@masahi, for other ops, pad can support any dimentions. I am looking at
pooling, it seems there would be some works, current pooling [implementation
](https://github.com/apache/incubator-tvm/blob/ba9d96bcb585557d4d3dbee40112367b08b28084/topi/include/topi/nn/pooling.h#L61)only
supports 2D. I am
# New Features
### Relay in Production
Relay is a functional, differentiable programming language designed to be an
expressive intermediate representation for machine learning systems. Relay
supports algebraic data types, closures, control flow, and recursion, allowing
it to directly represent
Hi @junrushao1994 , Thanks for the comments! :) I will get back to you about a
real world example as soon as possible.
But generally speaking, dead code elimination pass is required in some
workloads; and after TVM output program with intrinsics and not even targetting
CPU or GPU, LLVM or other
Hi,
Thank you for your detailed proposal! I think the design of data flow analysis
works for general cfgs.
However, I think I am not knowledgeable enough to understand the motivation and
use cases of liveness analysis in TVM IR. Could you kindly give a real-world
example how it may help analyz
### Comments: IsLattice
The basic usage is just:
```cpp
template
struct STD_SET_IS_LATTICE : public IsLattice> {
using SET = std::set;
public:
SET join(const SET& a, const SET& b);
SET meet(const SET& a, const SET& b);
const SET& top();
const SET& bottom();
bool equal
Hey, there is a similar RFC on the
topic(https://github.com/apache/incubator-tvm/issues/4449).
cc @gussmith23 @zhiics @jroesch @MarisaKirisame @icemelon9 @slyubomirsky
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# Problem
When developing program passes on TVM IR (the one once was Halide IR), it is
normal to ask for all sorts of information requiring program analysis, for
example, live variable analysis for dead code elimination. This requirement
becomes urgent when TVM has to directly issue intrinsic a
cc @jwfromm @jroesch @soiferj
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