ANSHUMAN87 commented on pull request #8368: URL: https://github.com/apache/tvm/pull/8368#issuecomment-871557346
> This patch adds infrastructure to directly generate TFLite model buffers > by using flatc, the flatbuffers command line tool. This gives us more > freedom in creating the models for testing since we don't have to > rely on any of the converters. > > * Add classes and helper functions to create the model buffer > * Add some convolution tests that test TFLite2 models in int8 > with per channel and per tensor quantization and remove the > orphaned Keras tests > > Co-authored with @NicolaLancellotti Hi @ekalda, I am just unable to see the need for such changes. As per my understanding, TFlite framework behaviour is not something we should control in TVM. Model buffers should be created using standard Apis in TFlite. We should not use a custom one to validate our requirements which may result in failure of complete TFlite frontend Parser. Maybe if you share what was the actual motivation for this change, we can discuss about the solution better. Thanks! -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
