* enable softmax op and add unit test

* move softmax sub-functions to softmax.cc, and move basic math functions to funcs.h

* migrate several ops:
  mean,
  mean_grad
  fill_constant
  square_grad
  elementwise_sub_grad
  mul_grad

* add sdg_op

* fix kernel platform registration issue

* code cleanup

* fix platform typo

* add fc unit test

* refine eigen fc
add cpu info, arm context
init packed sgemm

* enable packed sgemm

* add arm math

* pass fc ut

* follow comments

* code clean - refine ARM

cmake enhancement:

- add lite_cc_library and lite_cc_test

code clean:

- remove ARM feed and fetch kernels, reuse the Host's

remove unnecessary comments

* add cmake

* update

* fix proto pd

* fix compile

* tmp save

* fix protobuf device version

* fix protobuf and host compile

* fix std c++11 support on android

* change array to vector to fix ndk c++_static

* fix rt and add dockerfile

* fix android compile issue with latest merge

* init arm kernels

* enable run on arm

* update format

* update format

* update format

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make typesystem simpler

* reset drop local scope counter
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refine code

fuse cublas  calling and kernels into one cuda kernel.

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Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* Add conv2d_grad_grad_op
* Extracte the cuDNN conv algo searching code in conv_cudnn_helper.h.
    - Now use it in conv2d_grad_grad.
    - Will simply the searching code in conv2d and conv2d_grad in next PR.
* Enhance and fix bug in unit testing of gradient_checker.
* Support to fetch empty variables，return None in Python.

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1. infernce multi card occupy
2. facebox model inference occupy too much
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* test=develop
add elementwise_mod and elementwise_floordiv, fix equation problem in elementwise_mod

* fix train_from_dataset and infer_from_dataset example

* add inductive dim for data_reader, example: shape=[-1, 1], then -1 will be inducted through run-time reading of number of elements

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* Fix API example code of save_inference_model

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* Add "import" in exmaple of save_inference_model

* Fix typo "exsample" -> "example"

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* modified formula for lrn

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* modified api.spec

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* Refine elementwise kernel.

Add a simple cuda kernel if grad x and y both exist
Use 2D block cuda kernel to do broadcast.

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Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* refine code.

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Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* refine code.

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>