* Add mkldnn bfloat16 option to C-API

* Add test for bfloat16 gpu

* Change coverage test

* Repair capi_gpu test

This reverts commit 02083bda.

* Add mkldnn bfloat16 option to C-API

* Add test for bfloat16 gpu

* Change coverage test

* - Disabling inplace pass

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- Disable cycles

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 - fix

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- Enhancement to in-place

- Lint fixes

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* - Lint fixes

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* Remove the NGraph engine from PDPD repository
1. Each operator was removed from the operator's directory
2. Each test was removed from the unittest directory
3. The parallel executor support was removed from the PDPD
4. The CMake file was removed from the PDPD
5. The NG flags were removed from the repository
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* Remove ngraph from:
1. Cmake file
2. Python file
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* add dynamic plugin support.
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* change emb eltwise layernorm to math function
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* add emb eltwise layernorm
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* can run dynamic shape ernie
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* fix ci
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* add ut for trt ernie dynamic

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* refine dynamic shape c++ interface.
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* fix comments
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* fix comments
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* 1. add embedding eltwise layernorm fuse
2. add embedding eltwise layernorm op
3. refine inplace_add_relu
4. refine fc_eltwise_layernorm
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* 1. refine fc
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* fix comments
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* fix comments

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* 1. optim multihead matmul: fuse three fc to multihtead matmul

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* fix conflict
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* fix comments
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* add gelu plugin

* align trt bert with gpu

* add support for fused fc with relu,

* add unittest for bert trt

* refine trt int8 for dynamic range set
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* refine trt int8
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* Add multihead fuse pass for ernie opt

* Refine softmax

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* Refine cuda kernel

* Refine cuda version

* Refine cmake

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* refine header file

* refine test case and pass
* refine comments

* Add ConvTranspose + BatchNorm fuse pass
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* Add tests for conv+bn and conv_transpose+bn passes
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* Add fc_elementwise_layernorm_fuse pass and unittest.

* Add fused_fc_elementwise_layernorm op and its GPU kernel.
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* Apply fc_elementwise_layernorm_fuse_pass to GPU inference.

* Add the setting of attrs in the definition of binary_op.
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* Add comment.

* Implement the unittest.
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* Change the unittest name of layer_norm.
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* Refine the codes related to fc op.

* Add GPU implementation for fc functor.

* Apply fc_fuse_pass in GPU inference.
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* Change the cmake for fc op.

* Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ.

* Add an attribute to set the activation type in fc_op.

* Enhance the unittest of fc_op.
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* Remove the declaration of FCOpGrad back to the header file.
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* Set default value for newly added arguments in test_fc_op.
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* Add a interface to enable cudnn for inference.

* Add cudnn_placement_pass.
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* Set the default value of cudnn_enabled_op_types to null.
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* Write the common basic class, placement_pass_base, to refine the codes.
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* Call EnableCUDNN in unittest.
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* Refine cudnn_placement_pass tester.

* Enable the testing of cudnn_placement_pass in inference's unittest.
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* Add the check of op kernels.
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* Add simplify_with_basic_ops_pass to replace dropout_op with scale_op when is_test is true.
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* Delete dropout_op directly when upscale_in_train is true.
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* Improve the debug string, adding the print of op_desc information.

* Fix the case when dropout's input x is reused as the next op's output.

* Add the pass to inference.
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* Change the log level.
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* Add unittest for inplace case.

* Add comment to explain the pass.

* Apply the pass for CPU inference.
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* Fix the typo.
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* Add the check of AttrType.
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* fix mask rcnn bug:
1. affine channel fuse (diff)
2. condition block op (memory leak)
3. merge lod tensor op (diff)
4. memroy optim (diff)
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* fix ci aboud PADDLE_ENFOCE
fix merge lod infer op ut
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* add fusion_seqpool_cvm_concat test=develop

* simplify pass, test=develop

* fix code style, test=develop

* update paddle-trt for:
    1. fix bug: when batch > 2, core in split plugin.
    2. add leaky_relu trt5.0 support (yolov3 from 65ms to 42ms.)
    3. add new attr to dropout.
    4. shuffle channel, swish, relu6 support
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* 1. fix ci
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* - changes to graph detector

- Changes to pass

- Added ut for new pass

- use_pass

- Added pass to mkldnn passes

- fix to registration

- improved verbose messaging for conv bias passes

- Lint fixes

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* - Lint fixes

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* fluid int8 train and trt int8 predict align.
trt int8 predict init
op converter

* 2. align fluid int8 train and trt int8 inference.
enhance quant dequant fuse pass
enhance op converter, trt engine, trt engine op, trt subgraph pass.

