replace MD template with Yaml - feature (#15908)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

.github/ISSUE_TEMPLATE/3_feature_request.yaml

@@ -0,0 +1,47 @@
+name: Feature request
+description: Propose a feature for this project
+labels: ["needs triage"]
+body:
+  - type: textarea
+    attributes:
+      label: Description & Motivation
+      description: A clear and concise description of the feature proposal
+      placeholder: |
+        Please outline the motivation for the proposal.
+        Is your feature request related to a problem? e.g., I'm always frustrated when [...].
+        If this is related to another GitHub issue, please link it here
+
+  - type: textarea
+    attributes:
+      label: Pitch
+      description: A clear and concise description of what you want to happen.
+    validations:
+      required: false
+
+  - type: textarea
+    attributes:
+      label: Alternatives
+      description: A clear and concise description of any alternative solutions or features you've considered, if any.
+    validations:
+      required: false
+
+  - type: textarea
+    attributes:
+      label: Additional context
+      description: Add any other context or screenshots about the feature request here.
+    validations:
+      required: false
+
+  - type: markdown
+    attributes:
+      value: >
+        ### If you enjoy Lightning, check out our other projects! ⚡
+
+        - [**Metrics**](https://github.com/Lightning-AI/metrics):
+          Machine learning metrics for distributed, scalable PyTorch applications.
+        - [**Lite**](https://pytorch-lightning.readthedocs.io/en/latest/starter/lightning_lite.html):
+          enables pure PyTorch users to scale their existing code on any kind of device while retaining full control over their own loops and optimization logic.
+        - [**Flash**](https://github.com/Lightning-AI/lightning-flash):
+          The fastest way to get a Lightning baseline! A collection of tasks for fast prototyping, baselining, fine-tuning, and solving problems with deep learning.
+        - [**Bolts**](https://github.com/Lightning-AI/lightning-bolts):
+          Pretrained SOTA Deep Learning models, callbacks, and more for research and production with PyTorch Lightning and PyTorch.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -1,41 +0,0 @@
----
-name: Feature request
-about: Propose a feature for this project
-title: ''
-labels: needs triage
-assignees: ''
----
-
-## 🚀 Feature
-
-<!-- A clear and concise description of the feature proposal -->
-
-### Motivation
-
-<!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link it here -->
-
-### Pitch
-
-<!-- A clear and concise description of what you want to happen. -->
-
-### Alternatives
-
-<!-- A clear and concise description of any alternative solutions or features you've considered, if any. -->
-
-### Additional context
-
-<!-- Add any other context or screenshots about the feature request here. -->
-
-______________________________________________________________________
-
-#### If you enjoy Lightning, check out our other projects! ⚡
-
-- [**Metrics**](https://github.com/Lightning-AI/metrics): Machine learning metrics for distributed, scalable PyTorch applications.
-
-- [**Lite**](https://pytorch-lightning.readthedocs.io/en/latest/starter/lightning_lite.html): enables pure PyTorch users to scale their existing code on any kind of device while retaining full control over their own loops and optimization logic.
-
-- [**Flash**](https://github.com/Lightning-AI/lightning-flash): The fastest way to get a Lightning baseline! A collection of tasks for fast prototyping, baselining, fine-tuning, and solving problems with deep learning.
-
-- [**Bolts**](https://github.com/Lightning-AI/lightning-bolts): Pretrained SOTA Deep Learning models, callbacks, and more for research and production with PyTorch Lightning and PyTorch.
-
-- [**Lightning Transformers**](https://github.com/Lightning-AI/lightning-transformers): Flexible interface for high-performance research using SOTA Transformers leveraging PyTorch Lightning, Transformers, and Hydra.