* test=develop

* fix code_style test=develop

* test=develop

* test=develop

* fix code_style test=develop

* fix code_style test=develop

*test = develop

2. [bm] finish build related files

* add cv image process

* fix arm liunx build error

* add LITE_WITH_CV defien to make cv, test=develop

* fix cv format, annd add describe in utils/cv

* delete some Meaningless comments, test=develop

* set LITE_WITH_CV=OFF in build.sh, test=develop

* delete cv_enum.h in utils/cv, push the contents in cv_ennum.h to paddle_image_preprocess.h, test=develop

* according to reviews to redefine paddle_image_preprocess.h, test=develop

* add detailed note of flipParam, test=develop

* fix format in paddle_image_preprocess.h, test=develop

* fix error when build x86. test=develop

* lite_with_X86 does not contain lite_with_cv

* update concat and unsqueeze, test=develop

add cuda kernel:lookup table

* fix pooling bug and speed

* fix build error

* delete VLOG in pool, test=develop

* add openmp, test=develop

* fix lite/kernels/arm/pool_compute_test basic_pooling compute error bug, test=develop

* move multiclass_nms kernel back to host test=develop

* move layer_norm OP and arm_kernel into extra type since it's added after release/v2.0-beta1 and not related with CV test=develop

* fix code_style test=develop

[LITE][NPU] Add fusion_elementwise_add_activation bridge, remove the limitation of the dimensions of input tensors in the graph compute kernel, and refine log message (#2395)

test=develop

fix jit::matmul bug. Input x shape is (m, k), weight shape is (k, n). When k < 512, m==1, and n is a multiple of 16, the weight pointer is not correctly updated in the group calculation in the implementation of jit::matmul, resulting in the result diff 

mv deviceinfo.workspace and other relative member to thread_local_storage

* Add CMAKE_BUILD_TYPE check for strip. test=develop

We have changed 11 arm_kernels into extra type in #2347 , which has caused test_compiling failure. In this PR , we move their 11 related arm_kernel_test into build_extra=ON

* add channel_wise_dequantized_max_abs op and ChannelWiseDequantOpFuser, test=develop

update reshape op to support multiple input types of shape.
priority: input(ShapeTensor) > input(Shape) > attr(shape)

update slice op to support multiple iput types of starts and ends.
priority: input(StartsTensor) > input(StartsTensorList) > attr(starts)

fill_constant kernel only registered float type, only the float data type is produced, which is obviously a bug.

Now, produce data based on the data type attr.

By the way, fix the cast kernel bug.

* fix: fix omp thread bug

* fix: fix compile android level & test=develop

* fix: fix omp bug

* fix: fix omp bug
test=develop

test=develop

* fix step rnn model run bugs test=develop

* move some basic ops into extra type to reduce library size test=develop (#2347)

* [XPU] add batchnorm op bridge and unit test

test=develop

* fix DMLC_USE_GLOG

test=develop

fix buf: model_optimize_tool can not compile preperly on mac environment (#2326)