Re: [dmlc/tvm] [RFC] [Contrib] [Runtime] Minimal runtime (~12kb .text on ARMv7/x86) for subset of TVM models (#3567)

@ajtulloch Awesome work on this! We'll need a runtime for uTVM when we want to try self-hosted models, so the timing on this is great. My general understanding is that it's much more common for bare-metal devices to support C, so it'd be interesting to see if we could incrementally whittle thi

Re: [dmlc/tvm] [RFC] Initial support for Tflite operator SPLIT (#3520)

Thanks @u99127 LGTM now. -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/dmlc/tvm/pull/3520#issuecomment-513425857

Re: [dmlc/tvm] [QNN] [RFC] QNN Dialect - Supporting pre-quantized models in TVM (#3591)

Let's start with just Requantize to keep it focussed ### QNN proposal ~~~ def requantize(data, input_scale, input_zero_point, output_scale, output_zero_point, rounding="AWAY_FROM_ZERO", out_dtype="int8"):

Re: [dmlc/tvm] [RFC][Quantization] Support quantized models from TensorflowLite (#2351)

Let us move to https://github.com/dmlc/tvm/issues/3591 -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/dmlc/tvm/issues/2351#issuecomment-513418264

Re: [dmlc/tvm] [RFC][Quantization] Support quantized models from TensorflowLite (#2351)

Closed #2351. -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/dmlc/tvm/issues/2351#event-2497269051

Re: [dmlc/tvm] [QNN] [RFC] QNN Dialect - Supporting pre-quantized models in TVM (#3591)

also cc @ajtulloch @ZihengJiang @vinx13 , @anijain2305 can you please list the API proposals and the reference APIs(in tflite etcs?) Then we can try to get everyone's thoughts on these specific API designs -- You are receiving this because you are subscribed to this thread. Reply to this email

Re: [dmlc/tvm] [RFC][Quantization] Support quantized models from TensorflowLite (#2351)

@tqchen Thanks for reminding. Just created one :) -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/dmlc/tvm/issues/2351#issuecomment-513414742

[dmlc/tvm] [QNN] [RFC] QNN Dialect - Supporting pre-quantized models in TVM (#3591)

We are proposing a new dialect named `QNN`, that introduces a quantized version of existing relay operators. The goal is to support the models that have been pre-quantized in the framework. Some important notes about QNN dialect are * QNN operators are lowered to existing Relay operators to ens

Re: [dmlc/tvm] [RFC][Quantization] Support quantized models from TensorflowLite (#2351)

@anijain2305 can you open the RFC thread? Sorry for being a bit formal in this case, we want to set an example for the first dialect public discussions. -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/dml

[TVM Discuss] [Development] Adding tf.size operator to TVM

Thanks for your suggestions! Indeed, for the frontend there a bit of documentation and comments missing to know when to use what. For example, I see that is some cases the operator are invoked with the `_op` prefix like `_op.clip(...)`. Other times the `AttrCvt()` function is used for other o

Re: [dmlc/tvm] [RFC] Initial support for Tflite operator SPLIT (#3520)

@u99127 Could you modify PR as my suggestion? I think it will work now. Thanks. -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/dmlc/tvm/pull/3520#issuecomment-513176720