* 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
* update anakin-engine interfaces for content-dnn
test=develop
* support only-gpu mode of Anakin
modify eltwise parse
test=develop
* modification for thread-safe
test=develop
* Integrated template instance
test=develop
* increase template parameters
test=develop
* support MLU predictor
test=develop
* update anakin cmake files
test=develop
* update TargetWrapper::set_device
* update the initialization of anakin subgraph
test=develop
* use the default constructor of base class
test=develop
* load model from buffer with length
test=develop
* modify the access level of class
test=develop
* support anakin for bitmain arch
test=develop
* remove files
* checkout cmakelists
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
* some fixes for int8 mobilenet_ssd tester
test=develop
* change wrong data file name
test=develop
* change test images bin file from 200 images to 100 images
* change directory existence to file existence during downloading
test=develop
* reuse download_data
test=develop
* run full dataset when iterations=0
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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.
(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
* 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
* Remove layers.detection_map API
* Since uers can use fluid.metrics.DetectionMAP to calculate mAP of current-batch and cumulative-batch. layers.detection_map only can calculate cur-batch mAP.
* 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
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
* 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
* 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
* for debug
* test=develop, memory optimize for dygraph using shared_ptr
* test=develop, fix travis ci showed error
* test=develop, fix bug for recurrent usage of varbase
* test=develop, init varbase when it need to be Add
* test=develop, fix problem of recurrent gradient
* test=develop, add gradient test for recurrent varbase usage
* for debug
* test=develop, memory optimize for dygraph using shared_ptr
* test=develop, fix travis ci showed error
* test=develop, fix bug for recurrent usage of varbase
* test=develop, init varbase when it need to be Add
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
* fix the bug of mobilenet-ssd INT8 inference without overloading GetHash
test=develop
* remove the out_grad->format() in TransposeMKLDNNGradOpKernel
test=develop
* fix prepare context redundant code problem, optimize executor by caching create_varaiables
test=develop
* cache sub_scope, program, var when use_program_cache=True is set
* make fetch_list runable with variables, add more unittest for use_program_cache
* 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
* 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
* 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
* 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
* 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
* fix the bug that sub_scope_ may be null in AnalysisPredictor::Run.
* add more directions about io APIs' docs.
* update the API.spec. test=develop test=document_preview
* 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
* add conv_concat_relu fuse
test=develop
* add test code
test=develop
* added missing include with unordered_map
test=develop
* review fixes for wojtuss
test=develop
* remove 'should (not) be fused' comment statements
one of them was invalid anyway
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
* Fix examples of fluid.layers.sums.
test=document_preview
* Correct the example of DynamicRNN and its functions.
test=develop
* Add 'import paddle.fluid as fluid' to examples.
test=develop
* Update API.spec.
test=develop
* Add space lines.
test=develop
* Update the API.spec.
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