vvchernov commented on a change in pull request #10293:
URL: https://github.com/apache/tvm/pull/10293#discussion_r813703708
##########
File path: src/runtime/vm/vm.cc
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@@ -221,6 +211,9 @@ PackedFunc VirtualMachine::GetFunction(const std::string&
name,
} else if (name == "set_input") {
return PackedFunc(
[sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
SetInput(args[0], args, 1); });
+ } else if (name == "set_one_input") {
Review comment:
Yes, I use runtime module directly on native side. It is a reason why I
try to use `set_input` methods instead of direct using of `invoke`. The latter
requires to pack all input tensors to TvmArgs in certain sequence on native
side. For me it is more controlable and clear to input one by one tensor with
its tag (index or name). It is simultaneously the answer to your below
question. Nevertheless I agree that my patch was not full and I've extended
python API of VirtualMachine by `set_one_input` method. I observed that there
is no even `set_input` unit test. Unit tests are in progress.
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