* Remove the NGraph engine from PDPD repository
1. Each operator was removed from the operator's directory
2. Each test was removed from the unittest directory
3. The parallel executor support was removed from the PDPD
4. The CMake file was removed from the PDPD
5. The NG flags were removed from the repository
test=develop
* Remove ngraph from:
1. Cmake file
2. Python file
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* static model runner basic implement, test=develop
* add run program op to execute loaded program, test=develop
* refactor static model runner & run program op, test=develop
* reset engine.cc to resolve conflict
* adapt the change of dygraph double grad, test=develop
* refactor impl to solve control flow error, test=develop
* clear debug code, test=develop
* fix ci str compatible error & checkout dygraph grad maker & add example, test=develop
* hide api & add op test, test=develop
* fix run program op test places error, test=develop
* fix program by review comment, test=develop
* delete change var desc name, test=develop
* fix other program by review comment, test=develop
* remove _static_graph_guard, test=develop
* add selectedrows test, test=develop
* remove desc parser, test=develop
* fix detail program, test=develop
* change socpe create & add test, test=develop
* sequential reader stage 1, test=develop
* fix ut, test=develop
* fix iterable=False reset bug, add some logs and polish code, test=develop
* inference feed partial data, test=develop
* Turn on keep_order=True for test, test=develop
* enhance ut to test more cases, test=develop
* test commit for reverting
* Revert "test commit for reverting", test=develop
This reverts commit 80aef42ef52ba1ee79627d6f663a624ec4f12f58.
* add ut of merged and unmerged results, test=develop
* add more uts for coverages and add en doc of api, test=develop
* follow comments, test=develop
* change note style, test=develop
* update ScopeBufferedSSAGraphExecutor&AsyncSSAGraphExecutor&ThreadedSSAGraphExecutor&FastThreadedSSAGraphExecutor&ParallelSSAGraphExecutor&ParallelExecutor for fetching unmerged results.
* add the unit test for fetch_unmerged.
* update ut for multi-card and multi-cpu.
* add the error message and the user suggestion in FetchOpHandle. test=develop
* Add two types of Metric Calculator: MultiTaskCalculator & CmatchRankCalculator.
* Add a config for DynamicAdjustChannelNum function to denote whether we will discard the remaining instances when they are not be distributed evenly.
* Remove CPU code in Pull/PushSparse and we will add it back when testing it fully.
* Fix some known issues: such as copying persistable vars after one epoch running.
Refine PaddleBox Framework, Main functions:
* Add MetricMsg util class, which can calculate metrics like AUC, bucket_error, COPC.
* Replace FeedPass with new interface: BeginFeedPass & EndFeedPass
* Refactor Pull/Push Sparse Function in box_wrapper.
* Use CUDA Kernel to copy keys and copy feasign between tensor and boxps struct.
* Cache copied keys in pull sparse in order to reuse it in push period.
* Add the first implememtation of fusion_group op #19621 (#3)
* Add the dynamic load of nvrtc, and support runtime compiling of CUDA kernel using nvrtc.
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* Call CUDA driver api to launch the kernel compiled by nvrtc.
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* Disable for mac and windows.
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* Refine the codes to support manually specified num_threads and workload_per_thread.
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* Refine the CUDA kernel to support large dims.
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* Add DeviceCodePool to manage all device codes.
* Add the first implementation fusion_group op.
* Add unit-test for fusion_group op.
* Add the check of result.
* Add the check of nvrtc in unit-test.
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* Add comment to explain the inputs, outputs and features of fusion_group op.
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* Disable fusion_group op for mac and windows.
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* Make the compiling of device code return status instead of hanging up.
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* Add the check of whether there is CUDA driver library, and do not core dump when failing to call the CUDA driver API.
* Unify fusion_group_op's input and output names.
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* Add the check of CUDA driver library in unittest.
test=develop
* Enable generating code for a given subgraph. #21126 (#4)
* 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.
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* Improve the loading statements in generated codes.
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* Remove unused arguments from formal list.
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* Enable the detection of subgraph of grad ops.
* Generate code for detected subgraph in fusion_group_pass.
* Add an option in BuildStrategy to enable fusion_group_pass and add unittest.
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* Fix a bug when checking whether the shape of all inputs are the same.
* Add debug information.
* Remove subgraph_detector from inference/analysis to the common framework/ir directory. (#5)
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* Call subgraph_detector in fusion_group pass.
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* Disable fusion_group when WITH_GPU is OFF.
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* Refine all PADDLE_ENFORCE message.
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* Fix the case that some inputs are not defined in grad ops, and set op_role for fused op.
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* Follow review comments.
