* 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().
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
Note the append_batch_size variable is doing prepend. We should
change the name, but due to backward compatibility, I suggest to
change at v2.0. Not now.
test=develop
* improve the API Sample of DataFeeder, memory_optimize and release_memory, test=develop
* update API.spec, test=develop, test=document_preview
* tweak the code format of feed API, test=develop
* update API.spec, test=develop
* improve doc for DataFeeder and default_main_program, test=develop
Fix the following API examples:
paddle.fluid.scope_guard
paddle.fluid.backward.append_backward
paddle.fluid.cpu_places
paddle.fluid.cuda_pinned_places
paddle.fluid.cuda_places
paddle.fluid.in_dygraph_mode
paddle.fluid.CUDAPlace
paddle.fluid.CPUPlace
paddle.fluid.CUDAPinnedPlace
* Fix data and reader related api doc
* Fix data and reader related api doc
Review and fix the example code in some reader related API doc.
These APIs are:
Fix existing API example codes:
paddle.fluid.io.PyReader
paddle.fluid.layers.batch
paddle.fluid.layers.data
paddle.fluid.layers.Preprocessor
paddle.fluid.layers.py_reader
paddle.fluid.program_guard
Add new example codes:
paddle.fluid.io.PyReader.decorate_batch_generator
paddle.fluid.io.PyReader.decorate_sample_generator
paddle.fluid.io.PyReader.decorate_sample_list_generator
paddle.fluid.io.PyReader.reset
paddle.fluid.io.PyReader.start
test=develop
* Add changes to API.spec after changing doc.
test=develop
* Add blanks after python example code
test=develop
* Add blank line at py_reader example code
test=develop
* Merge API.spec
test=develop
* Modify reader.py based on reviewer's comment
test=develop
* Modify API.spec after changing doc
test=develop
* Change reader.py based on reviewer's comment
* Modify example code of decorate_sample_generator
test=develop
* Fix example code of PyReader based on reviewer
test=develop
Yibing Liu
0YuanZhang0
Chen Weihang
Aurelius84
guofei
Leo Chen
Zhou Wei
Zeng Jinle
Zhang Ting
songyouwei
tianshuo78520a
zhongpu
liym27
tangwei12
lilong12
Huihuang Zheng
wangchaochaohu
Tao Luo
liuwei1031
lanxianghit
hong
Jiabin Yang
wopeizl
mapingshuo
qingqing01
ShenLiang
Wojciech Uss
chengduo
Zhen Wang
zhang wenhui
gongweibao
chengduo
Yi Liu
xsrobin
HaoRen
tensor-tang
hutuxian
xiaoting
Huihuang Zheng
lujun
minqiyang
Qiyang Min
guru4elephant