- 14 11月, 2017 6 次提交
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由 peterzhang2029 提交于
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由 peterzhang2029 提交于
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由 peterzhang2029 提交于
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由 QI JUN 提交于
* add split lod tensor operator * add more test cast * clean code * add merge lod tensor operator * fix bug * clean code * add grad operator * make mask support GPU * add comments
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由 Yu Yang 提交于
* Assign Operator. Out=X, when type in [LoDTensor/SelectedRows/LoDTensorArray] * Follow comments
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由 Helin Wang 提交于
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- 13 11月, 2017 3 次提交
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由 Yu Yang 提交于
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由 QI JUN 提交于
* add lstm layer * set hidden shape * rename input parameter * add dynamic lstm * refine dynamic lstm layer * change parameter using XavierInitializer by default * refine dynamic lstm layer
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由 QI JUN 提交于
* create learning rate variable for every parameter * fix ci * set parameter lr relatively to global lr
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- 11 11月, 2017 1 次提交
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由 dzhwinter 提交于
* "fix ci failed" * "comment out seq_concate op to unblock PRs"
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- 10 11月, 2017 7 次提交
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由 guosheng 提交于
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由 guosheng 提交于
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由 Yancey 提交于
* fix seq_concat with refactaring LoD * fix failed unit test * rename function name
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由 yangyaming 提交于
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由 Yang Yang(Tony) 提交于
* first commit * Python API for while op * Python Unittest for simple while_op forward * fix out to be list * Fix UT * VarType * Fix several bugs * Fix bug * Fix bug * Fix Bug * Fix bug * Fix unittest * Remove debug log * Add comments * add PADDLE_ENFORCE * while_grad_op first commit * Add `BlockDescBind::FindRecursiveOrCreateVar()` and fix bugs * refine code * fix unittest bug
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由 kavyasrinet 提交于
* Adding operator assignment * Adding documentation to layers.py * Removing file from another PR
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由 Siddharth Goyal 提交于
* Fix attribute naming for momentum_op * Fix minor typo in comment * Fix attribute name * Fix names in test_optimizer * Fix python wrapper
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- 09 11月, 2017 10 次提交
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由 dangqingqing 提交于
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由 peterzhang2029 提交于
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由 yangyaming 提交于
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由 ranqiu 提交于
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由 Yang Yu 提交于
* increament is default inplace
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由 Helin Wang 提交于
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由 fengjiayi 提交于
* 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 * Add grad for ops * Debug * Fix a bug * fix a bug * fix a bug
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由 Yang Yu 提交于
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由 Yang Yu 提交于
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由 guosheng 提交于
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- 08 11月, 2017 13 次提交
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由 yangyaming 提交于
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由 caoying03 提交于
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由 ranqiu 提交于
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由 yangyaming 提交于
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由 Luo Tao 提交于
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由 Yang Yang(Tony) 提交于
* add fill_constant_batch_size_like_op to rnn h_boot * first commit * merge develop; fix conflict * update to main_program
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由 typhoonzero 提交于
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由 Yang Yu 提交于
Follow comments
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由 Yang Yu 提交于
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由 Wang,Jeff 提交于
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由 chengduoZH 提交于
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由 Yu Yang 提交于
* 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
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由 Yang Yu 提交于
Used for shrink memories state in DyRNN. The height of state could be shrinked after running a step block.
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