* supports multiple NCCL communicators preserved in NCCLCommContext
test=develop
* add ut for c_comm_init_all operator and fix cuda resource release problem
test=develop
* support tensor input with padding for warpctc op
* merge with develop
* test=develop
* modified python API examples test=develop
* nn.py is modified for code coverage test=develop
* update documents info about warpctc op in API.spec test=develop
* add test_warpctc_with_padding in test_layers test=develop
* add warning log for cuda_version back to warpctc_op.cc
* modify API.spec for warpctc op test=develop
* modify API.spec
* update warpctc test to new CompiledProgram API test=develop
* modify code examples for warpctc op test=develop
* modify API.spec for warpctc op test=develop
* modify API.spec for warpctc op test=develop
* Implement the operator with sprase matrix multiply
* Update the URL of mklml library.
test=develop
* Disable MKLML implematation when using no-linux.
test=develop
* optimize bp with mkl sparse matrix
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
* Implement the operator with sprase matrix multiply
* Update the URL of mklml library.
test=develop
* Disable MKLML implematation when using no-linux.
test=develop
* Ignore the deprecated status for windows
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.
* remove unused DefaultGradOpDescMaker in REGISTER_OPERATOR(), test=develop
* remove SplitIdsOpGradMaker since it is buggy and not tested, update spec file, test=develop
* instag lod tensor impl
* First PR for instag
* First PR for instag
* Before adding Selection Rows.
* Change name from instag to filter_instag, add upgrade the impl of filter_instag
* Change name from instag to filter_instag, add upgrade the impl of filter_instag
* Fix yapf error in gradient_checker.py to pass Travis-CI
* Fix Filter Instag Grad test=develop
* Fix Filter Instag Grad test=develop
* 1) Fix API.spec, add filter_instag Op. 2) Add Vector Support for CUDA. test=develop
* Impl Loss_weight and empty output handler
* change Loss Weight datatype to Float32, and add Loss Weight as 2nd output
* 1) Support Tensor Input(without LOD) 2) Add Unit test
* Filter By Instag Final test=develop
* Update API.spec for filter_by_instag test=develop
* Update API.spec for filter_by_instag 2 test=develop
* Add Filter By Instag Coverage
* code format of test_layers.py
* code format test_layers.py test=develop
* Make API args more readable test=develop
* Make API args more readable and pass code format test=develop
* Filter By Instag Op, Rename Map to Index Map test=develop
* Filter By Instag Op, code format err in filter_by_instag_op.cc test=develop
* Filter by instag op: code format of cpp files test=develop
* Filter by instag Op: Api spec modification test=develop
* Filter by instag Op: Api spec doc id modification test=develop
* Filter by instag Op: Api spec and doc preview test=develop test=document_preview
* Filter By Instag Op, fix doc erro test=document_preview test=develop
* Filter By Instag Op, fix doc err and Api spec test=document_preview test=develop
* Filter By Instag Op, fix Api spec test=document_preview test=develop
* Filter By Instag Op, fix Paddle Encoforce deprecated warning test=document_preview test=develop
* Filter By Instag Op, fix Paddle Encoforce deprecated and code format warning test=document_preview test=develop
* add hard_swish activation op (new op)
test=develop
* remove redundancy files
* modify document content of HardSwish OP
* add API test in test_layers.py
* add dynamic_graph for test_hard_swish
* 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
* test=develop
Add the op of unique_with_counts, the op is calc the unqiue input of data, and output the corresponding indices and count of data.
* test=develop
Check the input and dtype in the op of unique_with_counts
* test=develop
test=document_preview
update the API.spec for `unique_with_counts`, at the same time, optimize the python api in the op of `unique_with_count`
* test=develop
test=document_preview
Fix some python api problem in the op of `unique_with_counts`, and change the error messsage in this op.
