* add logs and fix a bug
* fix break buf
* modify path bugs
* fix by comments
* fix by comments
* add batch
* add float32tostring
* add pb support
* moidfy gotpaht
* compile ok
* add proto
* delete not need
* add proto
* add empty proto
* clean not need
* clean not need
* modify deps
* fix by comments and update depend
* fix compile error
* fix loop bugs
* 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
* 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
* support sparse output for lookup table grad op
* refine codes
* fix gpu build error
* fix lookup table grad gpu kernel
* fix ci
* fix ci
* fix ci
* fix bug in lookup_table_grad op
* fix bug in test_word2vec
* register double kernel for some operators
* set is_sparse=True in test_word2vec
* fix lookup table grad op CUDA kernel bug
* disable test_modified_huber_loss_op temporarily
* disable test_lstm_unit_op temporarily
* 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
* 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
* 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
* "add model format design doc"
* "add restore function"
* "add parse protobuf"
* "move necessary information to saver.proto"
* "format code"
* "add gpu option"
* "add lod info"
* "add saveop python test wrapper"
* "checkpoint reuse save operator"
* "rewrite model format design doc"
* "async support needed"
* "fix run once"
* "fix doc based on comments"
* "refine based on comments"
* "fix based comments"
* "remove persistable flag from framework.proto"
* "add IndicateDataType to restore op"
* "add save test"
* "modify save restore code"
* "modified the restore logic"
* rm checkpoint_op.cc
* rm test_checkpoint_op.py
* "get inputs outputs name from execution context"
* Saving each variable to a independent file
* Fix bugs
* Rewrite save_restore_op_test with new Python framework
* Move `SaveOp` and `RestoreOp` from OpWithKernel to OpBase
* Refine unit test of SaveOp and RestoreOp
* fix compile errorwq
* add test_fit_a_line
* Update
* fix persistable bug
* fix elementwise add bug
* set correct attr for bias op in fc layer
* set correct attr for bias op in fc layer
* Update
1. Add init_program to hold initializers
2. bug fix
* add test_fit_a_line
* fix persistable bug
* fix elementwise add bug
* fix type
* add gitignore
* Complete fit_a_line test
* revert code
* Clean up
* Revert "revert code"
This reverts commit eb1aa015cda4fc12b6dc778ada6c3507b98134f5.
* Refine
* Fix unit test
* 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
* Expose get global scope
* Make global scope not thread-safe
1. It is no need to make global scope thread-safe, since it will be
invoked in Python main thread.
2. Do not free the global scope when C++ exit. Let the OS free memories,
otherwise, we need to handle the destroy dependencies.
See
https://google.github.io/styleguide/cppguide.html#Static_and_Global_Variables
* Fix
* Implementation of simple conv_2d layer
* Stash
* Remove private data members in OpRegister
* Fix bugs
* Stash
* Expose FeedFetchList as VarType
* 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
* Working on executor
* Stash
* Add glog as dependencies of ops
* Use VLOG to logging some information is helpful when we debug Paddle
* Expose VarDesc::persistable to Python
* Test executor
* Complete unittest
* Polish code
* Fix merge error
* Follow comment
* Polish Python Code
* 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
* 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
* 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
* 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.
* init parameter base class
* optimize the Comments of optimizer
* basic implimentation of optimizer
* add test_optimizer
* add no_grad_set to interface
* update optimizer.py
* python code can run
* fix some problem
* add sync_with_cpp to Python Program and Block
* sync vars and ops in block from cpp
* optimize code and add some comment
* add more check for sync
* update optimizer with return value of Backward
* rm unused code
* infer shape when create gradient vairiable
* update test_optimizer
* update test_program.py
* update backward test
* follow comment
* 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
* add target to Backward, generate var in block when call backward
* modify backward_test
* fix executor_test
* set var desc default type to LOD_TENSOR
* update backward_test
* insert loss in the top level of backward
* create grad vars for all blocks in current program
* optimize code
* update test_program.py
* only create var for newly create blocks when backward
zchen0211
Abhinav Arora
dzhwinter
fengjiayi
guosheng
caoying03
dangqingqing
zhouxiao-coder
武毅
QI JUN
Qiao Longfei
gongweibao
chengduoZH
chengduo
whs
Yu Yang
dong zhihong
Tao Luo
Yang yaming
Siddharth Goyal
Yang Yang(Tony)
Peng Li
Peng LI
peterzhang2029
Guo Sheng
kexinzhao
Kexin Zhao
Yan Chunwei
kavyasrinet
Markus Kliegl