* Adding the increment op for global step

* Changing list to single op as per code review feedback

* Add `dump_to_file()` for ProgrameDescBind in pybind

* Update

* Add utility.py

* typo

* Fix bugs

* Move add_feed/fetch_components to untility.py

* Compelete dump

* Follow comments

* Change output of Prune() from inference to pointer

* Expose Prune() to Python

* Compelete save/load API of inference model

* Fix errors

* Debuging

* Compelete unit tests

* follow comments

* fix compile error

* remove unittest

* disable huber loss unittest

add logs and fix a python path bug

* Adding L1 norm op for L1 regularization

* Addressing code review feedback

* Address code review feedback

* Change variable names to match google style guide

* add sparse support for sum op

* typo fix

* fix gpu build error

* fix unittest error

* typo fix

* infer var type and shape in op_test

* follow comments

* fix build error

* bypass some unittests depend on NetOp

* Python API for save/load variables

* Polish names

* Add regularizer code
* Fix code

* Simplize Gradient Check

* Stash

* Extract apply_backward_pass to backward.py

Rename apply_backward_pass to append_backward_ops

* Use graph API to check gradient

* Fix ci

* Fix CI

* Fix backward for double precision

* Stash

* Fix CI

* Fix ci

* Ignore GRU test

* Ignore xe op

* Fix CI

* Fix softmax with xe gradient

The correct equation should be IG = OG * (d_softmax_with_xe())

* Fix typo

* Fix merge error

* Disable LRN

* compelete restoring program_bind from program_desc

* Fix bugs

* fix compile errors

* fix errors and add unit tests

* rename some vars

* Follow comments

Add local response normalize

* Cross Entropy Wrong

* Fix XE

* Polish gradient check for xe

* Fix compile

* Init

* Stash

* Polish SaveLoadOp

* Fix CI

* Polish code

* Save GPU Tensor

* Stash

* Fix CI

* Adding the L2 loss operator for L2 regularization
* Renaming l2_loss op to squared_l2_norm_op
* Addressing code review feedback

* Adding nesterov momentum to python momentum wrapper
* Fixing optimizer test after merge

* init batch norm op

* prepare input output

* compute mean_out var_out save_mean save_var on CPU

* active is test

* use eigen to do computation

* complete batch norm forward

* set default momentum to 0.9

* add batch norm grad op in CPU

* add tensor_format and NHWC support, add python test

* add test training

* add batch norm gradient test

* improve comment, fix foward Python UnitTest

* add gradient test

* fix eigen warning

* follow name style

* fix a bug

* change float to T

* add simple forward test

* test with different place

* add backward test

* refine python test

* remove old python test code

* code clean

* follow code style

* update comment

* Extract apply_backward_pass to backward.py

Rename apply_backward_pass to append_backward_ops

* Fix CI

* Update design doc