During tensorize, call Simplify on algorithm and intrinsic definitions before CanonicalSimplify. This will prevent a number of false tensorize mismatches. (#718)

thanks, this we can use this solution for now 

* 1) removed non-determinism from CanonicalSimplify
2) added couple of testcases for CanonicalSimplify

* Use IRDeepCompare instead of comparison of string representation

* Give a warning (instead of fatal error) when two "ComExprEntry"s are equal

* Simplify expressions early on

* fixed lint errors

* 1) Refactored some parts of the unrolling code into their own methods so we can reuse unrolling functionality in other parts of the code. E.g., to explicitly unroll loops with count of 1 when they are programmatically created.
2) Reorder based on top operator before resorting to pointers, which causes non-determinism.

* Fixed lint errors

* Use long long for platforms where long is 32 bits (like windows).

* Make sure scalar chars are signed.

* Re-add NOLINT marker.

* [CODEGEN] add fp16 and fp64 enable pragma for opencl

* fix style

* Port build_module.py to C++

* Fix lint errors

* Fix more lint errors

* Fix more lint errors

* Fix more lint errors

* Fix build error

* Implemented style fixes

* Fix lint errors

* Added function to construct target from string
lower now returns array

* Fix lint error

* Implemented review changes - style & Target options -> std::vector

* Fixed lint, argument alignment and added unit test

* Changed test to target LLVM, fixed sign compare warnings

* Reverted unit test to CUDA, changed Jenkinsfile to enable GPU for C++ tests

* Slight change to Jenkinsfile

* Changed build_module test from CUDA to LLVM

* Added function var() to construct a Var instance.
Changed implementation of LLVMEnabled()

* Reverted Jenkinsfile

* [CI] Enable llvm in CPU test

* fix llvm

* Support rank-0 tensor

* fix lint

* [RANDOM] Init contrib.random library

* [RANDOM] Add uniform

* [RANDOM] Fix lint

* [RANDOM] Add comments and tests

* [RANDOM] Fix lint

* [CUDA] Enable int64

* [PYTHON] Fix rpc tutorial with opencl

* OK

* update

Change the parameter 'C' name

In unroll_loop.cc the parameter name is "auto_max_depth", but in ir_pass.h the parameter name is "auto_min_depth"

* [RPC][JVM] Remove binary dist gradle from repo

* fix header

* [PASS] Allow compact checking when strides is available

* remove assert compact

Readability.

* [PASS/SETUP] Fix minior issues

* fix lint

* mps

* update

* scheduler tweaked for super resolution perf

* conv2d_transpose schedule error fixed

* nnvm issue #239 fixed

some host opencl runtime may at cpu mode, but remote

client opencl runtime at gpu mode, compat it

* scheduler tweaked for super resolution perf

* lint error fixed

* lint error fixed

* conv2d_transpose schedule error fixed

* [TOPI] Add out_dtype argument for conv2d; Add x86 schedules

* Fix

* Fix lint

* Fix

* conv2d perf improved for conv2d_56_64_128, test name added to differentiate workloads

* fix lint error

* Make the tvm conda package build with in-place source and use cmake from conda.

* Add a package for topi.