return self._accelerator_connector._gpus
+
+    @property
+    def model(self) -> torch.nn.Module:
         """The LightningModule, but possibly wrapped into DataParallel or DistributedDataParallel.
 
         To access the pure LightningModule, use