* fc-dequantize squash
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* change according to reviews
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* change PADDLE_ENFORCE
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* add second test when fc-dequant do not fuse
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* change all related PADDLE_ENFORCE
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* Add reshape int8 op

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* Change test to CPUPlace

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* Correct tests

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* Implement Int8 FC

* Integrate FC into INT8v2

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* int8 FC: transpose weights before computing scales

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* Add support for activation_type string in FC

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* Disable MKL-DNN's FC in VGG16 and 19

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* Disable FC quantization when mkldnn FC is disabled

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* Solve PADDLE_ENFORCES in FC int8

* Fix Paddle enforces and remove const cast

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* Fix style changes

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* Fix quantizer_tester test and add fc quantization

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* Fix FC test fail on CUDA

* Remove unnecessary log from quantize placement pass

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* Add Thread ID to FC hash key

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* Add comments to MKL-DNN FC Kernel

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* Refactor quantizer

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* Fix linter issues

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* Fix crash in slim googlenet

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* Fix PADDLE_ENFORCE messages

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* Add transpose2 INT8 for mkl-dnn

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* Fix test_transpose_int8_mkldnn

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* Revert "Merge branch 'develop' into transpose_int8_mkldnn_2"

This reverts commit 34011bdb, reversing
changes made to 2ce6473f.

* Revert "Revert "Merge branch 'develop' into transpose_int8_mkldnn_2""

This reverts commit 23754dd7.

* Add template to TransposeMKLDNNHandler

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* Resolve conflict

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* Restore get_size and refactor

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* Add ConvTranspose + BatchNorm fuse pass
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* Add tests for conv+bn and conv_transpose+bn passes
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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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* Add generalized Conv+Activation MKLDNN fuse pass creation Part2
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* Undefined behaviour of GetAttrIfExists<> FIX
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* Add requantize squash

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* Add more precise tests
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* REname and REfactor tester

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* Fix Mask rcnn predictor
    1. refine memory optim algorithm to support the model with the block op.
    2. output diff : modify the affine channel fuse
    3. add condition_block_infer op
add interface for setting trt calib table dir
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* add the missing files.
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add prior_box quantization code

add scale algo rules for prior box

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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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* 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

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* missing fix for multiple inputs quantize-squash

* wojtuss review fix: adding comment

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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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* 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

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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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* Add cpu_quantize_pass for C-API quantization

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* add cpu_quantize_pass test

* fix lint: add include memory unorderd_map and unordered_set

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* fuse_relu 1

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* tuned 2 without squash

* fixes

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* remove unused vars

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* refactored

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* fix lint c-style cast -> C++ style cast

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* remove QuantMax and c style casts

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* last usage of QuantMax removed

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* Fix Analysis Predictor UT

Check if memory_optimize_pass has already been added
to the analysis config before adding a new one, so
that it is not added multiple times.
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* change map to unordered_map

fix the forgotten part of cpu_quantize_pass_tester.cc

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* removed quantized attribute

* fixed cpu_quantize_pass_tester and op attr comments

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* removed redundant line

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* removed gmock

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* fix after merge

* Add cpu_quantize_squash_pass for C-API quantization

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* add cpu_quantize_squash_pass teste

* fix lint: add include memory unorderd_map and unordered_set

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* lint fix 2

* fixes

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* refactored

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* fix windows ci

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fix conv+elemenwise fuse bug.

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(test=develop)

* implements reachability check between identity node and non-identity argument to elementwise_add
* implements handling identity node as x and as y argument to elementwise_add

MKLDNN conv + elementwise_add fusion: UT for missing bias added. UTs refactored. Some minor changes in the pass

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