Comments (1)
You can try to edit the binaries directly, but it is not recommended because it will break them. It is safe to avoid such tricks unless you are an engineer who knows what index
means.
https://github.com/PINTO0309/tflite2json2tflite
I do not intend to assist with this requirement.
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Related Issues (20)
- Unable to replace flatten HOT 4
- How to convert onnx(NCHW) to NHWC and write back to onnx file Because my HW takes onnx file as input in NHWC format HOT 3
- How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file HOT 1
- How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file HOT 3
- Please do reply for the last time either this issue or @ How to convert onnx(NCHW) to NHWC(without adding transpose) and write back to onnx file #586 HOT 1
- ONNX Split operation converts to a tf StridedSlice operation with outputs in the wrong order. HOT 2
- Depth_Anything to ONNX model's conversion failed HOT 1
- Bad accuracy after conversion HOT 1
- onnx2tf conversion error for gpt2 transformers model HOT 2
- onnx2tf conversion error for gpt2 transformers model #591 follow up HOT 2
- Error when trying to run converted model; gpt2 tensorflow from onnx #591 follow up HOT 1
- Model modification issue HOT 2
- Onnx to tflite conversion issue on TILE layer.
- While converting onnx to tflite TILE layer is getting ignored. HOT 2
- [BUG] Celu: discrepancies between the outputs of the ONNX model and converted TensorFlow models. HOT 1
- Discrepancies between Conv layer outputs of the ONNX model and converted TensorFlow models HOT 3
- Resize operation fails (['unk__0', 'unk__1', 'unk__2', 'unk__3']) and raises UnboundLocalError: local variable 'new_size' referenced before assignment HOT 20
- FULL INTEGER QUANTIZED MODEL (INT8) infers always the same value HOT 2
- Error performing quantization-aware training (QAT) with keras onnx2tf generated model HOT 4
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