* Enable less_than ngraph operator

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* Added compare unit-tests test=develop

* Update: date && removed import test=develop

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* add depthwise_conv2d test=develop

* use cpu for ngraph test=develop

Optimize the concat and split kernel for specical cases when the number of inputs/outputs is 2 (#17415)

* Optimize the concat and split kernel for special cases that the number of inputs/outputs is 2.
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* Refine codes.
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* Correct the condition.
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* Move the define of tmp_data outside the if statement.

* Print the cudnn minor version.
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* Fix the case when in_num/o_num is 1 in concat/split op.
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* Remove const_cast.
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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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This reverts commit f34830e2.

* Enable sqrt operator for the nGraph Bridge.

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* Update activation_op.h

* 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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test=develop

* enhance print

* Revert "Revert "Fix allocator bug""

This reverts commit 174d0d0b.

* Revert "fix travis ci"

This reverts commit 5656fa9f.

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* 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

test=develop

* gather_op support int64_t index by adding a template typename

* add UT and rename typename

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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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* This PR adds broadcast for multi-process. And it could be used in dynamic graph to broadcast parameters.

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

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* add googlenet test

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* fix concat CreateKey not using input format

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*  Enable assign operator for a ngraph, test=develop

* Cross_entropy operators needs to be updated

* refine softmax fwd

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* refine cpu softmax bwd

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* fix batch size

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* fix compile issue with gpu

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* add value clip

* refine softmax fwd

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* fix compile issue wih gpu

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* add value clip to avoid exp

* fix concat op vartype check, test=develop

Async exe support communicator

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* add increment op to ngraph engine

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* fix style errors

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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.

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* Add LAMB optimizer

* Expose LAMB Optimizer's APIs

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* Cleanup code & doc

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* Update lamb optimizer's formula

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