From 54c9adae1ccd75e145fa7da87a63da39013c46aa Mon Sep 17 00:00:00 2001 From: Katsuya Hyodo Date: Wed, 26 Oct 2022 13:22:52 +0900 Subject: [PATCH] Update README.md --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index b1f17d34..68ec933b 100644 --- a/README.md +++ b/README.md @@ -25,6 +25,7 @@ Self-Created Tools to convert ONNX files (NCHW) to TensorFlow format (NHWC). The - [x] If there are ONNX OPs that are not supported by TensorFlow, use [simple-onnx-processing-tools](https://github.com/PINTO0309/simple-onnx-processing-tools) to replace them with harmless OPs in advance and then use this tool to convert them. In other words, you can convert any model with your efforts. - [x] ONNX splitting, merging, generating OPs, rewriting OP attributes, BGR<->RGB conversion, converting to JSON and editing in the IDE, batch size changes for undefined dimensions, and various other processing can be done with the [simple-onnx-processing-tools](https://github.com/PINTO0309/simple-onnx-processing-tools). Therefore, it is recommended that models with very complex structures be converted to TFLite after modifying the structure beforehand. - [x] `BatchNormalization` supports only inference mode. +- [x] `LayerNormalization` supports only inference mode. - [x] Only for `opset=11` or higher - [x] If you do not like the generated TFLite OP name, edit it using [tflite2json2tflite](https://github.com/PINTO0309/tflite2json2tflite). - [x] The generated Keras models cannot be used for retraining. If you want to train, you must build your own model.