Comments (3)
I think that Metal (MPS) support would be event better, because of mac GPU models list and Core ML GPU’s support. Metal supports AMD, NVidia and even Intel GPU’s. In ideal case we don’t want to think about hardware. And It would be great if Turi Create will chose optimal hardware backend themself as CoreML do in case of CPU/GPU choise.
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I wrote new issue with these notes - #115
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We are looking into this. We will use the issue in #115 to track the issue.
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Related Issues (20)
- TuriCreate not saving nor exporting in Google Colab HOT 1
- Install turicreate on Google colab HOT 1
- Is the image similarity example broken for CoreML?
- Turi Create installation on anaconda virtual environment HOT 1
- issue seaborn
- GraphLab Create requires a license to use in linux HOT 1
- SFRAME problem and turicreate HOT 3
- Can you continue training ObjectDetector model?
- Object detection - Segfault after a large number of iterations
- available data sets in turicreate
- Mac M2 model.export_coreml('.mlmodel') Unable to export model HOT 1
- TuriCreate still doesn't work on M1 using rosetta terminal HOT 7
- While training object_detector in colab randomly Using CPU/GPU to create model.
- Trying to create a model on a larger dataset - Loss stuck at the same number and not moving, resulting model predictions detect nothing
- Support Python 3.9 HOT 1
- pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
- Simple Image Classification Model gives different confidence level (Between Coreml UI and iOS App)
- pip dependency conflicts: conda-repo-cli 1.0.20 requires nbformat==5.4.0, but you have nbformat 5.7.3 which is incompatible. HOT 1
- AttributeError: module 'numpy' has no attribute 'typeDict' HOT 1
- Cannot install and import TuriCreate HOT 1
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