* [RUNTIME] Enable extension type to PackedFunc.

* More comments

* [RUNTIME][RPC] Enable remote linking of device code.

* fix build

* [SCHEDULE] Enahance cache_write to enable layout change.

* more tests

* [SETUP] Always use relpath for setup

* [CMAKE] Fix cmake llvm build

* [SCHEDULE][PASS] support storage_align of certain axis

* fix lint

* [CODEGEN] NVPTX backend.

* Fix pylint

* use fix

* v2: runtime support for rocm

* fixed coding space errors

* removed kROCM from c_runtime_api.h

* [BUILD][LLVM] Support LLVM mainline 5.0 6.0

* Reduce parallelism

* [NNPack] Support for threadpool

* fix lint

* fix lint

* Use static class function

* [Contrib] CuDNN v7 Support

* Add test

[TOPI] Add broadcast and reduce operators

* [WIP] C++ topi contributions

Summary:
This diff implements C++ topi contributions for:
  - relu with parametrix threshold
  - pad with generic padBefore / padAfter specification
  - matmult with transposes
  - conv2d_nchw, conv2d_hwcn with runtime constant padding and strides
  - depthwise_conv2d_nchw with runtime constant padding and strides
  - group_conv2d_ngchw with runtime constant padding and strides
  - broadcast_to a broadcastable shape
  - broadcast_bop where bop is an usual binary op (+ - * / %)

Convolution padding is implemented using the pad operation.
To avoid extra memory consumption, it is generally recommended to inline the padding with the autoinliner.
Unfortunately in its current form the elemwise checks are too restrictive to allow inlining.
So this diff also proposes an extension to LHS injective (i.e. no reduction axis in the current IR design)

Test Plan:
Tested in C++ testsuite in a separate repository, I am looking for suggestions to quickly spin up some tests for tvm.

Reviewers: tqchen

Subscribers:

Tasks:

Tags:

Blame Revision:

* Review + Lint + GSG C++

* [PASS][FIX] Fix LiftAttrScope with if

* [PASS] Fix on proc sync

* fix

* [TEST] Upgrade gpu docker to cudnn7

* fx

* [RUNTIME][PASS] Allow declare vector type array

* fix bcast

* [BUFFER] Enable vload/store function in buffer

* ok

* [NNPACK] Add nnpack.convolution

* Add instrinsic

* Fix lint