* 3. add delete_quant_dequant_pass for trt

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* 4. add the missing file
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* 5. i modify the c++ interface, but forget to modify the pybind code
fix the IS_TRT_VERSION_GE bug, and fix elementwise op converter
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* fuse mul and elementwise add to fc

* Reimplement the FC forward operator

* Fix FC MKLDNN integration by transposing weights

* Add FC MKLDNN Pass

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* FC MKLDNN Pass: change memcpy to std::copy

* Fix MKLDNN FC handling of mismatch input and weights dims

* Lower tolerance for MKL-DNN in resnet50 test

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* Adjust FC to support MKLDNN Op placement

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* Adjust Placement Op to set use_mkldnn attribute for graph

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* MKLDNN FC: fix weights format so that gemm version is called

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* FC MKLDNN: Remove tolerance decrease from tester_helper

* FC MKL-DNN: Refactor the code, change input reorder to weight reorder

* MKL-DNN FC: Introduce operator caching

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* FC MKL-DNN: Fix the tensor type in ExpectedKernelType

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* FC MKL-DNN: fix style changes

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* FC MKL-DNN: fallback to native on non-supported dim sizes

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* FC MKLDNN: fix CMake paths

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* FC MKLDNN: Refine placement pass graph mkldnn attribute

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* Fix Transpiler error for fuse_conv_eltwise

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* Fix missing STL includes in files

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* FC MKL-DNN: Enable new output size computation

Also, refine pass to comply with newest interface.
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* FC MKL-DNN: enable only when fc_mkldnn_pass is enabled

* FC MKL-DNN: Allow Weights to use oi or io format

* FC MKL-DNN: Adjust UT to work with correct dims

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* Enable MKL DEBUG for resnet50 analyzer

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* FC MKL-DNN: Improve Hashing function

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* FC MKL-DNN: Fix shape for fc weights in transpiler

* FC MKL-DNN: Update input pointer in re-used fc primitive

* Add log for not handling fc fuse for unsupported dims

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* FC MKL-DNN: Move transpose from pass to Op Kernel

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* FC MKL-DNN: Disable transpose in unit test

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* FC MKL-DNN: Remove fc_mkldnn_pass from default list

* Correct Flag for fake data analyzer tests

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* FC MKL-DNN: Add comment about fc mkldnn pass disablement

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* FC MKL-DNN: Disable fc in int8 tests

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* add conv_concat_relu fuse

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* add test code

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* added missing include with unordered_map

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* review fixes for wojtuss

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* remove 'should (not) be fused' comment statements

one of them was invalid anyway

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* Relu6 is the bottleneck op for Mobilenet-v2. As the mkldnn supports the conv/relu6 fusion, we implement it fusion via cpass way. Due to the int8 enabling for this fusion will be supported in MKLDNN v0.20, so this PR is focused on the fp32 optimization.

Below table shows the benchmark(FPS) which measured on skx-8180(28 cores)
Batch size | with fusion | without fusion
-- | -- | --
1 | 214.7 | 53.4
50 | 1219.727 | 137.280

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* Fix the format issue

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* Add the missing nolint comments.

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* Fix the typos.

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* Register the conv_brelu_mkldnn_fuse_pass for the MKLDNN engine.

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* Adjust the indentation.

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* Add the test_conv_brelu_mkldnn_fuse_pass case.

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* Slightly update the code per Baidu comments.
Let the parameter definition embedded into the code.
That's will make the code easy to understand.

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