* Enable generating code for a given subgraph.
* Support sorting the subgraph.
* Remove the rearange of expressions because we use the sorted subgraph directly.
* Enable generating code for a subgraph which is composed of grad ops.
* Use expression information to check the accuracy in unittest.
* Separate load and store from computation expressions.
test=develop
* Improve the loading statements in generated codes.
test=develop
* Remove unused arguments from formal list.
test=develop
* Add the definition of operation in fusion_group.
* Use operations in OperationMap to detect fusion_group of elementwise pattern.
* Add namespace fusion_group in code_generator.
* Use operations recorded in OperationMap to generate code.
* Remove implementation codes to .cc file.
* Refine Operation and CodeGenerator to make it easier to generate code for grad_op.
Refine the unittest for better reuse.
* Avoid recording the template's keyword in a array.
* Support the generating of code for grad_op and add unittest.
test=develop
* Remove replaced_element_in_order and use use number instead.
test=develop
* support no need buffer vars in dygraph, test=develop
* fix inference compilation error, test=develop
* update no_need_buffer_vars_inference, test=develop
* add unittests for no_need_buffer_vars_context, test=develop
* refine no_need_buffer_vars by return ref, test=develop
* polish some codes, test=develop
* Add fusion_group_pass and elementwise pattern.
* Rewrite the detector of elementwise group.
test=develop
* Add a comment in codegen.
* Add more unittest cases.
test=develop
* Move code_generator related code to fusion_group directory.
* Correct the including path.
* Add the definition of SubGraph and finish the insert of fusion_group op in pass.
* Insert graph_vis_pass in tester to visualize the graph for debug.
* Follow Wangzhen's comment in PR 18970, test=develop
* Review comments, test=develop
* Leave fake quantization around mul
test=develop
* Replace Fake with Real Quantized Mul
test=develop
* Fix bug in quantize placement pass
Nodes in the graph now have checked type instead of node name when they are to be marked for quantization test=develop
* Add fc_elementwise_layernorm_fuse pass and unittest.
* Add fused_fc_elementwise_layernorm op and its GPU kernel.
test=develop
* Apply fc_elementwise_layernorm_fuse_pass to GPU inference.
* Add the setting of attrs in the definition of binary_op.
test=develop
* Add comment.
* Implement the unittest.
test=develop
* Change the unittest name of layer_norm.
test=develop
* Refine the codes related to fc op.
* Add GPU implementation for fc functor.
* Apply fc_fuse_pass in GPU inference.
test=develop
* Change the cmake for fc op.
* Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ.
* Add an attribute to set the activation type in fc_op.
* Enhance the unittest of fc_op.
test=develop
* Remove the declaration of FCOpGrad back to the header file.
test=develop
* Set default value for newly added arguments in test_fc_op.
test=develop
* Enhance fc_fuse_pass to enable fusing relu.
* Allow print the shapes of var_desc in graph.
test=develop
* Enhance fc_fuse_pass_tester.
* Remove the use of PADDLE_ENFORCE.
test=develop
* Correct the number of ops after fusing.
test=develop
* Fix a typo.
test=develop
* Set activation_type to null when there is no relu in fc.
test=develop
* Refine fc_fuse_pass's codes.
* Enable the set of shape for tensor.
* Refine repeated_fc_relu_pass and add unittest.
test=develop
* Open fuse all reduce op
test=develop
* Add Fuse optimization op log
* Add log in fuse_optimizer op pass and fuse all_reduce op pass
* replace with boost::optional<bool>
test=develop
* Polish code
test=develop
* fix code coverage
test=develop
* Refine the codes related to fc op.
* Add GPU implementation for fc functor.
* Apply fc_fuse_pass in GPU inference.
test=develop
* Change the cmake for fc op.
* Change PADDLE_ENFORCE to PADDLE_ENFORCE_EQ.
* Add an attribute to set the activation type in fc_op.
* Enhance the unittest of fc_op.
test=develop
* Remove the declaration of FCOpGrad back to the header file.
test=develop
* Set default value for newly added arguments in test_fc_op.
test=develop
* Add a interface to enable cudnn for inference.
* Add cudnn_placement_pass.
test=develop
* Set the default value of cudnn_enabled_op_types to null.
test=develop
* Write the common basic class, placement_pass_base, to refine the codes.
test=develop
* Call EnableCUDNN in unittest.
test=develop
* Refine cudnn_placement_pass tester.
* Enable the testing of cudnn_placement_pass in inference's unittest.
test=develop
* Add the check of op kernels.
test=develop
* Add simplify_with_basic_ops_pass to replace dropout_op with scale_op when is_test is true.
test=develop
* Delete dropout_op directly when upscale_in_train is true.
test=develop
* Improve the debug string, adding the print of op_desc information.
* Fix the case when dropout's input x is reused as the next op's output.
* Add the pass to inference.
test=develop
* Change the log level.
test=develop
* Add unittest for inplace case.
* Add comment to explain the pass.
* Apply the pass for CPU inference.
test=develop
* Fix the typo.
test=develop
* Add the check of AttrType.
test=develop
* fix correctness of the communicator
* fix a bug in send thread when sending var context is empty, test=develop
* add lookup_table_prefetch_op and prefetch optimize, test=develop
* remove remote prefetch GPU supported
* word2vec force with CPU, test=develop
* test dist remote lookup table force with CPU, test=develop
* 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
* update paddle-trt for:
1. fix bug: when batch > 2, core in split plugin.
2. add leaky_relu trt5.0 support (yolov3 from 65ms to 42ms.)
3. add new attr to dropout.
4. shuffle channel, swish, relu6 support
test=develop
* 1. fix ci
test=develop
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)
* 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
* 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 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
* 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
* 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
* add use_cuda to inplace pass,test=develop
* add test softmax_with_xe_inplace test,test=develop
* fix potential inplace bug
test=develop
* add more skip vars in mem opt pass,test=develop
* follow comment,test=develop
* follow comments,move duplicate out arg check to program->graph,test=develop
* fix bn fuse vardesc and add model saver
test=develop
* unify save model in test helper
test=develop
* fix mkdir on windows
test=develop
* remove magic number use bn bias var desc
test=develop
Chen Weihang
Yiqun Liu
Zeng Jinle
Zhaolong Xing
WangXi
joanna.wozna.intel
Wilber
hong
wangchaochaohu
石晓伟
wopeizl
Pei Yang
zhaoyuchen2018
Adam
bingyanghuang
chengduo
baojun
Tao Luo
tangwei12
liuwei1031
juncaipeng
chengduo
Huihuang Zheng
gongweibao
Michał Gallus
Sylwester Fraczek
gongweibao
mozga-intel
Jacek Czaja
Qiao Longfei
guomingz
Zhen Wang
tensor-tang
Yihua Xu