* support elu activation double grad,test=develop

* delete the code commit in .cc,test=develop

* fix relu test unpass, test=develop

* add elu double grad kernel and unit test

* add caculate dX in elu double grad functor, test=develop

* update the commit code,test=develop

* register int/int64_t/float16 in  pow/square kernel,test=develop

* add abs/square/exp type,test=develop

* add_dygraph_execution_context

* add dygraph infershape context and execution context; test=develop

* fix imperative bug; test=develop

* remove inputs outputs interface from execution context,
because it have same function with inputNames;
test=develop

* remove tracer_test ctest; test=develop

* fix split op bug; test=develop

* fix unitests bug; test=develop

* fix distribute test bug; test=develop

* fix ngraph compile bug; test=develop

* fix grad maker bug; test=develop

* fix load op bugs; test=develop

* fix operator.cc construct bug; test=develop

* remove useless name find in operator; test=develop

* add tracer_test; test=develop

* fix concat, split bug; test=develop

* remove tracer_test unitest; test=develop

* fix attribute check bug; test=develop

* add test code to fix converage; test=develop

* remove useless code, change check backward input in engin; test=develop

* unlock var type infer shape;test=develop

* add ShareAllLoD api; test=develop

* add dygraph infershape context unitest; test=develop

* remove increase and decrease lod in dygraph; test=develop

* addd override; test=develop

* fix increase descrease lod; test=develop

* fix paddle_enforce; test=develop

* disable lod op dygraph check; test=develop

* fix paddle enforce error; test=develop

* add comment for op_registry and OperatorBase; test=develop

* optimize the comment of op_registry; test=develop

* fix format of comment; test=develop

* fix format of comment; test=develop

* optimize the format of comment; test=develop

* optimize the format of the comment; test=develop

* optimize comment of op_registry; test=develop

test=develop

* update elementwise double grad to save gpu memory, test=develop

* update elementwise_mul/div_grad_grad to save memory, test=develop

* remove eval function in eigen statement to save memory, test=develop

* add unittest for elementwise_div_grad_grad without dout, test=develop

* add unittest for elementwise_add_grad_grad without ddx, test=develop

* add float16 cuda kernel for elementwise double grad op, test=develop

improve pow op according to reviews:
1. Delete unnecessary judgement statements in PowGradOpDescMaker;
2. Improve test of test_api;

overload GetKernelTypeForVar

add stop_gradient=True when attr(factor) is tensor Variable, change examples in API pow.
test=develop,test=document_preview

* make leaky relu inplacable, test=develop

* force add unittests to pass coverage, test=develop

* add hard_swish activation op (new op)
test=develop

* remove redundancy files

* modify document content of HardSwish OP

* add API test in test_layers.py

* add dynamic_graph for test_hard_swish

test=develop

test=develop

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().

* double backward sqrt

* refine unittest. test=develop

* refine test. test=develop

* remove alpha in unittest. test=develop

* add double grad for square. test=develop

* formax code. test=develop

* fix for grad sum. test=develop

* refine shape. test=develop

* refine extract. test=develop

* refine_dropout_mem,test=develop

* # This is a combination of 14 commits.
# The first commit's message is:
remove ut test_dist_word2vec in mac ci, will fix it in private, test=develop (#17066)

# This is the 2nd commit message:

Fleet unify distributed training (#16791)

* implement distributed transpiler with fleet
# This is the 3rd commit message:

ParallelDyGraph with GPU collective mode (#16827)

implement dygraph.parallel.DataParallel to hook reduce op.

# This is the 4th commit message:

Init mixed precision training interface (#16856)

* Init mixed precision training interface

* Add fp16 test script

test=develop

* All initializers support float16

test=develop

* Code cleanup & add more code annotations

test=develop

* Update API spec

test=develop

* Add usage example in doc

test=develop

# This is the 5th commit message:

fix reference_count_pass,test=develop (#17060)

test=develop
# This is the 6th commit message:

Speedup roi_perspective_transform op by caching the information of linear interpolation in forward (#17090)

* Cache the information of linear interpolation in forward and use it in backward.
test=develop

* Fix cuda kernel.
test=develop

# This is the 7th commit message:

remove unnecessary prepare_data (#17080)

test=develop
# This is the 8th commit message:

fix interpolate cu. test=develop (#17101)

# This is the 9th commit message:

test=develop, double backward leaky_relu (#17067)

backward of backward: leaky_relu
# This is the 10th commit message:

fix fuse optimizer ops (#17102)

test=develop
# This is the 11th commit message:

truncated_gaussian_random supported in distributed training, test=develop (#17091)

# This is the 12th commit message:

 Detailed coordinate description for yolov3 loss (#17007)

* Detailed coordinate description for yolov3 loss

test=develop

* modified api.spec

test=develop

* modified loss name

* fix api.spec

test=develop

* polish description

test=develop

* modified api.spec

test=develop

# This is the 13th commit message:

fix test_weight_decay (#17109)

test=develop
# This is the 14th commit message:

Path flag (#17105)

* fix python/paddle/fluid/__init__.py detecting problems

backward of backward: leaky_relu

Support backward of backward for Relu and add a new gradient checker by comparing theoretical and numerical Jacobian. (#16862)

* Support backward of backward and a new gradient checker
* Rename decorators.py to decorator_helper.py, since Python on Windows CI has decorators package.

1. Add ReluDoubleGradMaker when register relu_grad.
2. Add a new gradient checker by comparing theoretical and numerical Jacobian.  Check double gradients by double_grad_check.

test=develop

add rsqrt op

test=develop

* staged.

* polish code

* polish code. test=develop

* polish code. test=develop

* api change. test=develop

* fix default value. test=develop

* fix default value. test=develop

test=develop

* staged.

* polish code

* polish code. test=develop

* polish code. test=develop

* api change. test=develop

* fix default value. test=develop

* fix default value. test=develop

test=develop

* Revert "Optimze Gelu with MKL Erf function (#15770)"

This reverts commit 676995c8.

* test=develop

* Optimize for gelu operator

* Set up the low accuracy mode of MKL ERF function.

test=develop

* Only enable MKLML ERF when OS is linux

* Use the speical mklml version included vmsErf function to verify gelu mkl kernel.

test=develop

* Add the CUDA macro to avoid NVCC's compile issue.

test=develop

* Add the TODO comments for mklml library modification.

test=develop

* Clean Code

test=develop

* Add the comment of marco for NVCC compiler.

test=develop

* Fix the gelu backward to avoid nan

test=develop

* Remove unnecessary calls

test=develop

* expose square
test=develop

* fix activation
test=develop

* Add square API
test=develop

* add necessary op

* code refine

* fix API.spec
test=develop

* fix unit test
test=develop

* add unit test sparse_grad_clip
test=develop

* fix API.spec
test=develop

* remove mac test for test_gradient_clip
test=develop

* remove selectedrows_mul_tensor
test=develop

test=develop

Fix code to support cpplint syntax check

test=develop

* add fp16 backward support
test=develop

* add sum_op fp16 test

* disable test_dist_save_load
test=develop

* add check_grad for sum

* add unit test for softmax_grad fp16
test=develop

* add scale_op unit test

* add mul_grad_op unit test for fp16

* add cross_entropy_grad and eman_grad unit test for fp16
test=develop

* fix cross_entropy unit test

* add pool2d fp16 unit test

* refine conv2d fp16 unit test
test=develop

* refine activation unit test
test=develop

* fix ci
test=develop

* follow zhihong's comment, copy from https://github.com/PaddlePaddle/Paddle/pull/12796
test=develop