【Hackathon 5th No.19】Update rfcs of ContinuousBernoulli and MultivariateNormal API #783
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cxxly
reviewed
Dec 14, 2023
| @@ -653,9 +653,10 @@ class ContinuousBernoulli(distribution.AutoCompositeTensorDistribution): | |||
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| ## 命名与参数设计 | |||
| ```python | |||
| paddle.distribution.continuous_bernoulli(probs) | |||
| paddle.distribution.continuous_bernoulli(probability, eps=0.02) | |||
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和PyTorch签名保持一致(logits不用支持), .ContinuousBernoulli(probs=None, lims=(0.499, 0.501),)
cxxly
reviewed
Dec 14, 2023
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| # 五、设计思路与实现方案 | ||
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| ## 命名与参数设计 | ||
| ```python | ||
| paddle.distribution.multivariate_normal(loc, sacle) | ||
| paddle.distribution.multivariate_normal(loc, covariance_matrix=None, precision_matrix=None, scale_tril=None) |
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和PyTorch签名保持一致，class用Pascal写法，MultivariateNormal(loc, covariance_matrix=None, precision_matrix=None, scale_tril=None)
…20230927_api_design_for_ContinuousBernoulli.md
…0230927_api_design_for_MultivariateNormal.md
cxxly
reviewed
Dec 15, 2023
| @@ -653,9 +653,10 @@ class ContinuousBernoulli(distribution.AutoCompositeTensorDistribution): | |||
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| ## 命名与参数设计 | |||
| ```python | |||
| paddle.distribution.continuous_bernoulli(probs) | |||
| paddle.distribution.ContinuousBernoulli(probs=None, lims=(0.499, 0.501)) | |||
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Update rfcs of ContinuousBernoulli and MultivariateNormal API