* 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
* append optimize op in the grad block of current block if current block is in control flow. test=develop
* add conditional grad op when optimizer used in control flow. test=develop
* add comment and modify typo. test=develop
* fix append_backward to support control flow. test=develop
* add test. test=develop
* fix copy_var_to_parent_block and conditional_block_grad. test=develop
* fix bug: revert to append conditional_block_grad vars to sub grad block. test=develop
* fix bug: revert to assign var to parent block even if var already is in parent block
* fix bug: consider outputs is empty. test=develop
* move _rename_grad_ out. test=develop
* modify code according to reviews from Huihuang. test=develop
* modify code according to reviews from Jinle. 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
* 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
* polish minimize en doc
* polish adam optimizer en doc
* polish adamax optimizer en doc
* polish adagrad and decayed adagrad optimizer en doc
* polish model average en doc, test=develop, test=document_fix, test=document_preview
* self review and further polishing doc
* update API.spec, test=develop, test=document_fix
* update fluid.data api in examples, test=develop, test=document_fix
* update fluid.data inferface, test=develop, test=document_fix
* replace -1 by none, test=document_fix
* add recompute based checkpoints methods for large batch training
test=develop
* add append_backward_with_forward_recomputation
test=develop
* refine optimizer
test=develop
* update backward and optimizer
test=develop
* make Variable usable
test=develop
* add recompute code
* refine optimizer
test=develop
* refine addup _append_backward_ops_with_checkpoints_
1) for recompute part, just cache the grad_op_desc without appending to block
2) before appending grad_op_desc to backward part, addup_repetitive_vars, remove unused branch
test=develop
* make method private
* add recompute strategy into DistributedStrategy
test=develop
* checkpoint version3
test=develop
* remove some print information
test=develop
* remove unused sumop
test=develop
* try to fix recompute with graph building modules
* add input names to vars should be held
* add memory debug tool
* backup backward
* Fix bugs
* add backward desc for op not in any segments
* add exception info for sub_block
test=develop
* modify code style
test=develop
* modify code style
test=develop
* remove print functions
test=develop
* add API spec
test=develop
test=document_preview
* make Recompute a child class of Optimizer
test=develop
test=document_preview
* add API spec
test=develop
test=document_preview
* modify API spec
test=develop
test=document_preview
* add document for Recompute
test=develop
test=document_preview
* change API doc of Rcompute
test=develop
test=document_preview
* code cleaning
test=develop
test=document_preview
* modify API spec
* fix bugs when segments hold no element
* add testcase for Recompute Optimizer
test=develop
test=document_preview
* add test for apply_gradient, and code cleaning
test=develop
test=document_preview
* add test case for load function
* enable CI
test=develop
test=document
* add test case
test=develop
test=document_preview
* add sample code for 4 function of recompute optimizer
test=develop
test=document_preview
* 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
Add Pipeline Concurrency Train Mode:
- Cpp: pipeline_trainer & section_worker
- Python: PipelineOptimizer
- Add a new data_feed type: PrivateInstantDataFeed
- Add a test demo of pipeline trainer and the test model is gnn
- Do not support win32 now
* save optimizer related vars in dygraph
* test=develop, add optimizer save and load
* test=develop, add optimizer save and load
* test=develop, merge code and add multi-optimizer save and load
* test=develop, fix test_imperative_checkpoint
* test=develop, fix include error
* test=develop, fix include error
* test=develop, renew api spec
* test=develop, refine code
* test=develop, set default value for checkpoint
* test=develop, fix ci error
* test=develop, change API.spec and make api more readable
* test=develop, refine version and time stamp
* test=develop, add example code and refine code
* test=develop, refine doc
* test=develop, change version
* add gradient clip in minimize; test=develop
* fix bug; test=develop
* fix format; test=develop
* move new grad clip to dygraph/grad_clip.py; test=develop
* fix lr decay and grad clip test; test=develop
* seperate dygraph grad clip; test=develop
* fix grad clip test; develop
* fix api spec bug; test=develop
* add blank line, test=develop,test=document_preview
to fix format problem
* fix the api example for create_global_var, create_parameter, SGDOptimizer, RMSPropOptimizer, MomentumOptimizer, LarsMomentumOptimizer, FtrlOptimizer
test=develop
* add example for adamoptimizer
fix API.spec
test=develop
* test=develop
* test=develop
Leo Chen
Zhang Ting
WangXi
mapingshuo
tianshuo78520a
zhaoyuchen2018
Aurelius84
hong
zhongpu
Yibing Liu
liym27
Chen Weihang
Aurelius84
tangwei12
hutuxian
Zeng Jinle
Kaipeng Deng
wopeizl
jhjiangcs
chengduo
gongweibao
Jiabin Yang
LielinJiang
xsrobin
lujun
wopeizl
Qiao Longfei
chengduo
gongweibao
minqiyang
Qiyang Min
Xin Pan