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* Int8: Fix Pooling output scale

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* Update scales quantization for certain operators

These include: concat, transpose, pool and reshape. test=develop

* Move concat minimum scale finding to quantizer

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add prior_box quantization code

add scale algo rules for prior box

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* some fixes for int8 mobilenet_ssd tester
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* change wrong data file name
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* change test images bin file from 200 images to 100 images

* change directory existence to file existence during downloading
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* reuse download_data
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* run full dataset when iterations=0
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* fix issue 18111;test=develop

* fix timer;test=develop

* refine code;test=develop

* fix spelling errors; test=develop

* Update API.spec

update md5

* Update API.spec

* change the order of api;test=develop

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* reuse C-API INT8 unit test application

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* updates after review

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* add pascalvoc preprocess script and mobilenet-ssd analyzer_tester, wait 17737

* change converting local dataset to downloading and converting tarfile
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* change the test data_path
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* change copyright (c) 2016 to copyright (c) 2019
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* update anakin-engine interfaces for content-dnn

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* support only-gpu mode of Anakin

modify eltwise parse

test=develop

* 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

test=develop

* 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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* fix: when use the load model from memory mode, the RAM occupy is high

test=develop

* ligth mem reuse
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* fix cpplint
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* refactor PR 16865

* delete mergetool files

* test=develop

* test=develop

* test=develop

* test=develop

* create dir for int8 model before call SaveOptimModel

* test=develop

* mkldnn int8 only support linux; test=develop

* refine code; test=develop

* remove comment; test=develop

* refine code; test=develop

* fix bug; test=develop

* add exception for mkldnn_post_training_strategy

* reuse int8v2 CAPI dataset; test=develop

* fix accuracy check bug; test=develop

* remove tab

* convert files to unix format

* test=develop

* reduce CI time;test=develop

* reduce CI time and refine code;test=develop

* refine comment; test=develop

* add cmake FLAGS;test=develop

* remove predict_num;test=develop

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* add INT8 conv+relu6 fuse and enbale mobilentv2 INT8 test
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* change fasle and 0.0 to fuse_brelu and brelu_threshold
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change the "fuse_relu||fuse_brelu" to "unsigned_output"
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* Use relu instead of brelu as INT8 post-op because INT8 brelu is not enabled in mkldnn v0.18
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* continuous-integration fix
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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

test=develop

* - Lint fixes

test=develop

* add Concat quantization
add unit test for quantizing concat
fix for wrong value when the input is not in map of calculated scales
add use_quantizer to concat_op.cc
add scale_algo rules for concat

test=develop

* missing fix for multiple inputs quantize-squash

* wojtuss review fix: adding comment

test=develop

* fix the bug that sub_scope_ may be null in AnalysisPredictor::Run.

* add more directions about io APIs' docs.

* update the API.spec. test=develop test=document_preview

* Revert "Revert "Fix allocator bug""

This reverts commit 174d0d0b.

* Revert "fix travis ci"

This reverts commit 5656fa9f.

test=develop

* add inlined_vector.h, test=develop

* add inlined_vector_test,test=develop

* clean code of allocator,test=develop

* delete zero_size_allocator.h,test=develop

* fix failed unittest,test=develop

* 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

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

test=develop

* Adjust FC to support MKLDNN Op placement

test=develop

* Adjust Placement Op to set use_mkldnn attribute for graph

test=develop

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

test=develop

* 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

test=develop

* FC MKL-DNN: fix style changes

test=develop

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

test=develop

* FC MKLDNN: fix CMake paths

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* FC MKLDNN: Refine placement pass graph mkldnn attribute

test=develop

* Fix Transpiler error for fuse_conv_eltwise

test=develop

* Fix missing STL includes in files

test=develop

* FC MKL-DNN: Enable new output size computation

Also, refine pass to comply with newest interface.
test=develop

* 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

test=develop

* FC MKL-DNN: Improve Hashing function

test=develop

* 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

test=develop

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

test=develop

* FC MKL-DNN: Disable transpose in unit test

test=develop

* FC MKL-DNN: Remove fc_mkldnn_pass from default list

* Correct Flag for fake data analyzer tests

test=develop

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

test=develop

* FC MKL-DNN: Disable fc in int8 tests

test=develop

* add conv_concat_relu fuse

test=develop

* add test code

test=develop

* added missing include with unordered_map

test=develop

* review fixes for wojtuss

test=develop

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

one of them was invalid anyway

test=develop

* fix quantize_squash_pass segfault when there is no tensor linked do Bias input

test=develop

* add googlenet test

test=develop

* fix concat CreateKey not using input format

test=develop

ban all trt ut. will fix it later.

test=develop

* modify saved model path in analyzer_save_model.cc test=develop

* 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

test=develop

* Add the missing nolint comments.

test=develop

* Fix the typos.

test=develop

* Register the conv_brelu_mkldnn_fuse_pass for the MKLDNN engine.

test=develop

* Adjust the indentation.

test=develop

* Add the test_conv_brelu_mkldnn_fuse_pass case.

test=develop

* 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

test=develop

* Add 6 models tests support in CMake

* enabling resnet101, vgg16, vgg19 INT8v2 model tests
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* remove SERIAL
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http://newicafe.baidu.com:80/issue/PaddleSec-33/show?from=page
http://newicafe.baidu.com:80/issue/PaddleSec-28/show?from=page
http://newicafe.baidu.com:80/issue/PaddleSec-25/show?from=page
http://newicafe.baidu.com:80/issue/PaddleSec-24/show?from=page
http://newicafe.baidu.com:80/issue/PaddleSec-21/show?from=page
http://newicafe.baidu.com:80/issue/PaddleSec-20/show?from=page

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