
2.3.16 [!IMPORTANT] Starting with onnx2tf v2.4.0, tf_converter will be deprecated and the default backend will be switched to flatbuffer_direct. With the v2.3.3 update, all backward compatible conversion options have been migrated to flatbuffer_direct, so I will only be doing minor bug fixes until April. If you provide us with ONNX sample models, I will consider incorporating them into flatbuffer_direct. I'll incorporate ai-edge-quantizer when I feel like it, but that will probably be about 10 years from now. What's Changed Fix TopK numpy 2.4 compatibility: use .item() before int() cast by @cdeil in https://github.com/PINTO0309/onnx2tf/pull/919 Update add PR invisible Unicode guard by @PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/920 New Contributors @cdeil made their first contribution in https://github.com/PINTO0309/onnx2tf/pull/919 Full Changelog: https://github.com/PINTO0309/onnx2tf/compare/2.3.15...2.3.16
If you use onnx2tf in your research, please cite it using these metadata.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
