* fix cuda building, test=develop

* remove sequence_pool from cmake because build error, test=develop

* add sequence_pool cuda kernel, test=develop

* fix sequence_pool cuda,test=develop

* fix and complete unittest, test=develop

* fix macro of sequence_pool cuda, test=develop

* fix x86 search_grnn and add unit test
* add cuda search_grnn and unit test

* add stack op and its unit tests, test=develop

* [ARM] sgemv support transA, test=develop

* add sgemv ut, test=develop

* add sequence_pool cuda kernel, test=develop

* fix sequence_pool cuda,test=develop

* fix and complete unittest, test=develop

* add cuda ci building, test=develop

* update comments, test=develop

test=develop

* add x86 op and kernel : search_fc and sequence_topk_avg_pooling   for content-dnn model test=develop

* [X86] add attention_padding_mask op, x86 kernel and unit test

test=develop

* [CUDA] add attention_padding_mask cuda kernel and unit test

test=develop

- add var_conv_2d cuda kernel

- add var_conv_2d cuda kernel unit test

- temporarily set to two input mode, remove input(ROW) and input(COLUMN)

* Fix bug target for kHost and kARM not equal. test=develop

* Fix license. test=develop

* add debug -g option. test=develop

* enable opencl demo. test=develop

* Fix model_optimize_tool found no opencl kernel. test=develop

* add more vlog. test=develop

* remove macro LITE_WITH_OPENCL, LITE_WITH_FPGA in passes. test=develop

* Fix valid_places in mobilenetv1_test. test=develop

* Fix bug of find no real output of fetch, after tool OPs of optimzer passes. test=develop

* Fix vlog as log message in model_optimize_tool. test=develop

* fix miscs. test=develop

* fix comment. test=develop

* Fix misspell of opencl, fpga kernels name in lite/api/CMakeLists.txt. test=develop

* add opencl macro in full_api of demo. test=develop

add sequence_pool cuda kernel

add search_group_padding op and x86 kernel

* [X86][CUDA] add sequence_arithmetic op , x86 kernel, cuda kernel and unit test

test=develop

* add sequence_arithmetic cuda kernel unit test

test=develop

* add cuda match_matrix_tensor op and test, test=develop

* add search_seq_depadding x86 and cuda
* add match_matrix_tensor x86
* add search_grnn x86, no test

fix the cuda bilinear and nearest precision caused by data type conversion. 

- add var_conv_2d op

- add var_conv_2d x86 kernel

- add var_conv_2d x86 test

* fix the compile error for cuda and fix unit test

* fix conv kernel bugs and open mobilenet ci test=develop

* update lookup_table arm x86, test=develop

* add lookup_table_v2_op for compatibility, test=develop

- add sequence_reverse op

- add sequence_reverse kernel for x86 and cuda

- add sequence_reverse_test for x86 and cuda

* add cast op for x86 platform

* alter the struct to class to hide the data and alter the pointer

- add sequence_concat op

- add sequence_concat kernel for x86 and cuda

- add sequence_concat_test for x86 and cuda

align the lite nearest， bilinear op to fluid on arm and cuda

* 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

mv deviceinfo.workspace and other relative member to thread_local_storage

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

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.