* rewrite abs op

* rewrite abs op and remove abs in activation

* remove abs register in old codes

* fix abs_grad type error

* fix abs double_grad output name error

* modify abs_grad, abs_grad_grad functor for windows building

* format code style

* fix the bug of result is nan when the divisor is zero

* add missing abs attr and add abs for float16

* fix elugradgrad test fail and error message opt

* fix unitest,test=develop

* Update prroi_pool_op.h

fix error message

* opt message,test=develop

* fix ci fail,test=develop

As the title

Add new operator log10

As the title

register log double grad kernel for cpu and cuda

add abs support double grad for the api 2.0

* New features, add sinh and cosh op, test=develop

* remove duplicate test function and remove out paramters, test=develop

* Add out paramters temporary, remove later. test=develop

* remove out args, PR 25570, test=develop

* remove TestParameter, test=developx

* add test api for static dygraph, test=develop

* add backword unittests for sinh and cosh, test=develop

* improve activation ops performance, test=develop

* use 32bit only GPU computation, test=develop

add new tensor: max,min,t,eye,log1p; test=develop

1. update error info of the ops (abs, acos, asin, atan, ceil, cos, exp, floor, log, pow, reciprocal, round, rsqrt, sin, sqrt, square, tanh)
2. add the unittests of the above refered ops (test error info)

* delete invalid check inferface Ref & VectorRef, test=develop

* fix vector ref delete error, test=develop

* try the new check inferface, test=develop

* change all related code with new check macro, test=develop

* remove static assert, test=develop

* polish detail, test=develop

* skip coverage problem, test=develop

* add new check macro, test=develop

add approximation for gelu, default value is False (only kernel with eigen is added, remove code for computing gelu with MKLDNN temporarily)

* 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.