* 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.
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- 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

* 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

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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

* hash_op support int64 hash_size
* add corresponding UT

* remove ctr reader, all functions are satisfied in dataset

* 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

* - Added partial draft of pooling acquire

- Workspace support

- compilation fix

- Added draft of pooling backward reimplementation

- Segfault fix

- reverted 'any' for diff_dst crewation in pooling

- Lint fixes

test=develop

- lint fixes

test=develop

- Further lint fixes

test=develop

* - Fixes after review

test=develop

* - Lint fixes

test=develop

* - Even more lint fixes

test=develop

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* make auc op compatible with 1 dim

* feature/buffer_shared_inplace, test=develop

* refine code, test=develop

* fix elementwise_add op cpu inplace and sum inplace bug, test=develop

* add unittest and debug log, test=develop

* fix parallel_executor scope bug, polish code, test=develop

* fix sum op, activation op, single_in_place_inference bug, test=develop

* remove kLocalExecScopeName, test=develop

* fix unittest,test=develop

* fix out_var first version bug, test=develop

* follow comments,test=develop

* clean code of dim and place, test=develop

* fix failed unittests, 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 transform matrix bug, test=develop

* modify API.spec

* 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
test=develop

* add the missing files.
test=develop

* Fix topk cannot handle 1D vector bug

Add path to handle 1D vector

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* refine code

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* Refine Infershape in activation_op for double_grad.

* test=develop
support Tensor input for chunk_eval op

* test=develop
fix testcase for chunk_eval op

* test=develop
fix typos in nn.py