* Fix some API problem in the op of `unique_with_counts`
test=develop
test=document_preview
* test=develop
test=document_preview
Fix the api sample of op `unique_with_counts`, and update api.spec
test=develop
- Extracted key generation from FWD and GRAD into separate function
test=develop
- Compilation fix
test=develop
- another compilation
test=develop
* fix security issue, test=develop
* bug fix, test=develop
* throw an exception when null pointer data with non-zero length PaddleBuf is passed, 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
* support center loss
* change tensor copy api to high level api tensorcopy
* test=develop rewrite the center_loss cuda_kernel to make it faster
and add document of the center loss api,also update test function
* test=document_preview test=develop
update document of center loss
* test=document_preview test=develop
modify API.spec modify test code remove nouse const_cast
* change INT8 to template so that checking dst_dt with if-else could be removed. CI will be enabled after fixing reviews
* reverse user_residual_memory_p and user_bias_memory_p declaration scope
test=develop
* extend matmul op to support multiple head multiplication
With the support of multiple head, the multiplication of two big matrixes is
split into multiplication of several (head_number) small matrixes. e.g. if
Mat A is [3, 24] and Mat B is [24, 4], when multiple A and B with head_number
as 4, Mat A will be split as 4 matrix of [3, 6] and Mat B will be 4 matrix of
[6, 4]. The result of final matrix will be 4 matrix of [3, 4], i.e. [3, 16].
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)
* Add GPU implementation for `prelu` backward pass
test=develop
* Fix logic error in `prelu` GPU backward and simplify a bit
test=develop
* Fix `prelu` backward CUDA implementation
test=develop
CPU version was not used actually, so test passed
* 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
* rename mkldnn set/get_cur_thread_id() to set/get_cur_mkldnn_session_id()
test=develop
* update session id definition and adjust logic for default behavior
test=develop
* reset logic in mkldnn reuse as most of cases work in default.
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 bug in quantize kernel which cause crash in vgg16/19 model
test=develop
* refine the code to reduce verbose code; test=develop
* remove useless code; test=develop
1. some key generation method is not aligned with PR#17965
2. enlarge ptr lifetime to avoid memory release if SetBlob fails
otherwise it will get core dump.
test=develop
* 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. fix the bug that out_put_var in SaveSelectedRows would be empty string
2. use merge_sparse_lookup_table to replace sum op for load_persistables_for_inference
3. fix the bug in _clone_var_in_block_ when the var is SELECTED_ROWS.
* test=develop
fix type error of std::pow in sigmoid_focal_loss_op.cu and sigmoid_focal_loss_op.h
* test=develop
fix wrong code stype in sigmoid_focal_loss_op.cu and sigmoid_focal_loss_op.h
* 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().
* test=develop add target assign for retinanet
* test=develop
run ci
* test=developp
add test_layers
* test=develop
add APi.spec
* test=develop
alter round 1
* test=develop
alter rpn_target_assign_op.cc
* test=develop
alter test_rpn_target_assign_op.py
* test=develop
alter rpn_target_assign_op.cc
* test=develop
alter API.spec
* test=develop
alter paddle/fluid/operators/detection/rpn_target_assign_op.cc
* test=develop
alter rpn_target_assign_op.cc
* test=develop
alter python/paddle/fluid/layers/detection.py
* test=develop
alter paddle/fluid/API.spec
* refractor the function ConvFwdPrimitiveDesc
test=develop
* change according to review
test=develop
* use pointer way without boost::optional
test=develop
* pass vector to function by reference instead of raw vector
test=develop
* change pointer to shared_ptr
test=develop
* test=develop
The scatter op has a calc bug when the indices has same index, the scatter op use overwrite mode to calculate the same index, fix this bug by using the accumulate mode to calculate the same index.At the same time, the gather op has the same bug when the op calc the grad. And we use the lib of open-blas and eigen to optimize the time cost in accumulate mode.
* test=develop
Fix some code format problem, and the same time add the test case in gather and scatter op
Fix bug in sequence_unpad op, when allocate the output memory do not match actual memory, check memory failed. Fix this bug by allocating the output memeory in correct code position.
