* add recordio support

* disable the openblas multi-thread on windows since no support
adjust the python script

* code style

* code style
test=develop

* add create_recordio_file_reader back

* fix code style
test=develop

* fix the gtest.cmake on windows

* fix cc_test on windows

* fix the win build
test=develop

* remove fused compile support on windows
test=develop

* add the jit support
test=develop

* add the jit support, test=develop

* add the jit support, test=develop

* add the jit back
fix compile error on windows

* rollback test=develop

* test case fix

* disable DSO by default on windows

* exclude warpctc_op on windows

* exclude the dynload_warpctc out on windows
test=develop

* fix the scripts error
test=develop

* disable avx on windows by default
test=develop

* re-organize the cmake file

* disable mkl on windows by default

* add warp_ctc back

* fix the dependency

* fix the dependency

* fix the build issue on windows

* remove unsupported flag on windows

* code style

* code style
test=develop

* fix issue

* add profiler, parallel_executor back

* clean up the pre-definitions on windows

* fix build issue

* test=develop

* fix input<tensor>
test=develop

* fix split_ids
test=develop

* ElementwiseMul should not support SelectedRows

* fix scale op
test=develop

* change GetTensorFromVar() method to GetTensorOrSelectedRowsFromVar()

* fix operator

* refine MultiOutput

* fix MultiOutput
test=develop

* disable test_dist_save_load
test=develop

* fix elementwise_op
test=develop

* add get_sparse_as_op
test=develop

* add info for check
test=develop

* rename get_sparse_as_op with extract_rows_as_op.
test=develop

* elementwise doesn't support selected_rows

* fix regularizer

* remove extract_rows_as
test=develop

* fix ci
test=develop

* add test for sum_op

* fix regularizer
test=develop

*  test=develop

* fix pserver weight decay multi inputs test=develop

* fix GetTensorFromVar
test=release/1.1

* refine GetTensorFromVar
test=develop

* fix sum_op's GetExpectedKernelType
test=develop

* fix ci fail
test=develop

It is used by NetOp before.

* Fix a bug related to dispensable inputs and refine the inference unittest.

* Fix the use of dispensable inputs in reshape_op.

* Polish the enforce statements.

* Fix an English writing typo.

* Fix the bug when a input variable of op is dispensable.

* Add HasInputs/Outputs interfaces to OperatorBase.

* Remove the unreferenced header file.

* delete unused IsNetOp() and Rename()

* rm OperatorBase::Rename implementation

* delete Operator::InputVars()

* remove unused OperatorBase::ShareLoD; ShareLoD has been implemented in infershape

* organize operatorbase; remove unused set_type

* add comments

* fix comment

* Move Pod Types from DataType enum to Type enum

* Fixed data_type.h

* Fix type in TensorDesc

* Add comment to framework.proto

* Fixed type in data_type.h

* Updated format of type in data_type.h

* Fix var_desc.h

* Fix op_kernel_type.h

* Fixed data_type_transform_test.cc

* Fix operator.h

* Fixed data_type_transform.cc

* Fixed op_kernel_type_test.cc

* Fix operator.cc

* Fixed data_layout_transform_test.cc

* Fix var_desc.cc

* Fixed assign_value_op.cc

* Fixed assign_value_op.h

* fixed protobuf.cc

* Fix data_layout_transform_test.cc and op_kernel_type_test.cc

* Fixed rnn_memory_helper_op.cc

* Fix progrma_desc_test.cc

* Fixed fill_constant_batch_size_like_op.cc

* Fix operator_test.cc

* Fixed fill_constant_op.cc

* Fixed gaussian_random_op.cc

* Fixed uniform_random_op.cc

* Fixed edit_distance_op.cc

* Fixed fill_constant_batch_size_like_op.cc

* Fixed rnn_memory_helper_op.cc

* Fixed chunk_eval_op.cc

* Fixed assign_value_op.cc

* Fixed assign_value_op.h

* Fixed cast_op.h

* Fixed cast_op.h

* Fix fill constant op

* Fixed clang for assign_value_op.cc

* Fix one_hot_op.h

* Fix one_hot_op.cc

* Fix fill_op.cc

* Fixed sum_op.cc

* Fixed sum_op clang

* Fix uniform_random_op.cc

* Fix gaussian_random_op.cc

* Fix backward.cc

* Fix protobuf.cc

* Fixed prune_test.cc

* Fixed op_registry_test.cc

* Fix data_device_transform_test.cu

* Fix travis error

* Fixed one_hot_op.cu

* Fixed op_registry_test.cc

* Fixed nccl_op.cc

* Fixing python tests

* Revert "Fixing python tests"

This reverts commit fccaa4c5.

