* add coreml

* fix bool

* fix flatten in fullyconnected

* fix duplicate flatten

* fix syntax

* add tutorial

* fix mxnet flatten, fix tutorials

* fix flatten issue

* fix lint

* resnet example merged to imagenet

* resnet example merged to imagenet

* merge with master

* merge with master

* cuda imagenet benchmakr added

* benchmark syntax fixed

* [TEST] include coreml tools in docker

* upgrade tvm

* [BENCH] Add Benchmark for Rasp

* [BENCH] Add arg opt-level

* [BENCH] Add model choices

* [BENCH] Improve

* [TUTORIAL] Deploy the Pretrained Model on Raspberry Pi

* [TUTORIAL] Improve

* [TUTORIAL] Improve

* [TUTORIAL] Improve

* [TUTORIAL] Improve

* add json spec intro

* fix error

* fix name attrs

* rename and move to top

* address boolean values

* update title

* update

* back to color

* [TUTORIAL] ImageNet Inference on Raspberry Pi

* Update tvm

* [PASS] FoldScaleAxis

* Move FoldAxis to O3

* Set unroll to 0 when ready

* add transform

* fix

* update doc

* Update tvm

* [TEST] Xavie initialization for benchmarks

* remove additional line

* use resnet v2

* fix

* add onnx

* fix

* [Tutorial] mxnet

update

add from_gluon

add to __init__

fix tutorial and from_gluon

fix doc lint

merge from_mxnet

fix

fix

fix tutorial

fix

fix header

* fix tutorial

* fix data

* fix

* resnet example merged to imagenet

* merge with master

* init onnx

finish onnx frontend

add onnx tests

fix various

backup

use transformer

[Frontend] graph passed

add test forward

test forward

fix doc and lint

fix test graph tuple

from_onnx now take 2 args, output (sym, params)

fix rename

fix input names

fix multiple

fix lint

fix lint check

* better doc

* [TUTORIAL] Move mobilenet to tutorial, fix precompute_prune

* Some language improvements

* register pool, global_pool; add mobilenet example

* tests of pool and global_pool

* use new API of runtime module

* small fix