docs: fixing links to the hosted docs (#2104)

README.md

@@ -10,7 +10,7 @@ ______________________________________________________________________
   <a href="#what-is-torchmetrics">What is Torchmetrics</a> •
   <a href="#implementing-your-own-module-metric">Implementing a metric</a> •
   <a href="#build-in-metrics">Built-in metrics</a> •
-  <a href="https://torchmetrics.readthedocs.io/en/stable/">Docs</a> •
+  <a href="https://lightning.ai/docs/torchmetrics/stable/">Docs</a> •
   <a href="#community">Community</a> •
   <a href="#license">License</a>
 </p>
@@ -106,7 +106,7 @@ You can use TorchMetrics with any PyTorch model or with [PyTorch Lightning](http
 
 ### Module metrics
 
-The [module-based metrics](https://torchmetrics.readthedocs.io/en/stable/references/metric.html) contain internal metric states (similar to the parameters of the PyTorch module) that automate accumulation and synchronization across devices!
+The [module-based metrics](https://lightning.ai/docs/torchmetrics/stable/references/metric.html) contain internal metric states (similar to the parameters of the PyTorch module) that automate accumulation and synchronization across devices!
 
 - Automatic accumulation over multiple batches
 - Automatic synchronization between multiple devices
@@ -257,7 +257,7 @@ print(my_metric(preds, target))
 
 ### Functional metrics
 
-Similar to [`torch.nn`](https://pytorch.org/docs/stable/nn.html), most metrics have both a [module-based](https://torchmetrics.readthedocs.io/en/latest/references/modules.html) and a [functional](https://torchmetrics.readthedocs.io/en/latest/references/functional.html) version.
+Similar to [`torch.nn`](https://pytorch.org/docs/stable/nn.html), most metrics have both a [module-based](https://lightning.ai/docs/torchmetrics/stable/references/metric.html) and functional version.
 The functional versions are simple python functions that as input take [torch.tensors](https://pytorch.org/docs/stable/tensors.html) and return the corresponding metric as a [torch.tensor](https://pytorch.org/docs/stable/tensors.html).
 
 ```python
@@ -277,7 +277,7 @@ acc = torchmetrics.functional.classification.multiclass_accuracy(
 
 ### Covered domains and example metrics
 
-In total TorchMetrics contains [100+ metrics](https://torchmetrics.readthedocs.io/en/stable/all-metrics.html), which
+In total TorchMetrics contains [100+ metrics](https://lightning.ai/docs/torchmetrics/stable/all-metrics.html), which
 convers the following domains:
 
 - Audio

docs/source/_templates/theme_variables.jinja

@@ -2,12 +2,12 @@
   'github': 'https://github.com/Lightning-AI/torchmetrics',
   'github_issues': 'https://github.com/Lightning-AI/torchmetrics/issues',
   'contributing': 'https://github.com/Lightning-AI/torchmetrics/blob/master/.github/CONTRIBUTING.md',
-  'docs': 'https://torchmetrics.readthedocs.io/en/latest',
+  'docs': 'https://lightning.ai/docs/torchmetrics/latest',
   'twitter': 'https://twitter.com/PyTorchLightnin',
   'discuss': 'https://pytorch-lightning.slack.com',
   'previous_pytorch_versions': 'https://torchmetrics.rtfd.io/en/latest/',
   'home': 'https://torchmetrics.rtfd.io/en/latest/',
-  'get_started': 'https://torchmetrics.readthedocs.io/en/latest/pages/quickstart.html',
+  'get_started': 'https://lightning.ai/docs/torchmetrics/latest/pages/quickstart.html',
   'blog': 'https://www.pytorchlightning.ai/blog',
   'support': 'https://github.com/Lightning-AI/torchmetrics/issues',
   'community': 'https://pytorch-lightning.slack.com',

docs/source/pages/implement.rst

@@ -12,7 +12,7 @@ Implementing a Metric
 While we strive to include as many metrics as possible in ``torchmetrics``, we cannot include them all. Therefore, we
 have made it easy to implement your own metric and possible contribute it to ``torchmetrics``. This page will guide
 you through the process. If you afterwards are interested in contributing your metric to ``torchmetrics``, please
-read the `contribution guidelines <https://torchmetrics.readthedocs.io/en/latest/generated/CONTRIBUTING.html>`_ and
+read the `contribution guidelines <https://lightning.ai/docs/torchmetrics/latest/generated/CONTRIBUTING.html>`_ and
 see this :ref:`section <contributing metric>`.
 
 **************
@@ -242,7 +242,7 @@ Wanting to contribute the metric you have implemented? Great, we are always open
 as long as they serve a general purpose. However, to keep all our metrics consistent we request that the implementation
 and tests gets formatted in the following way:
 
-1. Start by reading our `contribution guidelines <https://torchmetrics.readthedocs.io/en/latest/generated/CONTRIBUTING.html>`_.
+1. Start by reading our `contribution guidelines <https://lightning.ai/docs/torchmetrics/latest/generated/CONTRIBUTING.html>`_.
 2. First implement the functional backend. This takes cares of all the logic that goes into the metric. The code should
    be put into a single file placed under ``src/torchmetrics/functional/"domain"/"new_metric".py`` where ``domain`` is the type of
    metric (classification, regression, text etc.) and ``new_metric`` is the name of the metric. In this file, there should be the

src/torchmetrics/__about__.py

@@ -5,7 +5,7 @@
 __copyright__ = f"Copyright (c) 2020-2023, {__author__}."
 __homepage__ = "https://github.com/Lightning-AI/torchmetrics"
 __docs__ = "PyTorch native Metrics"
-__docs_url__ = "https://torchmetrics.readthedocs.io/en/stable/"
+__docs_url__ = "https://lightning.ai/docs/torchmetrics/stable/"
 __long_doc__ = """
 Torchmetrics is a metrics API created for easy metric development and usage in both PyTorch and
 [PyTorch Lightning](https://pytorch-lightning.readthedocs.io/en/stable/). It was originally a part of