test=develop

update embedding_eltwise_layernorm fuse pass and fused kernel, to support multi input

* add skip_layernorm pass. test=develop

* 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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当一个模型中有多个fc_lstm子图的时候，且其中fc共用了同一个persistable的bias，此时不应该将bias节点删除，只将非persistable的节点去除即可。

* Add the first implememtation of fusion_group op #19621 (#3)

* Add the dynamic load of nvrtc, and support runtime compiling of CUDA kernel using nvrtc.
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* Call CUDA driver api to launch the kernel compiled by nvrtc.
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* Disable for mac and windows.
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* Refine the codes to support manually specified num_threads and workload_per_thread.
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* Refine the CUDA kernel to support large dims.
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* Add DeviceCodePool to manage all device codes.

* Add the first implementation fusion_group op.

* Add unit-test for fusion_group op.

* Add the check of result.

* Add the check of nvrtc in unit-test.
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* Add comment to explain the inputs, outputs and features of fusion_group op.
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* Disable fusion_group op for mac and windows.
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* Make the compiling of device code return status instead of hanging up.
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* Add the check of whether there is CUDA driver library, and do not core dump when failing to call the CUDA driver API.

* Unify fusion_group_op's input and output names.
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* Add the check of CUDA driver library in unittest.
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* Enable generating code for a given subgraph. #21126 (#4)

* Enable generating code for a given subgraph.

* Support sorting the subgraph.

* Remove the rearange of expressions because we use the sorted subgraph directly.

* Enable generating code for a subgraph which is composed of grad ops.

* Use expression information to check the accuracy in unittest.

* Separate load and store from computation expressions.
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* Improve the loading statements in generated codes.
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* Remove unused arguments from formal list.
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* Enable the detection of subgraph of grad ops.

* Generate code for detected subgraph in fusion_group_pass.

* Add an option in BuildStrategy to enable fusion_group_pass and add unittest.
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* Fix a bug when checking whether the shape of all inputs are the same.

* Add debug information.

* Remove subgraph_detector from inference/analysis to the common framework/ir directory. (#5)

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* Call subgraph_detector in fusion_group pass.
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* Disable fusion_group when WITH_GPU is OFF.
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* Refine all PADDLE_ENFORCE message.
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* Fix the case that some inputs are not defined in grad ops, and set op_role for fused op.
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* Follow review comments.
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* add bn and relu fuse pass

* add op attr assert and dtype assert

* fix some inputs&&outputs bugs for the fused op and pattern.

* add the unittest for fuse_bn_act_pass. test=develop

* use normative enforce statements. test=develop

* add the cpu test. test=develop

* add the support of batch_size=1 for the bn with relu op. test=develop

* add the error type for paddle throws. test=develop

* add fused_batch_norm_act and fused_batch_norm_act_grad to op_has_unsed_vars_white_list. test=develop

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* Disable fusion_group pass for windows and mac. We will do some experiments on Linux first.
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* Print the subgraph when check failed.
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* Add fusion_group_pass and elementwise pattern.

* Rewrite the detector of elementwise group.
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* Add a comment in codegen.

* Add more unittest cases.
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* Move code_generator related code to fusion_group directory.

* Correct the including path.

* Add the definition of SubGraph and finish the insert of fusion_group op in pass.

* Insert graph_vis_pass in tester to visualize the graph for debug.

* 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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* codegen code for reconstruction test=develop

* fix the cmake test=develop

* fix review advice test=develop

* 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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* Enhance fc_fuse_pass to enable fusing relu.

* Allow print the shapes of var_desc in graph.
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* Enhance fc_fuse_pass_tester.

* Remove the use of PADDLE_ENFORCE.
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* Correct the number of ops after fusing.
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* Fix a typo.
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* Set activation_type to null when there is no relu in fc.
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* Refine fc_fuse_pass's codes.

* Enable the set of shape for tensor.

* Refine repeated_fc_relu_pass and add unittest.
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* test=develop codegen for fused elementwise operation

* fix test=develop

* 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

* support sparse gradients
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* update anakin-engine interfaces for content-dnn

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* support only-gpu mode of Anakin

modify eltwise parse

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* modification for thread-safe

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* Integrated template instance

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* increase template parameters

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* support MLU predictor

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* update anakin cmake files

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* update TargetWrapper::set_device

* update the initialization of anakin subgraph

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* use the default constructor of base class

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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

test=develop

* 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

test=develop

* 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

test=develop

* 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

test=develop

* 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

test=develop

* 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.

test=develop

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* move pass to ir

* polish code
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* fix dependency
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* cherry-pick commit from 88770542

* cherry-pick commit from 3f0b97df

* cherry-pick from 16691:Anakin subgraph support yolo_v3 and faster-rcnn

(cherry picked from commit 8643dbc2)

* Cherry-Pick from 16662 : Anakin subgraph cpu support

(cherry picked from commit 7ad182e1)

* Cherry-pick from 1662, 16797.. : add anakin int8 support

(cherry picked from commit e14ab180)

* Cherry-pick from 16813 : change singleton to graph RegistBlock
test=release/1.4

(cherry picked from commit 4b9fa423)

* Cherry Pick : 16837 Support ShuffleNet and MobileNet-v2

Support ShuffleNet and MobileNet-v2, test=release/1.4

(cherry picked from commit a6fb066f)

* Cherry-pick : anakin subgraph add opt config layout argument #16846
test=release/1.4

(cherry picked from commit 8121b3ec)

* 1. add shuffle_channel_detect

(cherry picked from commit 6efdea89)

* update shuffle_channel op convert, test=release/1.4

(cherry picked from commit e4726a06)

* Modify symbol export rules

test=develop

refine trt first run
add quant dequant fuse pass
omit simplify_anakin_priorbox_detection template
omit transpose_flatten_concat_fuse template
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test=develop

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