Polish fleet API to support cuda collective mode and nccl2 mode

Fix seq_pool failed when input dims is too large.
Resolve issue #3023

* add eye op,test=document_preview test=develop

* fix the API.spec, test=develop

* fix the document, test=document_preview test=develop

* add unitest for CI coverage, test=develop

* add trilinear interp. test=develop

* fix unittest. test=develop

* add python api and test_layers. test=develop

* refine API.spec. test=develop

* fix format. test=develop

* add python API test. test=develop

* format code. test=develop

* refine code strcuture. test=develop

* fix format

* fix doc. test=develop

* fix converage. test=develop

* fix format. test=develop

* optimize error message, test=develop

* optimize error message, test=develop

* Add the check of lod in sequence_softmax kernel.
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* Refine the comments.
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* fix overflow by int32 mul test=develop

* fix reference nullptr

* fix codestyle test=develop

* modify to point in ContextProjectFunctor test=develop

* modify to point in ContextProjectFunctor test=develop

* modify . to -> test=develop

* add var_conv_2d op test=develop

* edit api.spec test=develop

* ignore unittest if with_mkl=off test=develop

* fix python3 division test=develop

* fix ignore unittest bug test=develop

* remove useless code test=develop

* modify api.spec test=develop

* modify default_grad.spec test=develop

test=develop

* test=develop support Tensor input for ctc_align_op

* test=develop add some comment

* open gc by default, test=develop

* fix test_train_recognize_digits and disable gc when ngraph is enabled, test=develop

* fix conditional_block op eager deletion bug, test=develop

* add some comments to reviewers, test=develop

* add fusion_seqpool_cvm_concat test=develop

* simplify pass, test=develop

* fix code style, test=develop

* test=develop
Add the op of unique_with_counts, the op is calc the unqiue input of data, and output the corresponding indices and count of data.

* test=develop
Check the input and dtype in the op of unique_with_counts

* test=develop
test=document_preview
update the API.spec for `unique_with_counts`, at the same time, optimize the python api in the op of `unique_with_count`

* test=develop
test=document_preview
Fix some python api problem in the op of `unique_with_counts`, and change the error messsage in this op.

* Fix some API problem in the op of `unique_with_counts`
test=develop
test=document_preview

* test=develop
test=document_preview
Fix the api sample of op `unique_with_counts`, and update api.spec

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- Extracted key generation from FWD and GRAD into separate function

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- Compilation fix

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- another compilation

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* fix depthwise conv gpu kernel bug, test=develop
* add more depthwise conv test, test=develop

* fix security issue, test=develop

* bug fix, test=develop

* throw an exception when null pointer data with non-zero length PaddleBuf is passed, test=develop

* Fix Mask rcnn predictor
    1. refine memory optim algorithm to support the model with the block op.
    2. output diff : modify the affine channel fuse
    3. add condition_block_infer op
add interface for setting trt calib table dir
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* add the missing files.
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* 1 add trt fp16 support
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* update parallel.py
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* support center loss
* change tensor copy  api to high level api tensorcopy

* test=develop rewrite the center_loss cuda_kernel to make it faster
and add document of the center loss api,also update test function

* test=document_preview test=develop
update document of center loss

* test=document_preview test=develop
modify API.spec modify test code remove nouse const_cast

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Optimize the error report information when loadcombine fail to open model files test=develop (#18888)

* upgrade ngraph to v0.24 test=develop

* simplify io test=develop

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- optimization of TID to string

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* test=develop fix cpu roi_align_op backward bug

* 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
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* Fix unitest.
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* Add python api for lod append.
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* Fix API.spec
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* Fix format of doc.
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* Fix unitest.
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* Fix doc.
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test=develop

- compileation fix

- Yet another compilation fix

- Even yet another compilation fix

- Surprise! Again compilation fix

- lint fixes

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- Fix to workspace acquire of LRN

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- Fix to hash of BWD LRN

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- fix to lrn BWD PD acquire

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- Fixing LRN PD creation

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- cosmetic fix in comment

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- Fixes after review

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* support sparse gradients
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* 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