* update ScopeBufferedSSAGraphExecutor&AsyncSSAGraphExecutor&ThreadedSSAGraphExecutor&FastThreadedSSAGraphExecutor&ParallelSSAGraphExecutor&ParallelExecutor for fetching unmerged results.
* add the unit test for fetch_unmerged.
* update ut for multi-card and multi-cpu.
* add the error message and the user suggestion in FetchOpHandle. test=develop
* Add two types of Metric Calculator: MultiTaskCalculator & CmatchRankCalculator.
* Add a config for DynamicAdjustChannelNum function to denote whether we will discard the remaining instances when they are not be distributed evenly.
* Remove CPU code in Pull/PushSparse and we will add it back when testing it fully.
* Fix some known issues: such as copying persistable vars after one epoch running.
Refine PaddleBox Framework, Main functions:
* Add MetricMsg util class, which can calculate metrics like AUC, bucket_error, COPC.
* Replace FeedPass with new interface: BeginFeedPass & EndFeedPass
* Refactor Pull/Push Sparse Function in box_wrapper.
* Use CUDA Kernel to copy keys and copy feasign between tensor and boxps struct.
* Cache copied keys in pull sparse in order to reuse it in push period.
* Add the first implememtation of fusion_group op #19621 (#3)
* Add the dynamic load of nvrtc, and support runtime compiling of CUDA kernel using nvrtc.
test=develop
* Call CUDA driver api to launch the kernel compiled by nvrtc.
test=develop
* Disable for mac and windows.
test=develop
* Refine the codes to support manually specified num_threads and workload_per_thread.
test=develop
* Refine the CUDA kernel to support large dims.
test=develop
* Add DeviceCodePool to manage all device codes.
* Add the first implementation fusion_group op.
* Add unit-test for fusion_group op.
* Add the check of result.
* Add the check of nvrtc in unit-test.
test=develop
* Add comment to explain the inputs, outputs and features of fusion_group op.
test=develop
* Disable fusion_group op for mac and windows.
test=develop
* Make the compiling of device code return status instead of hanging up.
test=develop
* Add the check of whether there is CUDA driver library, and do not core dump when failing to call the CUDA driver API.
* Unify fusion_group_op's input and output names.
test=develop
* Add the check of CUDA driver library in unittest.
test=develop
* Enable generating code for a given subgraph. #21126 (#4)
* Enable generating code for a given subgraph.
* Support sorting the subgraph.
* Remove the rearange of expressions because we use the sorted subgraph directly.
* Enable generating code for a subgraph which is composed of grad ops.
* Use expression information to check the accuracy in unittest.
* Separate load and store from computation expressions.
test=develop
* Improve the loading statements in generated codes.
test=develop
* Remove unused arguments from formal list.
test=develop
* Enable the detection of subgraph of grad ops.
* Generate code for detected subgraph in fusion_group_pass.
* Add an option in BuildStrategy to enable fusion_group_pass and add unittest.
test=develop
* Fix a bug when checking whether the shape of all inputs are the same.
* Add debug information.
* Remove subgraph_detector from inference/analysis to the common framework/ir directory. (#5)
test=develop
* Call subgraph_detector in fusion_group pass.
test=develop
* Disable fusion_group when WITH_GPU is OFF.
test=develop
* Refine all PADDLE_ENFORCE message.
test=develop
* Fix the case that some inputs are not defined in grad ops, and set op_role for fused op.
test=develop
* Follow review comments.
test=develop
* Enable quantize to reorder to nchw as well
* Correct FC MKL-DNN input dim requirements to accept 3D
* Improve DNNL FC format, error and 3D input handling
test=develop
* Improve error checking in FC
test=develop
* Improve PADDLE_ENFORCE messages in fc-related files
* Remove data layout attribute from obligatory pass args
test=develop
* Fix message in fc_mkldnn_pass to be logically correct
test=develop
* Implement a common python unittest to test the ir passes.
test=develop
* Save the results in np.array and support to startup on CPU.
test=develop
* Fix the unittest.
test=develop
* Add check_program to check whether the optimized program is different from the origin one.
test=develop
* Remove the inferface all_ops.
test=develop
* Add exception test in pass_test.
test=develop
* add bn and relu fuse pass
* add op attr assert and dtype assert
* fix some inputs&&outputs bugs for the fused op and pattern.