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* Enable quantize to reorder to nchw as well
* Correct FC MKL-DNN input dim requirements to accept 3D
* Improve DNNL FC format, error and 3D input handling
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* Improve error checking in FC
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* Improve PADDLE_ENFORCE messages in fc-related files
* Remove data layout attribute from obligatory pass args
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* Fix message in fc_mkldnn_pass to be logically correct
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* Implement a common python unittest to test the ir passes.
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* Save the results in np.array and support to startup on CPU.
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* Fix the unittest.
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* Add check_program to check whether the optimized program is different from the origin one.
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* Remove the inferface all_ops.
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* Add exception test in pass_test.
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* add bn and relu fuse pass
* add op attr assert and dtype assert
* fix some inputs&&outputs bugs for the fused op and pattern.
* add the unittest for fuse_bn_act_pass. test=develop
* use normative enforce statements. test=develop
* add the cpu test. test=develop
* add the support of batch_size=1 for the bn with relu op. test=develop
* add the error type for paddle throws. test=develop
* add fused_batch_norm_act and fused_batch_norm_act_grad to op_has_unsed_vars_white_list. test=develop
* Polish the PADDLE_ENFORCE in fusion_group pass related codes.
test=develop
* Correct the unittest because of the change relu_grad's formula.
test=develop
* Add the dynamic load of nvrtc, and support runtime compiling of CUDA kernel using nvrtc.
test=develop
* Call CUDA driver api to launch the kernel compiled by nvrtc.
test=develop
* Disable for mac and windows.
test=develop
* Refine the codes to support manually specified num_threads and workload_per_thread.
test=develop
* Refine the CUDA kernel to support large dims.
test=develop
* Add DeviceCodePool to manage all device codes.
* Add the first implementation fusion_group op.
* Add unit-test for fusion_group op.
* Add the check of result.
* Add the check of nvrtc in unit-test.
test=develop
* Add comment to explain the inputs, outputs and features of fusion_group op.
test=develop
* Disable fusion_group op for mac and windows.
test=develop
* Make the compiling of device code return status instead of hanging up.
test=develop
* Add the check of whether there is CUDA driver library, and do not core dump when failing to call the CUDA driver API.
* Unify fusion_group_op's input and output names.
test=develop
* Add the check of CUDA driver library in unittest.
test=develop
* Refine the calling of PADDLE_ENFORCE.
test=develop
* optimize adam speed by removing _finish_update test=develop
* fix SparseAdamFunctor param list test=develop
* Remove scale_op in expect_list of adam_op test=develop
* fix test optimizer loss assert error test=develop
* fix test optimizer loss assert error test=develop
* modify PADDLE_ENFORCE usage test=develop
* fix op_type in lamb_op.cc test=develop
* fix errors ostream format bug test=develop
* add betaPowOut in ngraph op test=develop
* fix ngraph::op api for gcc8 test=develop
* clean code test=develop
* modify struct into class test=develop
* remove code of beta1Tensor in lamb_op test=develop
* fc-dequantize squash
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* change according to reviews
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* change PADDLE_ENFORCE
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* add second test when fc-dequant do not fuse
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* change all related PADDLE_ENFORCE
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* add fake init for the trainer, fix large memory hold in the trainer
* do not merge recv vars from a remote endpoint, test=develop
* add recv and save op, merge slice var in one op, save memory
* remove hsigmoid with pull sparse, test=develop
* add file check_op_desc.py and add interface to get default value. test=develop
* add test for c++ coverage rate. test=develop
* Correct typo. test=develop
* Commit before merging develop
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* Backup after working with Huihuang logs
* Commit before deleting Huihuang debug loggings
* Commit before debug
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* Fix bug commit
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* Backup of fixing bugs
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* Clean up code
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* Fix a bug in sum_op
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* Implement Int8 FC
* Integrate FC into INT8v2
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* int8 FC: transpose weights before computing scales
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* Add support for activation_type string in FC
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* Disable MKL-DNN's FC in VGG16 and 19
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* Disable FC quantization when mkldnn FC is disabled
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* Solve PADDLE_ENFORCES in FC int8
* Fix Paddle enforces and remove const cast
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* Fix style changes
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* Fix quantizer_tester test and add fc quantization
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* Fix FC test fail on CUDA
* Remove unnecessary log from quantize placement pass
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* Add Thread ID to FC hash key
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* Add comments to MKL-DNN FC Kernel
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* Refactor quantizer
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* Fix linter issues
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* Fix crash in slim googlenet
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* Fix PADDLE_ENFORCE messages
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* Add fc padding to solve mkl performance
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* fix gpu pass and error information
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* fix fc_fuse_pass_test
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* fix error information
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* fix error information
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* fix name and add fc op padding test
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* fix attributes
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* optimize fc padding
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* fix test
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* fix fetch handler problem and refactor
when a user define FetchHandler class, he or she should initialize a handler
with variable dict. the key of a variable dict is a user defined name,
the value of a variable dict is a Varaible generated from python API.
