为 amp.decorate 新增 master_grad、excluded_layers参数 #5792
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感谢你贡献飞桨文档，文档预览构建中，Docs-New 跑完后即可预览，预览链接：http://preview-pr-5792.paddle-docs-preview.paddlepaddle.org.cn/documentation/docs/zh/api/index_cn.html |
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docs/api/paddle/amp/decorate_cn.rst
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| @@ -20,6 +20,7 @@ decorate | |||
| - **dtype** (str，可选) - 混合精度训练数据类型使用 float16 还是 bfloat16，默认为 float16 类型。 | |||
| - **master_weight** (bool|None，可选) - 是否使用 master weight 策略。支持 master weight 策略的优化器包括 ``adam``、``adamW``、``momentum``，默认值为 None，在 ``O2`` 模式下使用 master weight 策略。 | |||
| - **save_dtype** (str|None，可选) - 网络存储类型，可为 float16、bfloat16、float32、float64。通过 ``save_dtype`` 可指定通过 ``paddle.save`` 和 ``paddle.jit.save`` 存储的网络参数数据类型。默认为 None，采用现有网络参数类型进行存储。 | |||
| - **master_grad** (bool, 可选) - 在 ``O2`` 模式下是否使用 float32 类型的权重梯度进行梯度裁剪、权重衰减、权重更新等计算。如果被启用，在反向传播结束后权重的梯度将会是 float32 类型。默认值：False。 | |||
zhangting2020
changed the title
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April 18, 2023 10:55
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为 amp.decorate 新增 master_grad参数