* add the unittest for fuse_bn_act_pass. test=develop
* use normative enforce statements. test=develop
* add the cpu test. test=develop
* add the support of batch_size=1 for the bn with relu op. test=develop
* add the error type for paddle throws. test=develop
* add fused_batch_norm_act and fused_batch_norm_act_grad to op_has_unsed_vars_white_list. test=develop
* Polish the PADDLE_ENFORCE in fusion_group pass related codes.
test=develop
* Correct the unittest because of the change relu_grad's formula.
test=develop
* Add the dynamic load of nvrtc, and support runtime compiling of CUDA kernel using nvrtc.
test=develop
* Call CUDA driver api to launch the kernel compiled by nvrtc.
test=develop
* Disable for mac and windows.
test=develop
* Refine the codes to support manually specified num_threads and workload_per_thread.
test=develop
* Refine the CUDA kernel to support large dims.
test=develop
* Add DeviceCodePool to manage all device codes.
* Add the first implementation fusion_group op.
* Add unit-test for fusion_group op.
* Add the check of result.
* Add the check of nvrtc in unit-test.
test=develop
* Add comment to explain the inputs, outputs and features of fusion_group op.
test=develop
* Disable fusion_group op for mac and windows.
test=develop
* Make the compiling of device code return status instead of hanging up.
test=develop
* Add the check of whether there is CUDA driver library, and do not core dump when failing to call the CUDA driver API.
* Unify fusion_group_op's input and output names.
test=develop
* Add the check of CUDA driver library in unittest.
test=develop
* Refine the calling of PADDLE_ENFORCE.
test=develop
* optimize adam speed by removing _finish_update test=develop
* fix SparseAdamFunctor param list test=develop
* Remove scale_op in expect_list of adam_op test=develop
* fix test optimizer loss assert error test=develop
* fix test optimizer loss assert error test=develop
* modify PADDLE_ENFORCE usage test=develop
* fix op_type in lamb_op.cc test=develop
* fix errors ostream format bug test=develop
* add betaPowOut in ngraph op test=develop
* fix ngraph::op api for gcc8 test=develop
* clean code test=develop
* modify struct into class test=develop
* remove code of beta1Tensor in lamb_op test=develop
* fc-dequantize squash
test=develop
* change according to reviews
test=develop
* change PADDLE_ENFORCE
test=develop
* add second test when fc-dequant do not fuse
test=develop
* change all related PADDLE_ENFORCE
test=develop
* add fake init for the trainer, fix large memory hold in the trainer
* do not merge recv vars from a remote endpoint, test=develop
* add recv and save op, merge slice var in one op, save memory
* remove hsigmoid with pull sparse, test=develop
* add file check_op_desc.py and add interface to get default value. test=develop
* add test for c++ coverage rate. test=develop
* Correct typo. test=develop
* Commit before merging develop
test=develop
* Backup after working with Huihuang logs
* Commit before deleting Huihuang debug loggings
* Commit before debug
test=develop
* Fix bug commit
test=develop
* Backup of fixing bugs
test=develop
* Clean up code
test=develop
* Fix a bug in sum_op
test=develop
* Implement Int8 FC
* Integrate FC into INT8v2
test=develop
* int8 FC: transpose weights before computing scales
test=develop
* Add support for activation_type string in FC
test=develop
* Disable MKL-DNN's FC in VGG16 and 19
test=develop
* Disable FC quantization when mkldnn FC is disabled
test=develop
* Solve PADDLE_ENFORCES in FC int8
* Fix Paddle enforces and remove const cast
test=develop
* Fix style changes
test=develop
* Fix quantizer_tester test and add fc quantization
test=develop
* Fix FC test fail on CUDA
* Remove unnecessary log from quantize placement pass
test=develop
* Add Thread ID to FC hash key
test=develop
* Add comments to MKL-DNN FC Kernel
test=develop
* Refactor quantizer
test=develop
* Fix linter issues
test=develop
* Fix crash in slim googlenet
test=develop
* Fix PADDLE_ENFORCE messages
test=develop
* Add fc padding to solve mkl performance
test=develop
* fix gpu pass and error information
test=develop
* fix fc_fuse_pass_test
test=develop
* fix error information
test=develop
* fix error information
test=develop
* fix name and add fc op padding test
test=develop
* fix attributes
test=develop
* optimize fc padding
test=develop
* fix test
test=develop
* fix fetch handler problem and refactor
when a user define FetchHandler class, he or she should initialize a handler
with variable dict. the key of a variable dict is a user defined name,
the value of a variable dict is a Varaible generated from python API.
