* add conj op for complex types

* add conj for complex types

* add more test case

* add conj_op test

* modify conj api and impl

* add complex type for fill_constant_op xpu

* add setConstant for complex type

* remove complex conj test file

* user define grad for test_conj_op

* add test case for static mode of conj api

* modify conj doc

* change input args name to x

* remove useless codes

* conj support real types

* add conj test case for real number

* Start implementing int8 eltwise add

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* - Fix to Michal PR

* - Fix

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* - Lint fixes

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* - Added checking if elementwise_mul can be used

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* - Added attribs to skip_attrs_set

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* - Improved broadcasting

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- fixes to compilation

- fix

- fix

- Lint fixes

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* - removed redundant condition

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Co-authored-by: NMichal Gallus <michal.gallus@intel.com>

Those ops add the kernel message enhancement, as follows
paddle.fluid.layers.elementwise_add	
paddle.fluid.layers.elementwise_div
paddle.fluid.layers.elementwise_floordiv
paddle.fluid.layers.elementwise_max	
paddle.fluid.layers.elementwise_min	
paddle.fluid.layers.elementwise_mod	
paddle.fluid.layers.elementwise_mul	
paddle.fluid.layers.elementwise_pow	
paddle.fluid.layers.elementwise_sub

* MKLDNN v1.0 rebase to Paddle 1.6
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* Add hacky paddle::string::to_string() implementation

* vectorize<int64-t>() -> vectorize() cleanup
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* PADDLE_ENFORCE and void_cast fixes
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* Rebase changes
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* Cosmetics
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* Delete MKL from mkldnn.cmake
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* CMake debug commands
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* Delete MKLDNN_VERBOSE and rebase fixes
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* Rebase fixes
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* Temporarily disable int8 resnet101 vgg16 and vgg19 tests
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* Add libmkldnn.so.1 to python setup
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* Add libmkldnn.so.1 to inference_lib cmake after rebase
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* Post rebase fixes + FC int8 changes
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* Fix LRN NHWC
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* Fix NHWC conv3d
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* Windows build fix + next conv3d fix
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* Fix conv2d on AVX2 machines
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* Refactor MKL-DNN ElementwiseMul

remove manual fallback, remove format attrs
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* Refine PADDLE_ENFORCEs in eltwise_mul_op.h

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* Make ElementwiseMulOp inherit from ElementwiseOp

* Change type of simd_width to int

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* Remove Constructor extensions in ElementwiseOp and ElementwiseMulOp

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* Restore attributes

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* Fix test coverage for mkldnn eltwise mul

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* Conform to new is_run_common_broadcast API

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* Add UT for AreDimsAndFormatCorrect

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* paddle::framework::vectorize() templatization

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* update pybind/imperative.cc

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* revert update on unsqueeze_op.cc and warpctc_cudnn_op.cu.cc

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* using MKLDNNMemoryFormat = mkldnn::memory::format changes
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* PADDLE_ENFORCE update
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resolve #16764

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