* update cluster train v2 doc

* WIP cluster train doc

* update

* cluster train doc

* add TOC for en doc

* fix sphix build issue

* fix error links

* fix link errors

* fix image link

* polish cluster train docs

* update general distributed training document

* fix sphinx compile error

* fix doc image error

Enable learning rate annealing of Adam Optimizer

Make LoDTensor::lod_element return start and end offset of sequence

* remove Program.instance

* fix test_program.py

* Implement FC layer with helper

* Update LayerHelper

* Add debug string for Python ProtoBuf

and Rename `Sync` to `Flush`

* Add check of ProtoBuf initialization

* Layer wrapper for FC

* Fix unittest

* Fix CI

* Add code generator

* AttributeChecker Better error log and speicalize bool

Since lots of types can be cast to bool

* Complete mlp, fit_a_line

* Implementation of simple conv_2d layer

* Fix bugs

* Change ProgramDesc not a global variable

* Polish code style

* Stash

* Correct implement BlockDesc destructor

* Correct implement BlockDesc destructor

* Unify program as parameter name

* Fix bugs

* Add unittest

* Fix unit test error

* Remove unused functions

* Add clone for Python Program

* Compare OpDescBind directly

update doc: no need to modify pybind_file

* Create prune.md

* modification based on comment

* remove insertion

* rename id to block_id

* Update prune.md

* formatting

Prune implementation

* Add glog as dependencies of ops

* Use VLOG to logging some information is helpful when we debug Paddle

* Fix Unittests

add sparse update kernel for sgd operator

* Adding Proximal Gradient Descent

* Fixing review comments

* Implement FC layer with helper

* Update LayerHelper

* Add debug string for Python ProtoBuf

and Rename `Sync` to `Flush`

* Add check of ProtoBuf initialization

* Layer wrapper for FC

* Fix unittest

* Fix CI

* Add code generator

* AttributeChecker Better error log and speicalize bool

Since lots of types can be cast to bool

* Complete mlp, fit_a_line

* Implementation of simple conv_2d layer

* Fix bugs

* Correct implement BlockDesc destructor

* Fix bugs

* Fix unit test error

* Follow comments

* Add design doc of batch_norm_op

* Move batch_norm_op.png to operator/images

* Refine batch_norm_op design doc

* Add initail design doc for regularization

* Updating image links

* Commiting the images for the equations

* Adding computation graph images

* Adding section on computation graph

* Change ProgramDesc not a global variable

* Polish code style

* Correct implement BlockDesc destructor

* Unify program as parameter name

* Implement FC layer with helper

* Update LayerHelper

* Add debug string for Python ProtoBuf

and Rename `Sync` to `Flush`

* Add check of ProtoBuf initialization

* Layer wrapper for FC

* Fix unittest

* Fix CI

* Add code generator

* AttributeChecker Better error log and speicalize bool

Since lots of types can be cast to bool

* Complete mlp, fit_a_line

* Implementation of simple conv_2d layer

* Fix bugs

* Remove debug code

Update the documentation of how to cross-compile for Android

Simplify executor

* initial matmul operator

Similar to np.matmul, but also has transpose_X and transpose_Y flags,
and only supports tensors from rank 1 to 3 inclusive.

For GPU, uses cublas?gemmStridedBatched. For CPU, uses
cblas_?gemm_batch if available via MKL; otherwise a simple serial
implementation that loops over the batch dimension is employed for now.