- 03 6月, 2021 1 次提交
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由 Qi Li 提交于
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- 31 3月, 2021 1 次提交
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由 tianshuo78520a 提交于
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- 08 2月, 2021 1 次提交
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由 Qi Li 提交于
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- 01 12月, 2020 1 次提交
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由 chentianyu03 提交于
* add complex64 and complex128 type; add +-*/@ and slice opreator for complex types * add test cases for complex elementwise, matmul and getitem unittest * add test cases for complex types * add test cases for complex matmul unittest
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- 08 5月, 2019 1 次提交
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由 zhaoyuchen2018 提交于
* Refine elementwise kernel. Add a simple cuda kernel if grad x and y both exist Use 2D block cuda kernel to do broadcast. test=develop Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com> * refine code. test=develop Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com> * refine code. test=develop Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>
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- 31 1月, 2019 1 次提交
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由 guoshengCS 提交于
test=develop
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- 24 1月, 2019 1 次提交
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由 Yiqun Liu 提交于
* Refine the beam_search op and test. * A basic CUDA implementation of beam_search for small batch_size. * Implement CUDA kernel for beam_search_op. * Use multiple CUDA threads in the same block to select the top beam. * Update the python api of beam_search op. * Enable extend function in CPU kernel of beam_search op. * Unify the CUDA codes. test=develop * Unify the CPU kernel of beam_search op. * Ensure the seletced items of beam_search_op's CPU kernel sorted by scores. * Update the description of beam_search in API.spec. * Enable the use of CUDA kernel in beam_search op. * Exclude the beam_search's CUDA unittest when there is no CUDA gpu, and delete some debuging statements. test=develop * Follow comments. test=develop * Call the CPU kernel for beam_search op when batch_size > 4. test=develop * Remove the except of is_empty op in PrepareData. test=develop
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- 17 8月, 2018 1 次提交
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由 dzhwinter 提交于
* "fix bug" * "add test case"
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- 30 7月, 2018 1 次提交
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由 dzhwinter 提交于
* cherry picked * "cherry picked platform" * "add comment" * "fix ci"
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- 08 5月, 2018 1 次提交
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由 chengduoZH 提交于
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- 04 5月, 2018 1 次提交
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由 chengduoZH 提交于
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- 03 5月, 2018 2 次提交
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由 chengduoZH 提交于
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由 chengduo 提交于
* fix __shfl_down_sync_ of cross_entropy * use reduceSum * "fix ci"
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