* add deformable psroi pooling
* test=develop
* test=develop
* test=develop
modify format
* fix bug
* test=develop run ci
* test=develop
add API.spec
* add test_layers.py
* run ci again
* test=develop
run ci again
* run ci again
* test=develop
run ci again
* test=develop
run ci again
* test=develop
run ci again
* add space between two lines
* test=develop
add space between two lines
* test=develop
add space between lines
* test=develop
modify comment in nn.py
* test=develop
add space between two lines
* test=develop
add space between two lines
* update API.spec
* run ci again
* test=develop
run ci again
* rerun ci
* test=develop
rerun ci
* change input shape
* run ci
* test=develop
run ci
* modify format of nn.py
* test=develop
* test=develop
* test=develop
update API.spec
* test=develop
fix API doc
* modify API comment
* modift API comment
* test=develop
update API.spec
* test=develop
modify comment
* test=develop
modift comment
* test=develop
modift comment
* test=develop
update API.spec
* test=develop
modify comment
* test=develop
add inference in nn.py
* test=develop
update API.spec
* test=develop
resolve confict
* test=develop
update API.spec
* add unfold op
test=develop
* fix divide bug in python3 when calculating output width and height
test=develop
* add name=None in python api, move redundant code into inline function
* try to trigger ci for this code
test=develop
* Enable seq_pool op to accept len 0 input
test=develop
* Update sequence_pool's api
test=develop
* Add more unittest cases for seq_pool op
test=develop
* Remove legacy comments
test=develop
* Don't use template in op maker
test=develop
* fix the bug of mobilenet-ssd INT8 inference without overloading GetHash
test=develop
* remove the out_grad->format() in TransposeMKLDNNGradOpKernel
test=develop
* Enhance fused_elementwise_activation op.
test=develop
* Move the api fused_elementwise_activation to contrib.
test=develop
* Add including files.
test=develop
* Add the support of sigmoid in fused_elementwise_activetion op.
* Update API.spec.
test=develop
* Optimize the concat and split kernel for special cases that the number of inputs/outputs is 2.
test=develop
* Refine codes.
test=develop
* Correct the condition.
test=develop
* Move the define of tmp_data outside the if statement.
* Print the cudnn minor version.
test=develop
* Fix the case when in_num/o_num is 1 in concat/split op.
test=develop
* Remove const_cast.
test=develop
* add INT8 conv+relu6 fuse and enbale mobilentv2 INT8 test
test=develop
* change fasle and 0.0 to fuse_brelu and brelu_threshold
test=develop
change the "fuse_relu||fuse_brelu" to "unsigned_output"
test=develop
* Use relu instead of brelu as INT8 post-op because INT8 brelu is not enabled in mkldnn v0.18
test=develop
* continuous-integration fix
test=develop
* add Concat quantization
add unit test for quantizing concat
fix for wrong value when the input is not in map of calculated scales
add use_quantizer to concat_op.cc
add scale_algo rules for concat
test=develop
* missing fix for multiple inputs quantize-squash
* wojtuss review fix: adding comment
test=develop
* fluid int8 train and trt int8 predict align.
trt int8 predict init
op converter
* 2. align fluid int8 train and trt int8 inference.
enhance quant dequant fuse pass
enhance op converter, trt engine, trt engine op, trt subgraph pass.
* 3. add delete_quant_dequant_pass for trt
test=develop
* 4. add the missing file
test=develop
* 5. i modify the c++ interface, but forget to modify the pybind code
fix the IS_TRT_VERSION_GE bug, and fix elementwise op converter
test=develop
* fuse mul and elementwise add to fc
* Reimplement the FC forward operator
* Fix FC MKLDNN integration by transposing weights
* Add FC MKLDNN Pass
test=develop
* FC MKLDNN Pass: change memcpy to std::copy
* Fix MKLDNN FC handling of mismatch input and weights dims
* Lower tolerance for MKL-DNN in resnet50 test
test=develop
* Adjust FC to support MKLDNN Op placement
test=develop
* Adjust Placement Op to set use_mkldnn attribute for graph
test=develop
* MKLDNN FC: fix weights format so that gemm version is called
test=develop
* FC MKLDNN: Remove tolerance decrease from tester_helper
* FC MKL-DNN: Refactor the code, change input reorder to weight reorder
* MKL-DNN FC: Introduce operator caching
test=develop
* FC MKL-DNN: Fix the tensor type in ExpectedKernelType
test=develop
* FC MKL-DNN: fix style changes
test=develop
* FC MKL-DNN: fallback to native on non-supported dim sizes
test=develop
* FC MKLDNN: fix CMake paths
test=develop
* FC MKLDNN: Refine placement pass graph mkldnn attribute
test=develop
* Fix Transpiler error for fuse_conv_eltwise
test=develop
* Fix missing STL includes in files
test=develop
* FC MKL-DNN: Enable new output size computation
Also, refine pass to comply with newest interface.