* Fixing Pybind to remove data type

* Fixing tensor.py

* Updated the new files:

* Resolve error in merge conflict of fill_constant_batch_size_like_op.cc

* "unified operators"

* "add CUDNN register"

* "add use cudnn attribute"

* "add attribute"

* "test conv tranpose op"

* "remove duplicated attr"

* "fix op test"

* "add attribute to set cudnn"

* "add more log"

* "need layout op register support"

* "add more log"

* "change GetExpectedKernelType "

* "fix Get attr in conv_op"

* "fix CI"

* "fix tests"

* "removed kernel priority fallback"

* "fix CI"

* "fix stack pointer bug"

* "refine buggy interface"

* "add const cast to save life"

* "fix get_output_with_grad"

* "fix op test with dataformat"

* ""fix pooling

* "fix pooling test"

* "fix CI"

* "fix with_gpu error"

* "add transform needed functional check"

* "fix unpack list error"

* "comment out parallel.do temporary"

* "fix CI"

* "fix compile doc error"

* "make threshold larger"

* add rename guard

* add device_data_transform

* add device_data_transform_test

* modify GetExpectedKernelType

* update operator.run

* support test test_label_semantic_roles

* optimize code

* optimize code

* rename GetActualKernelType to GetExpectedKernelType

* fix chunk_eval_op and device_data_transform_test

* add is_same_place to place

* optimize code, refine rename_guard

* refine rename guard, add GetKernelTypeForVar

* optimize code

* add some log

* rename guard

* use sub scope to create var

* fix compile

* add IsInitialized for Tensor

* add VarIsTensor

* fix op_registry_test

* test

* tmp disable priority

* restore switch_kernel.md

* code clean

This can make it easier to locate error.

* "add c++ side kernel selection"

* "add multiple kernel op test"

* "kernel selection only support cudnn"

* "better formatter"

* "small fix with UseCPU"

* "depends on change interface Get(Place, Library)"

* "fix CI"

* "fix python cudnn test"

* "leave the register cudnn op to another PR"

* "fix CI"

* "use all kernel by default"

* "fix CI"

* init kernel hint

* fix typo

* rm unused code

* add include in op_kernel.h

* restore op_kernel since it will be moved to op_kernel_type

* change force_cpu to use_cpu

* fix compilation

* refine OpKernelKey

* refine codes

* fix code style

* follow comments

* "change operator interface"

* "move devicepool to device_context"

* "fix operator test"

* "fix op_registry Run interface"

* "net op passed. Need to fix nccl multi-Context"

* "add nccl group function"

* "add nccl group function"

* "fix gpu count exceed 32 error"

* "fix recurrent op, nccl op"

* "change the other operators interface with Place"

* "fix typo"

* "fix pybind"

* "fix device in python side"

* "fix pybind failed"

* "add init for test"

* "fix CI"

* Move framework.proto to proto namespace

* Fix compile

* Fix compile

* Fix Compile

There are mainly following fixes:

- take `DeviceContext` as the template parameter of math functors and OpKernel instead of `Place`
- remove `eigen_device` interface in base class  `DeviceContext`
- remove `GetEigenDevice` interface in `ExecutionContext` and base class `DeviceContext`
- remove unused `platform::EigenDeviceConverter`
- rename `REGISTER_OP_GPU_KERNEL` to `REGISTER_OP_CUDA_KERNEL`
- rename `USE_GPU_ONLY_OP` to `USE_CUDA_ONLY_OP`

* Chage `IndicateDataType` to `GetKernelType`. Make it easier to
  understand.
* Change `OpKernelKey` to `OpKernelType`
* Make operator developers can customize which kernel the operator will
  use in runtime.

* add acc layer
* memory log level change from 3 to 10
* use gaussian random to init conv parameters
* use initializer
* fix import
* batch_norm use helper to create persistable var
* refine code
* train only 2 batches for test
* use g_program and g_init_program
* use XavierInitializer to init fc parameter

* add batch_norm_layer

* add img_conv_group layer and test

* add check to Tensor.type()

* forward can run

* with backward

* change label data time from int32 to int64

* refine code

* follow comment