* first version memory optimize pass, test=develop

* remove move_tensor_sharing_pass, test=develop

* refine code comments, add unittests, test=develop

* turn off memory_optimize by default, test=develop

* follow huihuang's comments, test=develop

* follow chengduoZH's comments, test=develop

* fix grammar error, add const qualifier, fix pass_test exception message, test=develop

* follow chengduoZH's comments 2nd, test=develop

* test=develop fix cpu roi_align_op backward bug

* fix logical APIs

test=develop

test=document_preview

* fix isfinite

* update matmul comments

* update API.spec

test=document_preview

test=develop

* update API.spec

test=document_preview

test=develop

* update API.spec

test=document_preview

test=develop

test=develop

Fix FleetWrapper:
1. fix shrink dense: just scale show
2. add datanorm scale: divide datanorm's gradient by batch_size

* change INT8 to template so that checking dst_dt with if-else could be removed. CI will be enabled after fixing reviews

* reverse user_residual_memory_p and user_bias_memory_p declaration scope
test=develop

* extend matmul op to support multiple head multiplication

With the support of multiple head, the multiplication of two big matrixes is
split into multiplication of several (head_number) small matrixes. e.g. if
Mat A is [3, 24] and Mat B is [24, 4], when multiple A and B with head_number
as 4, Mat A will be split as 4 matrix of [3, 6] and Mat B will be 4 matrix of
[6, 4]. The result of final matrix will be 4 matrix of [3, 4], i.e. [3, 16].

* Make lod reset op support for append lod level.

* Fix API.spec
test=develop

* Fix unitest.
test=develop

* Add python api for lod append.
test=develop

* Fix API.spec
test=develop

* Fix format of doc.
test=develop

* Fix unitest.
test=develop

* Fix doc.
test=develop

Modify auc doc. Add output variable description, previously was the scalar type, now changed to the tuple type.test=develop (#18771)

* update paddle-trt for:
    1. fix bug: when batch > 2, core in split plugin.
    2. add leaky_relu trt5.0 support (yolov3 from 65ms to 42ms.)
    3. add new attr to dropout.
    4. shuffle channel, swish, relu6 support
    test=develop

* 1. fix ci
test=develop

The change includes 2 things:

1. save delta model and shrink table are control by the same parameter before, now add delete_after_unseen_days to control shrink table.
2. value in sparse table has no slot before, now add slot in sparse table, and add DownpureCtrAccessor to support the new meta.
test=develop

test=develop

- compileation fix

- Yet another compilation fix

- Even yet another compilation fix

- Surprise! Again compilation fix

- lint fixes

test=develop

- Fix to workspace acquire of LRN

test=develop

- Fix to hash of BWD LRN

test=develop

- fix to lrn BWD PD acquire

test=develop

- Fixing LRN PD creation

test=develop

- cosmetic fix in comment

test=develop

- Fixes after review

test=develop

（1）support patch data （merge slots of instances of same line id, modify dense layer which
changes its size）
（2）add fleet load_one_table interface, support load from paddle model and load from pslib model
（3）fix push sparse bug which cause push sparse cost more time（about 10% in my testcase）
（4）when some slots are not in one of your network (join/update, etc.)，data feed、collect label info、push/pull sparse will skip these slots， instead of throw error.
（5）add more debug info in TrainFilesWithProfiler

* support sparse gradients
test=develop

* rewrite the conv_op using cudnn_conv_helper

* add workspace limit for v7 test=develop

* fix test=develop

* add half float test=develop

* fix test=develop

* fix test=develop

* revise code style test=develop

* fix test=develop

* supports distributed classification training
* update API.spec
* fix evenly division in python3
* change "index_range" to "index_num" in shard_index operator
test=document_preview
test=develop

test=develop

test=develop

add license

* fix clip_by_norm doc, test=develop

Test PaddingRNN on V100 GPU device.

Test configuration: large model, padding mode (which is the mode using recurrentOp), one GPU.
                   
GPU memory (MiB):   6414 (this PR)     vs   6837 (without this PR)
Speed (steps/s):         10.28 (this PR)    vs    9.89 (without this PR)
 

test=develop

test=develop

Optimize the content of error reporting information, print error code and official document web sites (#18671)

 optimize the error reporting information of cuda related API
 index on develop: 130ac177 Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into develop

* feature/auto_growth_allocator, test=develop

* add unittest of AlignedAllocator, test=develop

* try to turn on auto_growth to test on CI, test=develop

* fix segmentation fault in mixed_vector.h, test=develop

* add unittests, test=develop

* hash_op support int64 hash_size
* add corresponding UT

* remove ctr reader, all functions are satisfied in dataset

* remove async executor and add data_feed.proto to the deps of train demo

* Add GPU implementation for `prelu` backward pass

test=develop

* Fix logic error in `prelu` GPU backward and simplify a bit

test=develop

* Fix `prelu` backward CUDA implementation

test=develop

CPU version was not used actually, so test passed

* update anakin-engine interfaces for content-dnn

test=develop

* support only-gpu mode of Anakin

modify eltwise parse

test=develop

* modification for thread-safe

test=develop

* Integrated template instance

test=develop

* increase template parameters

test=develop

* support MLU predictor

test=develop

* update anakin cmake files

test=develop

* update TargetWrapper::set_device

* update the initialization of anakin subgraph

test=develop

* use the default constructor of base class

test=develop

* load model from buffer with length

test=develop

* modify the access level of class

test=develop

* support anakin for bitmain arch

test=develop

* remove files

* checkout cmakelists

test=develop

* modify interfaces

test=develop

* add cmake dependments

test=develop

* enforce the outputs of net

test=develop

test=develop