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Commit Graph

Author	SHA1	Message	Date
Yu Yang	f72729d407	Feature/rnn to array to lod tensor (#5411 ) * Add LoDRankTable LoD Rank Table stores the `level` of `lod` which is ordered by sequence length in descending order. It is useful when implement dynamic RNN and is shared by dynamic RNN memory, dynamic RNN slice input and dynamic RNN slice output operators. * Add skeleton for array_to_lod_tensor and lod_tensor_to_array * Add VarType::LoDTensorArray * Add PyBind of LoDTensorArray * Add InferVarType * Add first unittest * Add ut * Add unittest * Add unittest * Add unittests * update * init * add infershape for lod_tensor_to_array_op * compelete array_to_lod_tensor_op * copy data * clean code * clean code * Fix unittest data * fix bugs * fix compile error * Refine TensorToArrayOp * refactor array_to_lod_tensor * Unittest * fix bugs * Fix unittest * Fix unittest * debug * Debug * Fix unittest * clean code * refactor * use ostream * update test * fix gpu build error * make gpu test pass	8 years ago
Yu Yang	ea2fc4cc51	Use stable_sort in lod_rank_table (#5378 ) It is easy to debug and test when use `stable_sort`and the time complexity is not changed.	8 years ago
Yu Yang	74849158e3	Add LoDRankTable (#5349 ) * Add LoDRankTable LoD Rank Table stores the `level` of `lod` which is ordered by sequence length in descending order. It is useful when implement dynamic RNN and is shared by dynamic RNN memory, dynamic RNN slice input and dynamic RNN slice output operators. * Add InferVarType	8 years ago

Author

SHA1

Message

Date

Yu Yang

f72729d407

Feature/rnn to array to lod tensor (#5411 )

* Add LoDRankTable

LoD Rank Table stores the `level` of `lod` which is ordered by sequence
length in descending order. It is useful when implement dynamic RNN and
is shared by dynamic RNN memory, dynamic RNN slice input and dynamic
RNN slice output operators.

* Add skeleton for array_to_lod_tensor and lod_tensor_to_array

* Add VarType::LoDTensorArray

* Add PyBind of LoDTensorArray

* Add InferVarType

* Add first unittest

* Add ut

* Add unittest

* Add unittest

* Add unittests

* update

* init

* add infershape for lod_tensor_to_array_op

* compelete array_to_lod_tensor_op

* copy data

* clean code

* clean code

* Fix unittest data

* fix bugs

* fix compile error

* Refine TensorToArrayOp

* refactor array_to_lod_tensor

* Unittest

* fix bugs

* Fix unittest

* Fix unittest

* debug

* Debug

* Fix unittest

* clean code

* refactor

* use ostream

* update test

* fix gpu build error

* make gpu test pass

Yu Yang

ea2fc4cc51

Use stable_sort in lod_rank_table (#5378 )

It is easy to debug and test when use `stable_sort`and the time
complexity is not changed.

Yu Yang

74849158e3

Add LoDRankTable (#5349 )

* Add LoDRankTable

LoD Rank Table stores the `level` of `lod` which is ordered by sequence
length in descending order. It is useful when implement dynamic RNN and
is shared by dynamic RNN memory, dynamic RNN slice input and dynamic
RNN slice output operators.

* Add InferVarType

3 Commits (1c31bb94596266136ea9a77c32b6380cbe990a2b)