- 11 1月, 2021 5 次提交
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由 石晓伟 提交于
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由 chentianyu03 提交于
* type promotion for grad * add type promotion for div op
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由 liym27 提交于
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由 WeiXin 提交于
* modify error message based on comments * edit code according to review. * Correct spelling according to review.
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由 wawltor 提交于
add the op error message for the matmul xpu
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- 10 1月, 2021 2 次提交
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由 GaoWei8 提交于
* optimize softmax forward
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由 wangchaochaohu 提交于
reduce the occupied size of memory for the fused pattern of elementwise_add Op and activation Op(relu Op for example) (#29885)
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- 09 1月, 2021 3 次提交
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由 zhang wenhui 提交于
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由 pangyoki 提交于
* add view strategy on squeeze,unsqueeze,reshape,flatten * add squeeze unittest * add unittests * use View strategy as name rather than Reuse Allacation * fix view api doc * fix format * use core.ops when input of reshape2 is Tensor * fix test_cross_entropy_loss error because of reshape2 * delete selected_rows * change op_function * little change * solve HandleViewBetweenInputAndOutput
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由 Jacek Czaja 提交于
* - Added UT for testing elementwise_mul caching * lint fixes
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- 08 1月, 2021 10 次提交
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由 Zhen Wang 提交于
* add cast ops before and after unsupported fp16 ops. * Keep partial net in FP32 pattern. * Support check_finite_and_unscale and update_loss_scaling for FP16 calculation mode. * Add fp16 support for adam op. * add multi precision attr for adam. * Fix the bug of test_multi_precision_fp16_train UT. * Code format for CI. * Fix the redefine error about MPTypeTrait on windows. * fix bugs of the _create_accumulators func in Momentum. * fix bug when inserting post cast op. * Add the update_loss_scaling op in allow_set of UnusedVarCheck. * Update for ci coverage. * Add some doc for OptimizerWithMixedPrecision. * Fix the code style. * Imporve the doc of `amp_init`. * Change for fp16 testing if users have the infer program defined in separate way.
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由 Leo Chen 提交于
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由 Leo Chen 提交于
* fix dtype of ungenerated grad var * update ut * refine code * set default dtype * fix could_use_cudnn bug * remove debug code * re-implement * fix bug
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由 Wilber 提交于
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由 Wilber 提交于
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由 ruri 提交于
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由 Leo Chen 提交于
* change to tensor copy sync * change to tensor copy sync * make copy_to safe when use TensorCopy * refine code * add ut * add cudapinned garbagecollector * add testcase: cpu place -> cuda pinned place
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由 Chengmo 提交于
* add tensor table
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由 Wilber 提交于
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由 joanna.wozna.intel 提交于
* Add a necessary condition * Remove test for white list and add header
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- 07 1月, 2021 11 次提交
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由 lijianshe02 提交于
* enhance error message of nll_loss op test=develop
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由 Huihuang Zheng 提交于
Improve some error messages in parallel_executor.cc, conditional_block_op.cc, recurrent_op.cc
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由 Chen Weihang 提交于
* simplify prepared op impl to improve performance * fix kunlun compile error * continue fix kunlun compile error * only transform diff place when dtype diff * fix failed unittests * remove useless file * polish impl by review comment
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由 123malin 提交于
* test=develop, add index_select_cuda kernel
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由 wangchaochaohu 提交于
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由 WeiXin 提交于
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由 Wilber 提交于
* enhance error info for py_func * update
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由 weihaoji 提交于
[XPU] Remove lite_xpu ut lite_resnet50_test since fusion pass changes introduced precision diff. test=develop (#30122)
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由 liuyuhui 提交于
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由 Jack Zhou 提交于
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由 123malin 提交于
* test=develop, add model_average and lookahead
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- 06 1月, 2021 9 次提交
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由 Leo Chen 提交于
* add dispenable input 'shape' for core.ops.reshape2 * add dispenable inputs for core.ops.reshape2/expand/slice * add ut
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由 ShenLiang 提交于
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由 Zhou Wei 提交于
* Polish and Optimize the print/repr message of all layer * fix some code format
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由 wangguanzhong 提交于
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由 QingshuChen 提交于
* add aarch64 and sunway kunlun lib * minor * optimize elementwise_add for kunlun * update kunlun dependence * minor * minor
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由 Shang Zhizhou 提交于
* snap * add inference api: DisableTensorRtOPs * fix code style * update api to experimental * update variable name
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由 石晓伟 提交于
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由 xiemoyuan 提交于
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由 liym27 提交于
1. when slice_item is a slice: 1) the start of __getitem__ should be std::max(start, 0) if slice 2) the start of __getitem__ should be std::min(end, dim) 2. when slice_item is an integer, it should be in [-dim_len, dim_len) 3. Fix error message to use accurate data
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