test=develop
* FC MKL-DNN: enable only when fc_mkldnn_pass is enabled
* FC MKL-DNN: Allow Weights to use oi or io format
* FC MKL-DNN: Adjust UT to work with correct dims
test=develop
* Enable MKL DEBUG for resnet50 analyzer
test=develop
* FC MKL-DNN: Improve Hashing function
test=develop
* FC MKL-DNN: Fix shape for fc weights in transpiler
* FC MKL-DNN: Update input pointer in re-used fc primitive
* Add log for not handling fc fuse for unsupported dims
test=develop
* FC MKL-DNN: Move transpose from pass to Op Kernel
test=develop
* FC MKL-DNN: Disable transpose in unit test
test=develop
* FC MKL-DNN: Remove fc_mkldnn_pass from default list
* Correct Flag for fake data analyzer tests
test=develop
* FC MKL-DNN: Add comment about fc mkldnn pass disablement
test=develop
* FC MKL-DNN: Disable fc in int8 tests
test=develop
* fix quantize_squash_pass segfault when there is no tensor linked do Bias input
test=develop
* add googlenet test
test=develop
* fix concat CreateKey not using input format
test=develop
* Relu6 is the bottleneck op for Mobilenet-v2. As the mkldnn supports the conv/relu6 fusion, we implement it fusion via cpass way. Due to the int8 enabling for this fusion will be supported in MKLDNN v0.20, so this PR is focused on the fp32 optimization.
Below table shows the benchmark(FPS) which measured on skx-8180(28 cores)
Batch size | with fusion | without fusion
-- | -- | --
1 | 214.7 | 53.4
50 | 1219.727 | 137.280
test=develop
* Fix the format issue
test=develop
* Add the missing nolint comments.
test=develop
* Fix the typos.
test=develop
* Register the conv_brelu_mkldnn_fuse_pass for the MKLDNN engine.
test=develop
* Adjust the indentation.
test=develop
* Add the test_conv_brelu_mkldnn_fuse_pass case.
test=develop
* Slightly update the code per Baidu comments.
Let the parameter definition embedded into the code.
That's will make the code easy to understand.
test=develop
* Optimize the elementwise op with CUDA kernels.
test=develop
* Support setting of attr in op config file.
test=develop
* Add the support the setting dtype and initializer in config.
test=develop
* Save workspace.
* Add initializer "zeros".
test=develop
* Fix compiling error.
* Support the use of existed file to initailize tensor in op_tester.
* Use eigen to optimize the elementwise_add/mul for the case that x and y have the same dims.
test=develop
* add double grad for elementwise_mul. test=develop
* remove comment. test=develop
* fix grad sum. test=develop
* fix for axis expand. test=develop
* add test for axis expand. test=develop
Yi Liu
Huihuang Zheng
vincentXiyu
tangwei12
翟飞跃
Leo Chen
Aurelius84
Adam
wangguanzhong
zhaoyuchen2018
Yihua Xu
wangchaochaohu
Zhaolong Xing
qingqing01
Zeng Jinle
zhang wenhui
silingtong123
gongweibao
Kaipeng Deng
Yibing Liu
chengduo
Jiawei Wang
huangjun12
joanna.wozna.intel
ShenLiang
Zhang Ting
Yiqun Liu
pawelpiotrowicz
Liufang Sang
hutuxian
石晓伟
wawltor
Jacek Czaja
LielinJiang
liuwei1031
HaoRen
Leo Zhao
wopeizl
baojun
danleifeng
lidanqing
Physher
FDInSky
Bai Yifan
JesseyXujin
Bob Zhu
whs
chengduo
Tao Luo
cjt222
guru4elephant
Yang Zhang
Hongyu Liu
Jiabin Yang
zhoukunsheng
Yi Liu
Brian Liu
HaoRen
Sylwester Fraczek
tensor-tang
Qiao Longfei
songhao
xiaoting
FlyingQianMM
Wojciech Uss
Guo Sheng
lujun
SunGaofeng
mozga-intel
YishengCheng
Krzysztof Binias
Michał Gallus
Sevin F. Varoglu
guomingz
lvmengsi
Yan Xu
Yihua Xu