For each fetching, a user should implement handler function in which
fetched_result_dict will be available and the user can access the fetched value
with user defined keys.
* Disable fusion_group pass for windows and mac. We will do some experiments on Linux first.
test=develop
* Print the subgraph when check failed.
test=develop
* Enable generating code for a given subgraph.
* Support sorting the subgraph.
* Remove the rearange of expressions because we use the sorted subgraph directly.
* Enable generating code for a subgraph which is composed of grad ops.
* Use expression information to check the accuracy in unittest.
* Separate load and store from computation expressions.
test=develop
* Improve the loading statements in generated codes.
test=develop
* Remove unused arguments from formal list.
test=develop
* copy some feasigns and corresponding embeddings from one sparse table to another
* copy all feasigns and corresponding embeddings from one sparse table to another
* copy all dense params from one table to another
* copy some local vars to other local vars
* Add the check of lod_level between compile-time and runtime.
test=develop
* Fix bug in check_compile_vs_runtime.
test=develop
* Fix the check of output when it is dispensiable or intermediate.
test=develop
* Share lod of x to out in match_matrix_tensor op in compile-time.
* Implement GetLoDLevel in InferShapeContext.
* Set the default value of check_compile_vs_runtime to False and enable it in test_sequence_pad_op.
test=develop
* Enable check_compile_vs_runtime in test_match_matrix_tensor.
* Add the implementation of SetLoDLevel in InferShapeContext.
* Remove the implementation of IncreaseLoDLevel and call Get/SetLoDLevel instead.
* Remove the implementation of DecreaseLoDLevel and call Set/GetLoDLevel instead.
* Refine some ops and unittests.
test=develop
* Fix a typo.
test=develop
* Remove the check of var type, and change int to int32_t.
test=develop
* Add unittest for Get/SetLoDLevel.
test=develop
* Add the definition of operation in fusion_group.
* Use operations in OperationMap to detect fusion_group of elementwise pattern.
* Add namespace fusion_group in code_generator.
* Use operations recorded in OperationMap to generate code.
* Remove implementation codes to .cc file.
* Refine Operation and CodeGenerator to make it easier to generate code for grad_op.
Refine the unittest for better reuse.
* Avoid recording the template's keyword in a array.
* Support the generating of code for grad_op and add unittest.
test=develop
* Remove replaced_element_in_order and use use number instead.
test=develop
* Enrich the type of error and declare the error type interfaces, test=develop
* adjust tests to adapt new form, test=develop
* add inference deps with error_codes.pb.h, test=develop
* restore stack iter start pos, test=develop
* polish code based review comments, test=develop
* remove duplicate code and duplicate config of master+patch
* drop all ins which has conflict slot or size < merge_size
* user only need to set merge size，if ins num of same id is not equal to merge size, just drop these ins
* user must make sure master data and patch data has no same slot whose feasigns are both non-zero, otherwise these ins will be dropped. (slot list should still be the same of both master and patch)
* test=develop
* support no need buffer vars in dygraph, test=develop
* fix inference compilation error, test=develop
* update no_need_buffer_vars_inference, test=develop
* add unittests for no_need_buffer_vars_context, test=develop
* refine no_need_buffer_vars by return ref, test=develop
* polish some codes, test=develop
* Refine the cache of program, context and scope in executor.
test=develop
* Refine the unittest test_executor_and_use_program_cache.
* Add the test the PaddingRNN with use_program_cache=True.
test=develop
* Remove a check.
test=develop
* Refine the unittest to check whether it is correct when setting use_program_cache=True.
test=develop
* Refine the InferShape of ReadFrom and WriteTo op, and add comment to explain why not call ShareLoD for runtime.
test=develop
* Add comment for ReorderLoDTensorByRank op.
