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【Hackathon 7th No.31】NO.31 为 paddle.sparse.sparse_csr_tensor进行功能增强 -part #6876
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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-6876.paddle-docs-preview.paddlepaddle.org.cn/documentation/docs/zh/api/index_cn.html |
| crow_indices | crows | 每行第一个非零元素在 values 的起始位置,仅参数名不一致。 | | ||
| col_indices | cols | 一维数组,存储每个非零元素的列信息,仅参数名不一致。 | | ||
| values | values | 一维数组,存储非零元素。 | | ||
| size | shape | 稀疏 Tensor 的形状,仅参数名不一致。 | |
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验证一下,这个自动推导的结果与Pytorch是完全一致的
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验证过了的
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然后paddle和pytorch不同的是,paddle是只能一维向量,pytorch是多维向量
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所以paddle在切割一维向量后,需要判断每个子向量包含的数字个数是不是相同的
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然后paddle和pytorch不同的是,paddle是只能一维向量,pytorch是多维向量
什么是一维向量,没看明白差异。
要从torch角度往paddle看,torch的所有用法情况都可以被paddle覆盖,则视为一致,即使paddle有更多功能也不用管
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是指输入的参数维度
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稍等,我给个例子
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OK,看起来是paddle与torch的csr tensor,在3D情形下的设计是不一致的,paddle为展平式的设计
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LGTM
hi, @monster1015
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hi, @monster1015
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