Comments (1)
因为pytorch和onnx数据格式基本都是channel first的,而tensorflow是channel last的。因此你只需要对输出做一个tranpose。
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Related Issues (20)
- onnx转为tflite 为啥数据类型变成了uint8? HOT 1
- 模型转换缺少conv3d算子 HOT 3
- 报错
- 模型转换报错 HOT 2
- ValueError: Unrecognized keyword arguments passed to Conv2D: {'weights': [array([[[[-0.16197614, HOT 6
- weight value errot HOT 1
- 可以在转换的时候做fp16量化吗 HOT 2
- ValueError: Unrecognized keyword arguments passed to Conv2D: {'weights': [array([[[[-2.05928516e-02, -1.33914594e-02, -1.65286055e-03, ..., HOT 3
- 转换报错 'tuple' object has no attribute 'ndims' HOT 1
- Feature Request: NonMaxSuppression Layer HOT 1
- 转换onnx模型失败 HOT 1
- 转换后误差大,而且无法进行推理 HOT 2
- 用了博主说的官方onnx-tf和这个onnx2tflite做了yolox_tiny的对比 HOT 1
- KeyError:'GRU not implemented yet'
- 运行报错 HOT 1
- tflite模型精度严重下降 HOT 1
- int(self.shape[i]//inputs.shape[i]) > 1报错IndexError: tuple index out of range
- onnx.py 文件中尝试导入 load_onnx_modelproto 时发生了循环导入 HOT 1
- Error when specifying need_simplify=False when converting HOT 2
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