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Tools to convert ONNX files (NCHW) to TensorFlow format (NHWC)

Authors: Hyodo, Katsuya;

Tools to convert ONNX files (NCHW) to TensorFlow format (NHWC)

Abstract

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

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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).
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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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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