Installed through pypi

* Search PATH for DLLs

* Fix lint issue

* implement tuple pattern

* add tuple pattern

* lint;

* lint

* lint

* fix error

* fix

* add test

* save

* add test

* refactor

* fix indent

* save

* refactor

* Update from_source.rst

* Update deploy_ssd_gluoncv.py

* [Relay] enable NHWC of `relay.testing.mobilenet`

In this way, we can play around NHWC inside TVM regardless of
the frontends.

* [Test] test for NHWC of relay.testing.mobilenet

* initial conv2d_transpose

* correct select operator

* cleanup

* fix

* fix correcness check

* conv2d transpose declaration fix

* autotvm conv2d_transpose tuning script

* ir pass fix

* fix tuning script

* deriving params from env, adding bias

* removing bias comp from deconvolution

* lint

* fix

* lint

* lint

* turning off cpu

* lint, ops

* lint

* import fix

* removing hard coded values

* lint

* adding support for graphpack over multiply op

* increasing resnet model coverage

* fix indentation

* lint

* moving recursion limit fix into graphpack pass

* moving recursionlimit to relay init

* pooling on NCHWnc format

* adding more models

* deploy_resnet_on_vta.py

* trailing line

* generalizing to vision models

* merge conflicts

* fix, apply quantization to VTA only

* improving comments

* trimming models that have runtime issues for the moment

* lint

* lint

* lint

* init

* fix

* rework;

* `de10-nano` -> `de10nano`;

* fix compilation error;

* bug fix;

* Update install.md

* Update install.md

* Update install.md

* update with current runtime;

* add debug messages;

* bug fix in cma kernel module;

Rebasing. Empty commit.

Clang-format styling.

* [TENSORFLOW] Convert scalar Const into tvm.relay.const

* use _get_num_param() and _get_list_param()

* Add gradient implementations

* Add docstrings to fix lint errors

* test_darkent_bug

* test_darkent

* add resnext tests

* [VTA][Chisel] add scalafmt and format existing scala codebase

* change column width to 100

* add scalafmt conf file as a valid file type

* add asf header to scalafmt conf file and rerun formatter

* [VTA] Fix TSIM compile error in Linux (add missing -fPIC flag);

* [VTA] Fix TSIM compile error in Linux (add missing -fPIC flag);

* fix indentation problem;

This reverts commit 224cc243.

As GraphRuntime does not provide control-flow logics, we have to split
our model to two parts. While we need to share parameters between them
to save memory usage.

Solution:
1) add "lazy_init_input" in graph's attributes
   "attrs": {
     ... ...
     "lazy_init_input": [
       "list_str",
       [
         "p0"
       ]
     ]
    }
2) allow un-allocated NDArray entry in SetupStorage
3) utilize "set_input_zero_copy" function to set parameters

* fix

* lint

* init shape func in interpreter and vm compiler

* Update interpreter

* fix

* lint

* lint

* fix

* remove hack

* update

* fix

* fix

* update

* address comments & update for shape_of

* fix lint

* update

* fix hybrid

* lint

* fix bug & add take shape func

* lint

* lint

* update

* fix flaky test

* add todo

* Added arm_cpu NHWC schedules.

* Fixed kernel shape legalization.

* Added bitserial ops to relay.

* Snapshot and more missing files.

* Added dense testing.

* Added tests

* Added ASF header to new files.

* cc lint

* Pylint change.

* pylint fixes.

* Change arm legalize test.

* Added assert check to arm legalize.

* Added better documentation, fixed some bad style

* Reverted arm conv2d nhwc changes.

* [VTA][TSIM] add virtual memory support to tsim example

* fix identation

* remove USE_TSIM macro and use 32-bit addr instead