* sequential reader stage 1, test=develop
* fix ut, test=develop
* fix iterable=False reset bug, add some logs and polish code, test=develop
* inference feed partial data, test=develop
* Turn on keep_order=True for test, test=develop
* enhance ut to test more cases, test=develop
* test commit for reverting
* Revert "test commit for reverting", test=develop
This reverts commit 80aef42ef52ba1ee79627d6f663a624ec4f12f58.
* add ut of merged and unmerged results, test=develop
* add more uts for coverages and add en doc of api, test=develop
* follow comments, test=develop
* change note style, test=develop
* change the ci trt from version 5. to 6.0
* paddle-trt dynamic shape support init
* conv+bias or conv+bn dynamic shape support
test=develop
* modity trt engine opconvert
test=develop
* fix ci error
test=develop
* 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
* Refine adam op, test=develop
* Fuse kernels together to reduce cpu time.
* Refine paddle enforce, test=develop
* Remove some comments, test=develop
* Refine code,test=develop
* Refine cuda kernel, test=develop
* Refine code according to comments, 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.
* 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
* 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
* modify fc to linear in sample code, test=develop
* remove FC, test=develop
* remove warnings, test=develop
* drop fluid/imperative/README.md , test=develop
* change fc to linear, test=develop
* polish code style, 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
* test=develop, fix docker with paddle nccl problem
* don't expose numerous Tensor.set(), test=develop
* fix condition, test=develop
* fix float16 bug, test=develop
* feed should be Tensor or np.array, not Variable or number, test=develop
* use forcecast to copy numpy slice to new array, test=develop
* remove float16-uint16 hacking, test=develop
* add variable method to varbase and refactor to_variable to support return varbase
* support kwargs in varbase constructor
* add VarBase constructor to support default python args
* refine varbase initial method
* reset branch
* fix ut for change VarBase error info to PaddleEnforce
* cherry is parameter change before
* overload isinstance to replace too many change of is_variable
* rm useless files
* rm useless code merged by git
* test=develop, fix some ut failed error
* test=develop, fix test_graph_wrapper
* add some tests, test=develop
* refine __getitem__, test=develop
* add tests, test=develop
* fix err_msg, 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.
* 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 c++ global current tracer for dygraph, test=develop
* add tracer property in c++, test=develop
* support different place, test=develop
* add unittest for tracer, test=develop
* don't expose numerous Tensor.set(), test=develop
* fix condition, test=develop
* fix float16 bug, test=develop
* feed should be Tensor or np.array, not Variable or number, test=develop
* use forcecast to copy numpy slice to new array, test=develop
* remove float16-uint16 hacking, 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
* update the api en doc of BuildStrategy and its setting, test=develop, test=document_fix
* update api.spec, test=develop, test=document_fix
* update the en doc of fuse_relu_depthwise_conv, test=develop, test=document_fix
* test=develop, fix docker with paddle nccl problem
* test=develop, refine en_doc for Variable and Program
* test=document_fix, fix English doc for Variable and Program
* test=document_fix, refine astype code block style
* test=document_fix, add example code for Variable properties
* test=document_fix, fix BackwardStrategy English Doc
* test=document_fix, fix syntax
* test=document_fix, refresh API.spec
* test=document_fix, refine api spec
* test=document_fix, refine api spec
* 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.
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?
* Add support for new QAT models
test=develop
Co-Authored-By: Michał Gallus <michal.gallus@intel.com>
Co-Authored-By: Wojciech Uss <wojciech.uss@intel.com>
* fixed fps results
test=develop
* fix top5 accuracy drop problem
* updated for new QAT models
* skip quantizing average pooling - dirty but working
* add missing pass
* added missing conv+brelu fuse pass
* removed a call to non-existent pass
test=develop
* renamed pass
test=develop
* Adjust finding pooling scale to newest QAT models
* Remove unnecessary code from quantization_mkldnn_pass
* Copy Pooling input scale to output scale in QAT
* Refactor & remove unused code in QAT
* Incorporate fp32 FC into QAT
test=develop
* Enable graph drawing with debug flag
test=develop
* Add tests for QATv2
* Fix paths for QATv2 models
test=develop
* Add option to save transformed int8 qat model
test=develop
* Remove redundant lines from qat mkldnn pass
test=develop
* Delegate disablement of avg pooling to qat
test=develop
* fix CI bug, test=develop
* Follow Wangzhen's Review, test=develop
* Update API.spec
test=develop
* Name False in (is_unsigned, TensorScale) tuple
test=develop
* 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
* 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
* test=develop, refoctor name to make it easier to understand
* test=develop, refoctor name to make it easier to understand
* test=develop, fix multi-gpu failed problem , add Tracer tests, change PADDLEENFORCE to PADDLEENFORCE_EQ
* test=develop, fix ut failed on parallel se-resnext
