diff --git a/CHANGELOG.md b/CHANGELOG.md
index fa9bd9c0ce71b..ed23d361164d7 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -63,7 +63,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Changes in `LightningCLI` required for the new major release of jsonargparse v4.0.0 ([#10426](https://github.com/PyTorchLightning/pytorch-lightning/pull/10426))
 
 
-- Renamed `refresh_rate_per_second` parameter to `referesh_rate` for `RichProgressBar` signature ([#10497](https://github.com/PyTorchLightning/pytorch-lightning/pull/10497))
+- Renamed `refresh_rate_per_second` parameter to `refresh_rate` for `RichProgressBar` signature ([#10497](https://github.com/PyTorchLightning/pytorch-lightning/pull/10497))
 
 
 - Moved ownership of the `PrecisionPlugin` into `TrainingTypePlugin` and updated all references ([#10570](https://github.com/PyTorchLightning/pytorch-lightning/pull/10570))
@@ -116,6 +116,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated the access to the attribute `IndexBatchSamplerWrapper.batch_indices` in favor of `IndexBatchSamplerWrapper.seen_batch_indices` ([#10870](https://github.com/PyTorchLightning/pytorch-lightning/pull/10870))
 
 
+- Deprecated `Trainer.call_hook` in favor of `Trainer._call_callback_hooks`, `Trainer._call_lightning_module_hook`, `Trainer._call_ttp_hook`, and `Trainer._call_accelerator_hook` ([#10979](https://github.com/PyTorchLightning/pytorch-lightning/pull/10979))
+
+
 - Deprecated `TrainingTypePlugin.post_dispatch` in favor of `TrainingTypePlugin.teardown` ([#10939](https://github.com/PyTorchLightning/pytorch-lightning/pull/10939))
 
 
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index bb9398570bc08..7687b5ecf148c 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -1446,6 +1446,63 @@ def _call_teardown_hook(self) -> None:
         # summarize profile results
         self.profiler.describe()
 
+    def call_hook(
+        self, hook_name: str, *args: Any, pl_module: Optional["pl.LightningModule"] = None, **kwargs: Any
+    ) -> Any:
+        r"""
+        .. deprecated:: v1.6
+            The Trainer's `call_hook` method was deprecated in v1.6 and will be removed in v1.8.
+        """
+        rank_zero_deprecation("The Trainer's `call_hook` method was deprecated in v1.6 and will be removed in v1.8.")
+        pl_module = self.lightning_module or pl_module
+        if pl_module:
+            prev_fx_name = pl_module._current_fx_name
+            pl_module._current_fx_name = hook_name
+
+        # always profile hooks
+        with self.profiler.profile(hook_name):
+
+            # first call trainer hook
+            callback_fx = getattr(self, hook_name, None)
+            if callable(callback_fx):
+                callback_fx(*args, **kwargs)
+
+            # next call hook in lightningModule
+            output = None
+            model_fx = getattr(pl_module, hook_name, None)
+            if callable(model_fx):
+                output = model_fx(*args, **kwargs)
+
+            # *Bad code alert*
+            # The `Accelerator` mostly calls the `TrainingTypePlugin` but some of those calls are deprecated.
+            # The following logic selectively chooses which hooks are called on each object.
+            # In the case of `setup` and `teardown`, the hooks on the `LightningModule` should not call the hooks of the
+            # same name in these objects as they are meant to be managed outside of the `LightningModule` lifecycle.
+            # All of this should be fixed by #8506
+
+            # call the accelerator hook
+            if hook_name in ("on_train_start",) and hasattr(self.accelerator, hook_name):
+                accelerator_hook = getattr(self.accelerator, hook_name)
+                accelerator_output = accelerator_hook(*args, **kwargs)
+                # Rely on the accelerator output if lightningModule hook returns nothing
+                # Required for cases such as DataParallel where we reduce the output for the user
+                # todo: move this data parallel logic into the data parallel plugin
+                output = accelerator_output if output is None else output
+
+            # call the ttp hook
+            if hook_name not in ("setup", "teardown", "on_train_start") and hasattr(
+                self.training_type_plugin, hook_name
+            ):
+                ttp_hook = getattr(self.training_type_plugin, hook_name)
+                ttp_output = ttp_hook(*args, **kwargs)
+                output = ttp_output if output is None else output
+
+        if pl_module:
+            # restore current_fx when nested context
+            pl_module._current_fx_name = prev_fx_name
+
+        return output
+
     def _call_lightning_module_hook(
         self,
         hook_name: str,
diff --git a/tests/deprecated_api/test_remove_1-8.py b/tests/deprecated_api/test_remove_1-8.py
index 7ef0fe2a15e4f..e58e7927641c3 100644
--- a/tests/deprecated_api/test_remove_1-8.py
+++ b/tests/deprecated_api/test_remove_1-8.py
@@ -16,6 +16,7 @@
 import pytest
 import torch
 
+from pytorch_lightning import Trainer
 from pytorch_lightning.utilities.apply_func import move_data_to_device
 from pytorch_lightning.utilities.enums import DeviceType, DistributedType
 from pytorch_lightning.utilities.imports import _TORCHTEXT_LEGACY
@@ -41,3 +42,15 @@ def test_v1_8_0_deprecated_torchtext_batch():
         data_iterator, _ = get_dummy_torchtext_data_iterator(num_samples=3, batch_size=3)
         batch = next(iter(data_iterator))
         _ = move_data_to_device(batch=batch, device=torch.device("cpu"))
+
+
+def test_v1_8_0_deprecated_call_hook():
+    trainer = Trainer(
+        max_epochs=1,
+        limit_val_batches=0.1,
+        limit_train_batches=0.2,
+        enable_progress_bar=False,
+        logger=False,
+    )
+    with pytest.deprecated_call(match="was deprecated in v1.6 and will be removed in v1.8."):
+        trainer.call_hook("test_hook")