- 12 4月, 2023 1 次提交
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由 Yiqun Liu 提交于
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- 05 6月, 2022 1 次提交
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由 Sing_chan 提交于
* use yapf to format all python file * yapf exclude two unittests file for they rely on writing and reading file, and format will break them * disable diff_py_file because too many diff files cause command following failed
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- 28 4月, 2022 1 次提交
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由 sneaxiy 提交于
* add gradient merge for DistributedFusedLamb * use master acc gradient * fix CI ut * polish * remove math_function_impl.h change * fix test_update_loss_scaling_op.py * try to fix XPU/NPU CI * add gm ut
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- 23 4月, 2021 1 次提交
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由 Leo Chen 提交于
* refactor_check_finite_and_scale_npu_kernel * fix compile * add alloc_float_status op * add alloc_float_status op * add FloatStatus for check_finite_and_unscale * refine code * remove unneccessary logic * refine for fleet
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- 08 1月, 2021 1 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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- 14 9月, 2020 1 次提交
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由 Zhen Wang 提交于
Update amp_check_finite_and_scale_op and add an updating_loss_scaling op for static graph amp training. (#26240) * update amp_check_finite_and_scale_op for static_amp. * use amp_check_finite_and_scale in static graph amp. * update grads to zero when grads own infinite values(as for amp_checkout_finite_and_scale op). * add update_loss_scaling op in cpp. * add update_loss_scaling_op unit test. * update the doc of the check_finite_and_unscale op * Update the process of gradients updating skipping if the gradients have infinite values. * update the way to zero grads. * update test_update_loss_scaling_op.py * add log info when find infinite grads. * add the unit test for UpdateLossScaling Layer.
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