Re: [dmlc/tvm] [RFC] Frontend layout transformation (#2519)

2019-04-18 Thread Zhao Wu
@srkreddy1238 @yzhliu Thanks comments! If all of you agree, I will make TFLite frontend support from NCHW to NHWC. @yzhliu Yes. quantization part support is not been upstreamed yet. It has many changes. I plan to upstream it in dev 0.6. My original plan is to support TFLite NHWC the reason is w

Podling Report Reminder - May 2019

2019-04-18 Thread jmclean
Dear podling, This email was sent by an automated system on behalf of the Apache Incubator PMC. It is an initial reminder to give you plenty of time to prepare your quarterly board report. The board meeting is scheduled for Wed, 15 May 2019, 10:30 am PDT. The report for your podling will form a p

Re: [dmlc/tvm] [RFC] Frontend layout transformation (#2519)

2019-04-18 Thread Yizhi Liu
I prefer not to do any layout conversion in frontend. Just to clarify, tflite quantization has not been upstreamed, right? @FrozenGene -- 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/2519

Re: [dmlc/tvm] [RFC][DISCUSS] Tuple-related Fusion (#3039)

2019-04-18 Thread Tianqi Chen
@masahi In your exmaple of two strided_slice, given that we do not yet cooperatively fuse the two parallel strided_slice together atm, the second version is mostly as efficient as the first one. -- You are receiving this because you are subscribed to this thread. Reply to this email directly or

[TVM Discuss] [Development] [DISCUSS] Contributing new docs for InferBound

2019-04-18 Thread Jessica Davies via TVM Discuss
I added a section on PassUpDomain's limitations, and made a pull request #[3040](https://github.com/dmlc/tvm/pull/3040). @YuanLin, I didn't end up including the content on threads. I think it would be helpful to add more explanation of basic thread concepts, to help the reader understand why

Re: [dmlc/tvm] [RFC][DISCUSS] Tuple-related Fusion (#3039)

2019-04-18 Thread masahi
@tqchen I'm looking into the following approach: * Initially, the tuple and its fields are marked as Injective, so that they can be fused as much as possible. * Later, if we detect that a tuple is the root of its group in [this line](https://github.com/dmlc/tvm/blob/master/src/relay/pass/fuse_op

Re: [dmlc/tvm] [RFC][DISCUSS] Tuple-related Fusion (#3039)

2019-04-18 Thread Zhi
@masahi I see, thanks. Another option is probably using a copy operator if there are duplicates. -- 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/3039#issuecomment-484385353

Re: [dmlc/tvm] [RFC][DISCUSS] Tuple-related Fusion (#3039)

2019-04-18 Thread masahi
@zhiics It looks like the tuple with duplicated tensors is only problematic if it is the return value of a subfunction (i.e. a function that is lowered to topi and compiled by TVM). If we lift the tuple out of a subfunction and put it under the global function, it seems to work fine. The test be