TF_ONNX documentation¶
This is an introduction tutorial to TF_ONNX. TF_ONNX is a conversion module to let a protobuffer defined on a protocol buffer another protobuffer on ONNX.
This supports not only just another straightforward conversion, but enables you to customize a given graph structure in a concise buf very flexible manner to let the conversion job very tidy.
For instance, it will support following features in a least confusing manner.
- operation conversion (controlling number of arugments)
- sub-branch pruning (removing identity node on a tensorflow protobuf)
- sub-branch evaluation (useful for quantization function )
- visualization (dot language provided by graphviz library)
Note
This is stil not a general converter from tensorflow pb to onnx pb as the combination of current onnx supported operation cannot cover the operator defined under the Nodedef object on tf-pb.
That being said, numbers of kinds of “op” on Nodedef() would be much less than seeming number of operators written in a tf-tutorial which is nearly 1000 as a function defined as python would be decomposed as a set of basic operators written in c++ on tf.