* [DOCS] add a solution to installation error

* Fix the command for updating submodules

* fix same var used in single op

* revert to older version

* initial NHWC layout support

* remove layout param from softmax

* more nhwc support

* fix typo

* add nhwc layout test

* fix lint

* update tvm

* update for c++ topi

* fix lint

* update tvm

The below compilation warning is fixed.

In file included from /mnt/D_DRIVE/work/nnvm_8_feb/dmlc-core/include/dmlc/any.h:16:0,
                 from include/nnvm/./base.h:11,
                 from include/nnvm/graph.h:15,
                 from src/compiler/fold_scale_axis.cc:6:
src/compiler/fold_scale_axis.cc: In function ‘nnvm::Graph nnvm::compiler::FoldScaleAxis(nnvm::Graph)’:
src/compiler/fold_scale_axis.cc:155:39: warning: enum constant in boolean context [-Wint-in-bool-context]
     CHECK(kind == kPassTroughFirst || kMulConsumer);
                                       ^
/mnt/D_DRIVE/work/nnvm_8_feb/dmlc-core/include/dmlc/./logging.h:110:9: note: in definition of macro ‘CHECK’
   if (!(x))

* Updated TVM version. Implemented fix for nnvm_compiler crash on exit on windows. Changed TOPI ops from using python to using C++ where applicable.

* Fix lint

* Fix lint

* Fix macro

* Fix reshape

* Update TVM to fix test fails

The below compilation warning issue has been fixed.

src/top/tensor/matrix_op.cc:37:21: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for (int i = 0; i < lshape.ndim() - 1; i++) oshape[i] = lshape[i];
                     ^
src/top/tensor/matrix_op.cc:38:21: warning: comparison between signed and unsigned integer expressions [-Wsign-compare]
   for (int i = 1; i < rshape.ndim(); i++) oshape[i + lshape.ndim() - 1] = rshap

Before Fix
************* 
************* Module nnvm._base
R: 21, 0: Disallow trailing comma tuple (trailing-comma-tuple)
R: 27, 0: Disallow trailing comma tuple (trailing-comma-tuple)

-----------------------------------
Your code has been rated at 9.99/

After Fix
************* 
siju@siju-DAEMON:~/D/Community/nnvm$ make lint
pylint python/nnvm --rcfile=/media/siju/DATA/Community/nnvm/tests/lint/pylintrc

-------------------------------------------------------------------
Your code has been rated at 10.00/10 (previous run: 9.99/10, +0.01)

x = np.transpose(img, (2, 0, 1))[np.newaxis, :]
TypeError: an integer is required

fix similar problem like https://github.com/apache/incubator-mxnet/pull/4589/files .

* [Convolution] Error while imported onnx model has weights.

Fix the use_bias based on the input parameters to use bias (Ex: sqeezenet). Ref #336

* Review corrections.

* add CacheItem2Schedule extension

* fix lint

* move function position

* make cache item visible to frontend

* add extern lib tutorial

* do fix

* Added test for adding down-/up-sampled layers

* Enabled test for adding down-/up-sampled layers

* Normalize whitespace

* Added elementwise-add test

* Fix typo

* Fixed elem-wise ops for lists with len>2

* add tutorial for mali gpu

* update submodule version

* fix doc error

* fix server error

* fix server in test

* Explain how to generate module library

* Small fix

* Add conv2d max_pool backward op

* Added tests

* Fix testing

* Address comments

* Change dot to matmul

* Address comments

* Break down indicator function

* Make greater, less numpy compatible

* Keras keeps renaming properties. Update frontend for keras 2.1.3 compatibility

* Add error message when inbound_nodes is not found

* [CI] turn on keras frontend test

* fix

* using tensorflow cpu version

* make shape inference of BatchNorm layout neutral

* refactor to use the axis variable to do BatchNorm shape inference

* refactor to use the axis variable to do BatchNorm shape inference

* add unittest to the axis param for batch norm shape inference

* Add support for keras upsampling

* Fix code formatting

* Fix indentation

* Fix indentation round 2

* Hide unused parameter

* Only enable UpSampling2D since the others are not currently supported by TVM

* Improve error messages and code layout

* add nnvm upsampling symbol

* add upsampling mxnet frontend

* add doc for upsampling op

* cleanup upsampling test

* minor fix

* use schedule_injective for upsampling

* upgrade tvm