[TVM Discuss] [Development/RFC] Introducing TVM.NET for bringing TVM features into .NET world

@tqchen: I seek your expert advice for below point. Please help! This is regarding NDArray Design. As in this feature i am trying to bridge between TVM.NET runtime(Managed Memory) and TVM C runtime(Unmanaged Memory) . Below is a snapshot of NDArray Class Design which i have currently. ![imag

[TVM Discuss] [Development/RFC] Introducing TVM.NET for bringing TVM features into .NET world

Others may confirm if this is correct, but I believe they implement this in the Java version by keeping track if the managed NDArray is the owner of the native handle, using that to determine if it can release it. https://github.com/apache/incubator-tvm/blob/1dcf8a16ee3a93dff5ffc1ad1a66892eda0

[TVM Discuss] [Development/RFC] Introducing TVM.NET for bringing TVM features into .NET world

Sorry. Actually, I may have been mistaken on the use of the isView after a closer look at the Java impl and the test code here: https://github.com/apache/incubator-tvm/blob/1dcf8a16ee3a93dff5ffc1ad1a66892eda03ef13/jvm/core/src/test/java/org/apache/tvm/contrib/GraphRuntimeTest.java --- [Vis

[TVM Discuss] [Development] [VTA] A Workaround for Deploying Faster R-CNN on VTA

The pointer should be 64 bits on my virtual machine. After correcting it, I have deployed the Faster R-CNN on VTA. Actually solving this problem, the Faster R-CNN can be supported by VTA. ``` auto data_ptr_tmp = static_cast(input->data); auto data_ptr = reinterpret_cast(*data_ptr_tmp); au

[TVM Discuss] [Development/RFC] Pure WebAssembly support

Thanks for starting the topic. I think one thing we do need to do is to reuse existing cpu autotvm templates and possibly tune for wasm. The lack of dlopen in wasm is not going to go away for a while due to the special programming model. We recently have some rough idea to get around it and w

[TVM Discuss] [Development] [VTA] A Workaround for Deploying Faster R-CNN on Target ext_dev(VTA and ARM CPU)

At present, there is few problem with quantization. The following work is to modify the graph pack function to transform most convolutions into NCHW1n16c to get accelerating. I need to add some op names to complete AST traverse in graph pack function. If there is a mistake, please correct me.

[TVM Discuss] [Development] [VTA] A Workaround for Deploying Faster R-CNN on Target ext_dev(VTA and ARM CPU)

How is the “ lower schedule” printed out? --- [Visit Topic](https://discuss.tvm.ai/t/vta-a-workaround-for-deploying-faster-r-cnn-on-target-ext-dev-vta-and-arm-cpu/6516/4) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click h

[TVM Discuss] [Development] [RFC] Improve Pull Requests with respect to bug fixes

**Motivation** We would like to move towards a world where there is a clear attempt to try and start becoming more predictable with release cycles and what the usage of a release is going to be . As part of this ,releases need regression fixes. However, if the community is making releases, th

[TVM Discuss] [Development] [VTA] A Workaround for Deploying Faster R-CNN on Target ext_dev(VTA and ARM CPU)

tvm.lower python api, you need to give the schedule and input/output symbol. ``` print(tvm.lower(s, [data, valid_count, out], name="test_nms")) ``` --- [Visit Topic](https://discuss.tvm.ai/t/vta-a-workaround-for-deploying-faster-r-cnn-on-target-ext-dev-vta-and-arm-cpu/6516/5) to respond.

Re: [apache/incubator-tvm] [COMMUNITY] @liangfu -> committer (#5460)

Merged #5460 into master. -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/apache/incubator-tvm/pull/5460#event-3283017557

[TVM Discuss] [Development/RFC] [RFC] Improve Pull Requests with respect to bug fixes

cc @yzhliu @haichen @jroesch @ajtulloch @liangfu @jroesch @thierry --- [Visit Topic](https://discuss.tvm.ai/t/rfc-improve-pull-requests-with-respect-to-bug-fixes/6529/2) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click he

[TVM Discuss] [Development/RFC] Introducing TVM.NET for bringing TVM features into .NET world

[quote="ANSHUMAN.TRIPATHY, post:10, topic:6213"] I have proposal for 2 APIs as below: 1. –> NDArray().Detach() --> Once Get output from TVM runtime, and keep it only for read only purpose. 2. –> NDArray().Attach() --> When User wants to Feedback the same NDArray into the Runtime. Please share