- 23 3月, 2022 1 次提交
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由 xiongkun 提交于
* transfer unsqueeze to phi * fix conflict * add squeeze * add infershape * fix xpu and npu error
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- 15 3月, 2022 1 次提交
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由 xiongkun 提交于
[phi] Transfer lgamma, kldiv_loss, isclose, cumprod kernels into phi and pass the tests of these four kernels (#39770) * tranfer and pass the lgamma unittest * merge and pass the test * transfer kldiv_loss and kldiv_loss_grad; pass the unitest * trafer the isclose and cumprod kernel * change PT_REGISTER -> PD_REGISTER * fix by code review * fix by code review * fix * remove enforce include dependence from scalar * fix * fix by code review * fix by code review
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- 25 2月, 2022 1 次提交
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由 Aganlengzi 提交于
* [phi]migrate increment addmm multinomial cholesky InferShapes to phi * set_dtype and mod MultinomialFunctor
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- 24 2月, 2022 1 次提交
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由 Aganlengzi 提交于
* migrate increment addmm multinomial cholesky kernels to phi * test pr39869 * test pr39869 * fix style and ci
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- 20 2月, 2022 1 次提交
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由 Chen Weihang 提交于
* rename pten dir to phi * rename namespace to phi * rename infrt pten dir to phi * resolve conflict * rename pten to phi in cmake * revert all infrt change * change needed files * fix infrt failed * fix inference failed
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- 21 1月, 2022 1 次提交
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由 Aurelius84 提交于
* Migrate Dim and DDim from paddle::framework into pten namespace * fix paddle::framework::Array * fix framework::Array
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- 19 10月, 2020 1 次提交
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由 pangyoki 提交于
* fix multinomial doc * fix multinomial error message * little doc change * fix Categorical class doc * optimize format of error message * fix CPU Kernel error message format * fix isinf and isnan error in WindowsOPENBLAS CI * delete inf and nan * add manual_seed in sample code * little error message change * change error message to InvalidArgument * add full point for error message and add manual_seed in CPU environment
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- 29 9月, 2020 1 次提交
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由 pangyoki 提交于
* add multinomial cpu kernel * fix C++ notype error * fix windows ci array len error * let array len be const * change array to vector * add cuda kernrl with num_distribution is 1, and not support replacement=False * add multinomial python api * support num_distribution different multinomial distributions * add multinomial python api unittest * change output dtype to int64 * fix coverage prob * optimize format * fix dtype of output error, should be int64_t
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