- 12 12月, 2022 4 次提交
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由 Maxim Kochurov 提交于
Co-authored-by:Maxim Kochurov <max.kochurov@pymc-devs.org>
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由 Adrian Seyboldt 提交于
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由 Adrian Seyboldt 提交于
Co-authored-by:Ricardo Vieira <28983449+ricardoV94@users.noreply.github.com>
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由 Adrian Seyboldt 提交于
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- 11 12月, 2022 18 次提交
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由 juanitorduz 提交于
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由 Michael Osthege 提交于
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由 Michael Osthege 提交于
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由 Michael Osthege 提交于
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由 Michael Osthege 提交于
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由 Michael Osthege 提交于
This gives easier access to mypy error messages that would otherwise be suppressed by settings from `setup.cfg`.
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由 Michael Osthege 提交于
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由 Michael Osthege 提交于
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由 Rémi Louf 提交于
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由 Rémi Louf 提交于
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由 Rémi Louf 提交于
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由 Rémi Louf 提交于
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由 Rémi Louf 提交于
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由 Rémi Louf 提交于
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由 Rémi Louf 提交于
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由 Brandon T. Willard 提交于
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由 Brandon T. Willard 提交于
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由 Brandon T. Willard 提交于
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- 10 12月, 2022 7 次提交
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由 Sudarsan Mansingh 提交于
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由 Ricardo Vieira 提交于
* Fix bug in AdvancedSubtensor infer_shape The underlying utility `indexed_result_shape` was off by 1 in terms of when do the advanced index operations have to be brought to the front of the array.
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由 Maxim Kochurov 提交于
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由 Maxim Kochurov 提交于
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由 Maxim Kochurov 提交于
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由 Maxim Kochurov 提交于
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由 Maxim Kochurov 提交于
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- 09 12月, 2022 2 次提交
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由 Thomas Wiecki 提交于
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由 Adrian Seyboldt 提交于
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- 07 12月, 2022 1 次提交
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由 Thomas Wiecki 提交于
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- 04 12月, 2022 6 次提交
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由 Ricardo Vieira 提交于
* The rewrite no longer bails out when dimshuffle affects both unique param dimensions and repeated param dimensions from the size argument. This requires: 1) Adding broadcastable dimensions to the parameters, which should be "cost-free" and would need to be done in the `perform` method anyway. 2) Extend size to incorporate implicit batch dimensions coming from the parameters. This requires computing the shape resulting from broadcasting the parameters. It's unclear whether this is less performant, because the `perform` method can now simply broadcast each parameter to the size, instead of having to broadcast the parameters together. * The rewrite now works with Multivariate RVs * The rewrite bails out when dimensions are dropped by the Dimshuffle. This case was not correctly handled by the previous rewrite
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
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由 Ricardo Vieira 提交于
This allows PyTensor to infer more broadcastable patterns, by placing the casting inside the MakeVector Op
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由 Ricardo Vieira 提交于
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- 03 12月, 2022 2 次提交
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由 Adrian Seyboldt 提交于
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由 Adrian Seyboldt 提交于
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