* Add comment for lod_tensor_to_tensor_array op to explain why only call DecreaseLoDLevel for compile time.
test=develop
* ShrinkRNNMemory op should call ShareLoD for compile time.
test=develop
* Add the implementation of IncreaseLoDLevel and add the compile-time check of lod_level in InferShape of sequence_pool.
test=develop
* Refine the unittest of DynamicRNN.
test=develop
* Change PADDLE_ENFORCE to PADDLE_ENFORCE_NE.
test=develop
* Add fusion_group_pass and elementwise pattern.
* Rewrite the detector of elementwise group.
test=develop
* Add a comment in codegen.
* Add more unittest cases.
test=develop
* Move code_generator related code to fusion_group directory.
* Correct the including path.
* Add the definition of SubGraph and finish the insert of fusion_group op in pass.
* Insert graph_vis_pass in tester to visualize the graph for debug.
* replace part of the old implementation, test=develop
* restore concat op, test=develop
* update all ops implemention & delete GetDataTypeOfVar func, test=develop
* no longer need to define all embedding layers (no one less) of all slots in each program. make trainer_param repeated in ps.proto.
* add find_distributed_lookup_table_grads instead of hard code GRAD
* support embedding stop gradient. push sparse has error before fix this.*
* fix fill sparse, skip slots which do not have embedding. each slot's embedding in a sparse table should be used in all training programs before fix this.
* fix pull sparse, skip slots which do not have embedding.
* fix collect feasign label info, skip slots which do not have embedding.
* support when there are multi sparse tables in one or multi training programs, each program can pull/push its own related sparse tables instead of all sparse tables.
* test=develop
* - Flushing mkl-dnn cache
test=develop
- Disabled clearing cache for LoadModel
- Added clearing of mkl-dnn cache when Executor is created
test=develop
- Do not clear for GPU places
test=develop
- compilation fix
test=develop
* - Moved clearing of mkl-dnn cache in destructor of executor
test=develop
* - Compilation fix
test=develop
- Reverted conditional clearing of mkl-dnn cache in Executors's
destructor
test=develop
- compilation fix
* How to write custom op needs to follow framework OP spec.
* Package fluid_framework.so and headers into whl.
* Add paddle.sysconfig.get_include() and paddle.sysconfig.get_lib() to get include dir and lib dir.
* Export some C-APIs to merge OpInfo between core.so and custom_op.so.
* Add unit testing.
* Update API.spec.
* Follow Wangzhen's comment in PR 18970, test=develop
* Review comments, test=develop
* Leave fake quantization around mul
test=develop
* Replace Fake with Real Quantized Mul
test=develop
* Fix bug in quantize placement pass
Nodes in the graph now have checked type instead of node name when they are to be marked for quantization test=develop
The new "fluid.data" changes old "fluid.layers.data":
1. Add shape and dtype check.
2. Remove "append_batch_size" parameter. We won't offer this in the new data layer because other deep learning platforms don't have this kind of data layer pre-processing. It may confuse users.
3. Remove "stop gradient" parameter because the data layer doesn't do back-propagation
TODO：
Now data layer feeded by executor is checked, will we want to check the feed data of readers in the future?
* support change shuffle thread num
* support change train thread num
* fix receive shuffle data of each channel
* data norm stop gradient
* add check thread_tensor type and root_tensor type when merge metric
* remove sleep in shuffle, add config
* add config of pslib client to client communication
* fix xbox str
* add data norm op testcase
* add flush in trainer finalize
* Set states of recurrent op as dependent vars in prune of save inference model
This PR will fix the save/load inference model problem of RNN models.
The reason of the bug is that save_inferenc_model will prune OPs that doesn't contribute to Output. But in recurrent_op, States are not Output, OPs refers States will be pruned.
This fix adds States of recurrent_op as dependent var so that OPs referring States won't be pruned.
* Add fc_elementwise_layernorm_fuse pass and unittest.
* Add fused_fc_elementwise_layernorm op and its GPU kernel.
test=develop
* Apply fc_elementwise_layernorm_fuse_pass to GPU inference.
* Add the setting of attrs in the definition of binary_op.
test=develop
* Add comment.
