* add a place field in DataFeed to denote which place it will feed data to.
* abstract the copy process in CopyToFeedTensor function
* add UT for float32 type and for CUDAPlace

* Enhance fuse optimization op pass
test=develop

* Add call stack info during runtime and compile time
test=develop

* Rename operator_call_stack
test=develop

* Add unit test
test=develop

* follow comment
test=develop

* fix QueueDataset queue size，set queue size = batch size * 100, to avoid too many instances in channel when training is much slower than reading data.

* fix memory overlapping of fetch var (return of executor.run), test=develop

* fix wrong usage of ParallelExecutor in op_test, test=develop

* remove useless parameter and simplify code

* avoid tensor destruct untimely, test=develop

* add testcase independent of OpTest, test=develop

* 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

* support filelist size < trainer num
* pull dense when stop, to make sure local dense params are same as pserver, so save paddle model will save dense model same as pserver
*  enable QueueDataset train same filelist for serveral times

* Disable fuse optimization
test=develop

* add fusion_seqpool_cvm_concat test=develop

* simplify pass, test=develop

* fix code style, test=develop

adjust ins weight according to nid slot , user can specify adjust_ins_weight in strategy

Revert "use static variable to do cache instead of thread local in thread frequent switching case (#18428)" (#18879)

This reverts commit ce38bb53.

test=develop

* remove legacy memory optimization codes, test=develop

* follow huihuang's comments,test=develop

* follow luotao's comments, test=develop

* dump slot

* test

* proto

* dump slot

* test

* proto

* code style

* code style

* code style

* style

* add delete after unseen days

* add unseen days

* code style

* conflict solve
test=develop

* add clear model

* code style
test=develop

* code style
test=develop

* open fuse optimization ops
test=develop

* 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

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

* 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

（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

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)
 

* 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

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

test=develop

* not use transferscope cache in cpu case

test=develop

* adjust variable name and add comments

test=develop

* use correct format for class member in operator.h

* use correct format for class member in operator.cc

test=develop

* fix int64_t

* update fill constant op unittest

* add empty line

* 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 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

test=develop

test=develop

1. Since allreduce op has 4 reduce types, We split these four reduce types into four ops
2. We also refined the collective op code, e.g. we separated the collective op kernel into CPUKernel and CUDAKernel, and remove the device specified DeviceContext parameter in template as we already knew the target DeviceContext
3. We remove the newly added Collective op role to reduce the complexity of program and graph analysis

* Int8: Fix Pooling output scale

test=develop

* Update scales quantization for certain operators

These include: concat, transpose, pool and reshape. test=develop

* Move concat minimum scale finding to quantizer

test=develop

fix data feed ptr runtime error, pipeline trainer will core in some cases, so set it nullptr as default value.