* test=develop, change one more PADDLE_ENFORCE
* support auto prune in dygraph mode
* test=develop, support auto prune
* test=develop, merge develop conflict
* test=develop, fix test_layer and test_tracer ut
* test=develop, fix bug which may cause stop_gradient disabled with a list of backward inputs
* 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
* 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
* test=develop, refoctor name to make it easier to understand
* test=develop, refoctor name to make it easier to understand
* test=develop, fix multi-gpu failed problem , add Tracer tests, change PADDLEENFORCE to PADDLEENFORCE_EQ
* test=develop, fix ut failed on parallel se-resnext
* test=develop, change one more PADDLE_ENFORCE
* 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
* 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
* fix warpctc.dll not found issue, test=develop
* revert the linux platform change, test=develop
* delete warpctc_lib_path.h.in, test=develop
* add SetPySitePackagePath function
* fix warpctc.dylib not found issue on Mac, test=develop
* improve the paddle lib path setting logic, test=develop
* fix mac ci issue caused by test_warpctc_op unittest, test=develop
* tweak code, 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
* 1 add trt fp16 support
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
* 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
* 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
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
* fix prepare context redundant code problem, optimize executor by caching create_varaiables
test=develop
* supports collective training in executor
* make fetch_list runable with variables, add more unittest for use_program_cache
test=develop
* fix comment
test=develop
* use unique name for nccl_id
* supports output to stream in program_to_code
* insert sync_comm_stream before regularization; add skip_op_callstack capability in program_to_code
* set op role in collective training
* add collective op role
* remove orig file
* add build optimizer by strategy
* add collective strategy
* refine collective strategy
* add multi-process role maker
* refine strategy building factory so that we can easily plugin more strategy
* scale loss grad in collective sgd transpiler
* add support for distributed fc
* code format
* revert some features for dist fc
* add support for distributed fc training
* fix prepare context redundant code problem, optimize executor by caching create_varaiables
test=develop
* supports collective training in executor
* make fetch_list runable with variables, add more unittest for use_program_cache
test=develop
* use unique name for nccl_id
* supports output to stream in program_to_code
* insert sync_comm_stream before regularization; add skip_op_callstack capability in program_to_code
* set op role in collective training
* add collective op role
* fix comment
test=develop
* remove orig file
* add build optimizer by strategy
* add collective strategy
* refine collective strategy
* add multi-process role maker
* refine strategy building factory so that we can easily plugin more strategy
* scale loss grad in collective sgd transpiler
* add support for distributed fc
* code format
* revert some features for dist fc
* add support for distributed fc training
* test=develop
add collective op unittest standard
* test=develop
remove the test_collective directory
* test=develop
remove the test_collective directory
* remove slicegather test
* code format for reducescatter
* update attr of shard_index_op
* Modify macro nccl_helper
* remove test without distribute
* macro collective_helper
* marcro update
* test=develop
update support python3.5
* test=develop change gpu memory use to 0.1 when test
* test=develop
update ut equal func
* test=develop
set flags to 1.5
* test=develop fix pickle dumple py35
* test=develop
fix divide in slice and add sync_comm_stream
update atol and rtol to 1e-05
rm shard_index op and test
modify read input from file to read from memory
remove origin_program in framework and add i/o in c_sync_calc_stream
* test=develop update unittest sync operator I/O
(1) use channel instead of vector/BlockingQueue in Dataset，to keep same with existing implementation, and make code more readable and flexible (dataset single output channel or multi output channel). one previous memory out of limit problem is cause by not release memory after training.
(2) add Record because MultiSlotType costs too much memory (80B)，fix memory out of limit problem.
(3) add Channel, Archive in paddle/fluid/framework
(4) change dataset from shared_ptr to unique_ptr in pybind
(5) move create/destroy readers from trainer to dataset
(6) move shuffle from datafeed to dataset. dataset holds memory, datafeed is only for load data and feed data to network.
(7) fix thread num bug of Dataset when filelist size < thread num
(8) support set_queue_num in InMemoryDataset
Leo Chen
songyouwei
Zeng Jinle
Zhaolong Xing
xujiaqi01
zhaoyuchen2018
石晓伟
Zhang Ting
Zhen Wang
Chen Weihang
hutuxian
tianshuo78520a
tangwei12
wangchaochaohu
yaoxuefeng
Wilber
Yiqun Liu
zhongpu
Huihuang Zheng
123malin
zhouwei25
flame
mapingshuo
liym27
Aurelius84
Thunderbrook
Dong Daxiang
WangXi
hong
633WHU
Pei Yang
liu zhengxi
Jiabin Yang
Chengmo
qingqing01
Yang Zhang
Wojciech Uss
chengduo
Tao Luo
liuwei1031
chengduo
gongweibao
Yi Liu
xsrobin
lujun
HaoRen
Sylwester Fraczek
tensor-tang
wopeizl
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