* Implement the unittest.
test=develop
* Change the unittest name of layer_norm.
test=develop
* refactor dygraph,test=develop
* fix failed unittest,test=develop
* polish code,test=develop
* check windows ci error,test=develop
try to fix windows ci error by np.allclose,test=develop
* polish vlog and profiler, test=develop
* try to fix preceding ops order,test=develop
* test transformer in windows ci, test=develop
* use python c-api to speed up tracer.trace,test=develop
* test=develop, fix docker with paddle nccl problem
* test=develop, add ut for debug string and gradient_accumulator
* test=develop, add tests for layer/gradient_accumulator/prepared_op
* test=develop, fix complie error for test_prepared_op
* test=develop, add more ut for dygraph
* test=develop, create API.spec for dygraph api change
* add transform_data to dygraph
* test=develop, refoctor name to make it easier to understand
* test=develop, refoctor name to make it easier to understand
* add test and change input to const ref for safety
* test=develop, fix multi-gpu failed problem , add Tracer tests, change PADDLEENFORCE to PADDLEENFORCE_EQ
* add ut for data transform
* refine ut for data_transform
* test=develop, fix ut failed on parallel se-resnext
* test=develop, change one more PADDLE_ENFORCE
* add test_tracer on multiple devices
* test=develop, change place to mutable for data transform
* test=develop, add transform data on same place test and remove useless log
* test=develop, Add to do for data layout and and ut for conv2d with no bias
* Refine the codes related to fc op.
* Add GPU implementation for fc functor.
* Apply fc_fuse_pass in GPU inference.
test=develop
* Change the cmake for fc op.
* Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ.
* Add an attribute to set the activation type in fc_op.
* Enhance the unittest of fc_op.
test=develop
* Remove the declaration of FCOpGrad back to the header file.
test=develop
* Set default value for newly added arguments in test_fc_op.
test=develop
* Enhance fc_fuse_pass to enable fusing relu.
* Allow print the shapes of var_desc in graph.
test=develop
* Enhance fc_fuse_pass_tester.
* Remove the use of PADDLE_ENFORCE.
test=develop
* Correct the number of ops after fusing.
test=develop
* Fix a typo.
test=develop
* Set activation_type to null when there is no relu in fc.
test=develop
* Refine fc_fuse_pass's codes.
* Enable the set of shape for tensor.
* Refine repeated_fc_relu_pass and add unittest.
test=develop
* Open fuse all reduce op
test=develop
* Add Fuse optimization op log
* Add log in fuse_optimizer op pass and fuse all_reduce op pass
* replace with boost::optional<bool>
test=develop
* Polish code
test=develop
* fix code coverage
test=develop
TemporaryAllocator is a singleton used for allocating memory for Cudnn. Since it is a singleton, we can delete it for better performance in memory.
We replace TemporaryAllocator by CUDADeviceContextAllocator and CUDADeviceContextAllocation, which uses stream callback to delete the memory allocated for the stream to avoid singleton.
Also added data_feed_proto to operator to fix CI in CPU compilation
* Refine the codes related to fc op.
* Add GPU implementation for fc functor.
* Apply fc_fuse_pass in GPU inference.
test=develop
* Change the cmake for fc op.
* Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ.
* Add an attribute to set the activation type in fc_op.
* Enhance the unittest of fc_op.
test=develop
* Remove the declaration of FCOpGrad back to the header file.
test=develop
* Set default value for newly added arguments in test_fc_op.
test=develop
* Add a interface to enable cudnn for inference.
* Add cudnn_placement_pass.
test=develop
* Set the default value of cudnn_enabled_op_types to null.
test=develop
* Write the common basic class, placement_pass_base, to refine the codes.
test=develop
* Call EnableCUDNN in unittest.
test=develop
* Refine cudnn_placement_pass tester.
* Enable the testing of cudnn_placement_pass in inference's unittest.
test=develop
* Add the check of op kernels.
test=develop
* Support looking up embeddings from BoxPS.
* Add a _pull_box_sparse op, for now this op is not exposed to users.
* Add a BoxHelper class, providing 'BeginPass', 'EndPass', 'FeedPass' functions and so on.
* Add 'BoxPSDataset' in python code.
* Add a compile options WITH_BOX_PS and a MACRO PADDLE_WITH_BOX_PS.
* Add UT.
