* expose and unify the Tensor concepts to the user
* expose tensor to user
* add copy place for Tensor
* add copy place for Tensor
* add note
* add macro PADDLE_WITH_CUDA
* remove RUN_TYPE=DIST
* fix some error
* add more settings for distributed strategy
Basically, DistributedStrategy has several parts of configurations:
- BuildStrategy: the same as paddle.fluid.BuildStrategy, but the distributed arguments are moved out of BuildStrategy
- ExecutionStrategy: the same as paddle.fluid.ExecutionStrategy
- collective communication configs: nccl_comm_num, hierarchical allreduce and so on
- distributed algorithms: async_update(mainly used in PS), lars, lamb and so on
* Refine Model
1. Take the network (instance of Layer) as the input of Model.
2. Refine set_dict/load_dict of Layer.
3. Refine Input interface, so update code sample about Input
* Compatible int32 and int64 for attr in op slice/strided_slice. test=develop
* Polish code in nn.py test=develop
* Fix bug: set the same dtype for the inputs of elementwise_add. test=develop
* Convert int32 to int64 in slice op to avoid data overflow. test=develop
* Convert int32 to int64 in strided_slice_op to avoid data overflow. test=develop
* support to train in static
* support to independent decorator
* remove in_dygraph_mode condition in ProgramTranslator
* fix import param_guard and add train/eval test=develop
* Modify into ShareVarsFromScope and rm __all__ in partial_program test=develop
* Add a function to update FLAGS
test=develop
* Add a function to update FLAGS
test=develop
* expr flags
* Add a function to update FLAGS
test=develop
* distinguish public/private vars, test=develop
* fix windows issues, test=develop
* expr flag
* Add functions to get and set FLAGS
test=develop
* Add functions to get and set FLAGS
test=develop
* Add functions to get and set FLAGS
test=develop
* Add functions to get and set flags
test=develop
* Add functions to get and set FLAGS
test=develop
* Add a function to update FLAGS
test=develop
* Add a function to update FLAGS
test=develop
* Add functions to get and set flags in Paddle
test=develop
Co-authored-by: sneaxiy <sneaxiy@126.com>
* 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
* 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
* 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
* 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
* 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.
* test=develop, fix docker with paddle nccl problem
* test=develop, Add Variable api and refine dygraph related API
* test=develop, Add Variable api and refine dygraph related API
* test=develop, refine test for new api and error info
* test=develop, refine error info and test_layers
* test=develop, add API.spec
* test=devleop, fix to_string python2 and python3 compat error and refien doc
* test=devleop, add API spec
* test=devleop, update API spec
* test=devleop, update API spec
* test=develop, invoke ci
* test=develop, fix example code
* test=develop, update API spec
* test=develop, add compat test and fix inplace campat dict error
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
* 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
add support parameter inference when arguments starts or ends is a list containing integer and tensor variable;
test=develop,test=document_preview
improve slice op according to review(from hongyu). test=develop
fix slice op according to review: infer_flags, test=develop
fix slice op: improve overload operator __getitem__ to support attrs(starts and ends) are Variable.
test=develop,test=document_preview
fix test_slice_op: add TestSliceOp_decs_dim_6 to resolve conflict with test_slice_ngraph_op. test=develop
add stop_gradient=True when attr(starts) or attr(ends) is tensor Variable.
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 to and detach for Variable in dygraph, test=develop
* add detach for Variable in dygraph, test=develop
* add detach for Variable in dygraph, test=develop
* add detach for Variable in dygraph, test=develop
* add detach for Variable in dygraph, test=develop
* add detach for Variable in dygraph, test=develop
* add exception check, test=develop
add fl_listen_and_serv op for Federated_learning and fl_distribute_transpiler add this op to pserver program . This op just listen the endpoint and sum&scale.
* 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
* Update backward.py:
- If there is no input grad var in all outputs of previous ops, do not append this op into graph.
- Only apply this stragety when double backward.
* Update some double backward op.
* Update sum_op to judge whether a tensor is empty by numel or IsInitialized().
Zhou Wei
pangyoki
gongweibao
wangchaochaohu
Chen Weihang
tangwei12
Dong Daxiang
qingqing01
Leo Chen
hong
Liufang Sang
lilong12
liym27
Cindy Cai
Aurelius84
Yibing Liu
0YuanZhang0
guofei
Zeng Jinle
Zhang Ting
songyouwei
tianshuo78520a
zhongpu
Huihuang Zheng
Tao Luo
liuwei1031
lanxianghit
Jiabin Yang
wopeizl
mapingshuo
ShenLiang
Wojciech Uss
chengduo
Zhen Wang
zhang wenhui
chengduo
Yi Liu
xsrobin
HaoRen