* Add IndicateVarDataType interface to block tensor is not initialized problem in OP GetExceptedKernelType (#20044)

* add indicate_var_data_type inferface, test=develop

* add unittests & polish error message, test=develop

* remove needless include, test=develop

* extract public function & polish message, test=develop

* delete empty var check, test=develop

* change data_type to pointer parameter, test=develop

* polish details, test=develop

* Replace risky GetInputType method with secure IndicateVarDataType interface (#20668)

* replace part of the old implementation, test=develop

* restore concat op, test=develop

* update all ops implemention & delete GetDataTypeOfVar func, test=develop

test=release/1.6

* add error log

1.support asymmetric padding;
2.support padding algorithm:"SAME" and "VALID";
3.support channel_last: data_format NHWC and NDHWC;
4.change doc of python API and c++;

test=release/1.6

* cpu conv_grad_grad

test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, fix/gcc_4.8_ubt_link_error

* test=develop, fix code format

* fix spelling errors; test=develop

* Update API.spec

update md5

* Update API.spec

* change the order of api;test=develop

* Update backward.py:
     - If there is no input grad var in all outputs of previous ops, do not append this op into graph.
     - Only apply this stragety when double backward.
* Update some double backward op.
* Update sum_op to judge whether a tensor is empty by numel or IsInitialized().

* 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

* Add conv2d_grad_grad_op
* Extracte the cuDNN conv algo searching code in conv_cudnn_helper.h.
    - Now use it in conv2d_grad_grad.
    - Will simply the searching code in conv2d and conv2d_grad in next PR.
* Enhance and fix bug in unit testing of gradient_checker.
* Support to fetch empty variables，return None in Python.

* make_conv_cudnn_ws_size_configurable, test=develop

* change std::max to std::min
test=develop

test=develop

test=develop

fix ctest eager deletion disable bug
test=develop

test=develop

* Add cpu_quantize_pass for C-API quantization

test=develop

* add cpu_quantize_pass test

* fix lint: add include memory unorderd_map and unordered_set

test=develop

* fuse_relu 1

test=develop

* tuned 2 without squash

* fixes

test=develop

* remove unused vars

test=develop

* refactored

test=develop

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

test=develop

* remove QuantMax and c style casts

test=develop

* last usage of QuantMax removed

test=develop

* 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.
test=develop

* change map to unordered_map

fix the forgotten part of cpu_quantize_pass_tester.cc

test=develop

* removed quantized attribute

* fixed cpu_quantize_pass_tester and op attr comments

test=develop

* removed redundant line

test=debug

* removed gmock

test=develop

* fix after merge

test=develop

test=develop

test=develop

* mem opt

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* refine code  test=develop

* refine code  test=develop

* refine code  test=develop

* refine code  test=develop

* refine with cub test=develop

* fix mkldnn test && remove comments && test=develop

* polish code && test=develop

* add only_forward test && test=develop

* Enable basic MKL-DNN INT8 Conv OP
test=develop

* Modify test case
test=develop

* Clean unittest code
test=develop

* Fix test
test=develop

* Modify test
test=develop

* Modify basic INT8 Conv
test=develop

test=develop

test=develop

test=develop

test=develop

test=develop

test=develop

* Convolution fusion operator.
* Clean code
test=develop

* add is_test to pooling and activations

add prop_kind support for layers activation. conv and pooling

add a pass that sets is_test to true

add transpiler version of is_test pass

test=develop

* patch test and pass

test=develop

* add pass to analyzer.h

test=develop

* add is_test attr description & pass only on mkldnn

in:
activation_op.cc
batch_norm_op.cc
conv_op.cc
dropout_op.cc
lrn_op.cc
pool_op.cc
sequence_pool_op.cc
softmax_op.cc

* fix is_test handling for activation pool and conv

* change description of is_test for all layers again

* remove GetAttr(use_mkldnn) from pass

* rename correct_mkldnn_test_phase to is_test

and remove dependency on MKLDNN
test=develop

* review fix magic number

* two if(..)s into one

* Check is_test once and pass mkldnn forward prop kind

* dereference shared_ptr with * (without get())

test=develop

* add is_test_pass back

test=develop

* add_infer_var_type
test=develop

* InferVarTypeHelper-> VarTypeInferenceHelper
test=develop

* PassInputTypeAndDTypeOnOutput
 test=develop

* follow comment
test=develop

* exhaustive search for cuDNN conv.
* Refine code and add unit testing.
* Fix model load in fluid/inference and unit testing in conv2d
* Follow comments.
* Fix compiling test=develop

This reverts commit ce7d9b07.

* exhaustive search for cuDNN conv.
* Refine code and add unit testing.
* Clean code
* Fix model load in fluid/inference and unit testing in conv2d
* Follow comments.