* More concrete information pls refer to: https://github.com/PaddlePaddle/Paddle/pull/18982
- Refactor step 1
- Compilation fix
- Yet another compilation fix
- Even more compilation fix
- Lint fixes
test=develop
- Removed deprectaed PADDLE_ENFORCE occurance
test=develop
- Candidate fix to BN forward
- Lint fixes
test=develop
- Refactoring in data_layout_transform
- compilation fix
- Another comppilation fix
- Step further into darkness
- Yet another compilation fix
- Yet another compilation fix
- missing header
- compilation fix
- Added MKLDNN -> Paddle conversion in fetch op
test=develop
- Compilation fix
test=develop
- Lint
test=develop
- Mul fix
- Fix to MKLDNN MUL op and Elementwise MUL UT
test=develop
- Workaround for diffrent weights with groups representation Paddle vs
MKL-DNN.
test=develop
- Candidate fix for 5D convolution with groups
- Refactor of fix for conv3d and conv2d in fetch op
test=develop
- Compilation fix
- Still same compilation fix
- Compilation fix
- Compilation fix
- Reverted refactoring of fixes
- Adapted test_conv2d_int8_mkldnn so it exects data in NCHW format
not NHWC
test=develop
- minor fix in UT
test=develop
- Lint fixes
test=develop
* Add simplify_with_basic_ops_pass to replace dropout_op with scale_op when is_test is true.
test=develop
* Delete dropout_op directly when upscale_in_train is true.
test=develop
* Improve the debug string, adding the print of op_desc information.
* Fix the case when dropout's input x is reused as the next op's output.
* Add the pass to inference.
test=develop
* Change the log level.
test=develop
* Add unittest for inplace case.
* Add comment to explain the pass.
* Apply the pass for CPU inference.
test=develop
* Fix the typo.
test=develop
* Add the check of AttrType.
test=develop
* fix correctness of the communicator
* fix a bug in send thread when sending var context is empty, test=develop
* add lookup_table_prefetch_op and prefetch optimize, test=develop
* remove remote prefetch GPU supported
* word2vec force with CPU, test=develop
* test dist remote lookup table force with CPU, test=develop
* add pybind interface to get all inplace ops, test=develop
* enhance OpTest to check whether the consistency of operator when using and not using inplace, test=develop
* handle corner cases in op_test, test=develop
* support outputs without tensor holder_, like XShape in reshape_op, test=develop
* fix bug, some op has GradOpMaker, but actually no grad_op in OpInfoMap, test=develop
* use reshape_grad instead of reshape in FlattenGradOp, test=develop
* fix error debug dims info for variables like XShape, test=develop
* change computational order in sum_op to relieve computation difference using inplace, test=develop
* add inplace_atol to check group_norm, and skip inplace_grad for mkldnn, test=develop
* follow sneaxiy's comments, test=develop
* remove unused DefaultGradOpDescMaker in mkldnn op, test=develop
* Enhance the error message when GrapOpMaker is null.
test=develop
* Call Proto() instead of directly using proto_ pointer.
test=develop
* Rollback to use proto_ directly, because some sepecial grad ops, such some double grad ops, donot have proto.
test=develop
* 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
* 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.
* 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
* 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
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
* 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 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
Wilber
Adam
Zhaolong Xing
Zeng Jinle
liu zhengxi
wangchaochaohu
hong
Zhang Ting
Zhen Wang
hutuxian
tianshuo78520a
Leo Chen
GaoWei8
tangwei12
Yiqun Liu
123malin
flame
yaoxuefeng
zhaoyuchen2018
guofei
joanna.wozna.intel
xujiaqi01
石晓伟
Michał Gallus
lidanqing
Wojciech Uss
zhouwei25
Chen Weihang
zhongpu
bingyanghuang
silingtong123
Jacek Czaja
Huihuang Zheng
Pei Yang
qingqing01
Aurelius84
Thunderbrook
WangXi
liym27
Tao Luo
Jie Fang
Youwei Song
Dong Daxiang
wopeizl
Chengmo
633WHU
chengduo
Jiabin Yang
Huihuang Zheng
wangguanzhong
mapingshuo
tensor-tang
baojun
gongweibao
liuwei1031
juncaipeng
Leo Zhao
chengduo
fuyinno4
Huihuang Zheng