'generate_detections/while/while' for RetinaNet model
- Dominant language
- Python
- Stars
- 5.4k
- Forks
- 850
- Avg merge
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- Merged PRs (30d)
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Description
- Name of layer type: **'generate_detections/while/while'**
- Is this a PyTorch or a TensorFlow layer type: **Tensorflow**
- Your version of coremltools: **7.1**
- Your version of PyTorch/TensorFlow: **2.13**
- Impact of supporting this layer type. Why is adding support for this layer type important? Is it necessary to support a popular model or use case? **It allows using object detection model `RetinaNet` from the TF2 model garden/ official vision task. (see [here](https://github.com/tensorflow/models/tree/master/official/vision#retinanet-imagenet-pretrained))**
Contributor guide
Research direction
Start by reading the TensorFlow 2 official vision task's RetinaNet model and reproducing its conversion with coremltools 7.1. Trace how the TensorFlow layer named 'generate_detections/while/while' is handled, then add support and a regression check showing that RetinaNet conversion succeeds.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100