For each fetching, a user should implement handler function in which
fetched_result_dict will be available and the user can access the fetched value
with user defined keys.
* Disable fusion_group pass for windows and mac. We will do some experiments on Linux first.
test=develop
* Print the subgraph when check failed.
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* 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
* copy some feasigns and corresponding embeddings from one sparse table to another
* copy all feasigns and corresponding embeddings from one sparse table to another
* copy all dense params from one table to another
* copy some local vars to other local vars
* Add the check of lod_level between compile-time and runtime.
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* Fix bug in check_compile_vs_runtime.
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* Fix the check of output when it is dispensiable or intermediate.
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* Share lod of x to out in match_matrix_tensor op in compile-time.
* Implement GetLoDLevel in InferShapeContext.
* Set the default value of check_compile_vs_runtime to False and enable it in test_sequence_pad_op.
test=develop
* Enable check_compile_vs_runtime in test_match_matrix_tensor.
* Add the implementation of SetLoDLevel in InferShapeContext.
* Remove the implementation of IncreaseLoDLevel and call Get/SetLoDLevel instead.
* Remove the implementation of DecreaseLoDLevel and call Set/GetLoDLevel instead.
* Refine some ops and unittests.
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* Fix a typo.
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* Remove the check of var type, and change int to int32_t.
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* Add unittest for Get/SetLoDLevel.
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* 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.
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* Enrich the type of error and declare the error type interfaces, test=develop
* adjust tests to adapt new form, test=develop
* add inference deps with error_codes.pb.h, test=develop
* restore stack iter start pos, test=develop
* polish code based review comments, test=develop
* remove duplicate code and duplicate config of master+patch
* drop all ins which has conflict slot or size < merge_size
* user only need to set merge size,if ins num of same id is not equal to merge size, just drop these ins
* user must make sure master data and patch data has no same slot whose feasigns are both non-zero, otherwise these ins will be dropped. (slot list should still be the same of both master and patch)
* 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
* Refine the cache of program, context and scope in executor.
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* Refine the unittest test_executor_and_use_program_cache.
* Add the test the PaddingRNN with use_program_cache=True.
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* Remove a check.
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* Refine the unittest to check whether it is correct when setting use_program_cache=True.
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* Refine the InferShape of ReadFrom and WriteTo op, and add comment to explain why not call ShareLoD for runtime.
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* Add comment for ReorderLoDTensorByRank op.
* Add comment for lod_tensor_to_tensor_array op to explain why only call DecreaseLoDLevel for compile time.
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* ShrinkRNNMemory op should call ShareLoD for compile time.
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* Add the implementation of IncreaseLoDLevel and add the compile-time check of lod_level in InferShape of sequence_pool.
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* Refine the unittest of DynamicRNN.
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* Change PADDLE_ENFORCE to PADDLE_ENFORCE_NE.
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* Add fusion_group_pass and elementwise pattern.
* Rewrite the detector of elementwise group.
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* Add a comment in codegen.
* Add more unittest cases.
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* 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.
* replace part of the old implementation, test=develop
* restore concat op, test=develop
* update all ops implemention & delete GetDataTypeOfVar func, test=develop
* no longer need to define all embedding layers (no one less) of all slots in each program. make trainer_param repeated in ps.proto.
* add find_distributed_lookup_table_grads instead of hard code GRAD
* support embedding stop gradient. push sparse has error before fix this.*
* fix fill sparse, skip slots which do not have embedding. each slot's embedding in a sparse table should be used in all training programs before fix this.
* fix pull sparse, skip slots which do not have embedding.
* fix collect feasign label info, skip slots which do not have embedding.
* support when there are multi sparse tables in one or multi training programs, each program can pull/push its own related sparse tables instead of all sparse tables.
* test=develop
* - Flushing mkl-dnn cache
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- Disabled clearing cache for LoadModel
- Added clearing of mkl-dnn cache when Executor is created
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- Do not clear for GPU places
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- compilation fix
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* - Moved clearing of mkl-dnn cache in destructor of executor
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* - Compilation fix
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- Reverted conditional clearing of mkl-dnn cache in Executors's
destructor
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- compilation fix
* 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.
* Follow Wangzhen's comment in PR 18970, test=develop
* Review comments, test=develop
* Leave fake quantization around mul
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* Replace Fake with Real Quantized Mul
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* 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
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?
* support change shuffle thread num
* support change train thread num
* fix receive shuffle data of each channel
* data norm stop gradient
* add check thread_tensor type and root_tensor type when merge metric
* remove sleep in shuffle, add config
* add config of pslib client to client communication
* fix xbox str
* add data norm op testcase
* add flush in trainer finalize