* 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

test=debug

* 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

test=develop

MKLDNN conv + elementwise_add fusion: skip connection attribute renamed. Comments about patterns added.

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review fix

review from hshen14 fix

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fix error in broadcast and code cleanup

rename bias -> eltwise and added macro to shorten code

formatting

- Added draft of new operator

- Added fused embedding fc lstm files

- First time embedding_fc_lstm_fuse_pass was invoked in
  test_text_classification

- Added Embedding pattern

- Not crashing

- Enabled draft of embedding_fc_lstm pass (does it job)

- First working (Seqcompute only) version

- Removed diagnostic comment

- First enabling of BatchCompute

- Disabling pass for embedding with is_sparse and is_distributed

- Cosmetics

- Style

- Style