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映射文档No.79 #5853
映射文档No.79 #5853
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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-5853.paddle-docs-preview.paddlepaddle.org.cn/documentation/docs/zh/api/index_cn.html |
@Tomoko-hjf 请检查一下还有没有什么问题 |
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需要保持和已合并PR格式上的统一,可以参考格式文档https://github.com/PaddlePaddle/docs/blob/develop/docs/guides/model_convert/convert_from_pytorch/api_difference/pytorch_api_mapping_format_cn.md 和已经合并的PR
辛苦修改一下格式~
@Tomoko-hjf 已修改,麻烦在检查一下 |
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有几个共性问题:
- api签名和转写示例部分 代码前面的空格可以删去
- 参数映射部分前面 需要一句话说明,可以参考格式文档。如果是参数不一致的情况,需要说明哪个参数用法不一致,并用
- 文档里有很多无用的注释,可以检查后删去
- 参数映射部分的备注部分可以精简一下,不必把官网内容全都拿过来
辛苦修改一下~
### [torch.Tensor.permute](https://pytorch.org/docs/1.13/generated/torch.Tensor.permute.html) | ||
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```python | ||
torch.Tensor.permute(*dims) |
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可以删去前面多余的空格
### 转写示例 | ||
#### *dim: Tensor 的维度序列,可变参数用法 | ||
```python | ||
# pytorch |
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转写示例也可以删去前面多余的空格
``` | ||
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### 参数映射 | ||
两者部分参数用法不同,具体如下: |
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改为 Pytorch 的 dims
参数与 Paddle 的 perm
参数用法不同,具体如下:
位置放在 ### 参数映射 的上一行
两者部分参数用法不同,具体如下: | ||
| PyTorch | PaddlePaddle | 备注 | | ||
| ------------- | ------------ | ------------------------------------------------------ | | ||
| *dims | perm | dim :torch 可以为 *dim 和 list/tuple 的用法; perm :paddle 仅为 list/tuple 的用法。 torch 的参数为 *dim 时需要转写 | |
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备注 改为 torch 支持可变参数或list/tuple,paddle仅支持list/tuple,参数用法不一致,需要进行转写。
``` | ||
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### 参数映射 | ||
两者部分参数用法不同,具体如下: |
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改为 Pytorch 的 sizes
参数与 Paddle 的 repeat_times
参数用法不同,具体如下:
位置放在 ### 参数映射 的上一行
### 转写示例 | ||
#### *sizes: 各个维度重复的次数,可变参数用法 | ||
```python | ||
# pytorch |
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前面的空格可以去掉~
### [torch.Tensor.reshape](https://pytorch.org/docs/1.13/generated/torch.Tensor.reshape.html) | ||
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```python | ||
torch.Tensor.reshape(*shape) |
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可以去掉空格,顺便检查一下其他文件~
| some | full_matrices | 表示是否计算完整的 U 和 V 矩阵。默认时效果一致。 some 为 True 时, full_matrices 需设置为 False ,反之同理。 | | ||
| compute_uv | - | 如果 compute_uv 为 False ,则返回的 U 和 V 将分别为形状为 (m, m) 和 (n ,n) 的零填充矩阵,并且与输入设备相同。当 compute_uv 为 False 时,参数 some 不起作用。一般直接删除即可,无需转写。 | | ||
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<!-- ### torch 多的参数 |
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这部分多余的内容可以删去
| ------------- | -------------------------------------------------------------------- | | ||
| compute_uv | 默认参数,默认一致。如果 compute_uv 为 False ,则返回的 U 和 V 将分别为形状为 (m, m) 和 (n ,n) 的零填充矩阵,并且与输入设备相同。当 compute_uv 为 False 时,参数 some 不起作用。 | --> | ||
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<!-- ### 转写示例 |
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转写示例前后的 <!---->
注释符号删去
``` | ||
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<!-- ### 一致的参数 | ||
| PyTorch | PaddlePaddle | 备注 | |
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一致的参数也需要写到参数映射中去,不能注释起来
@Tomoko-hjf 已修改,麻烦再检查一下还有什么问题。 |
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- 有几个api名称和链接不一致,辛苦检查修改一下 ~
- 一句话描述部分的参数用一对 ` ` 强调即可,不需要两对
torch.cuda.get_device_name(device=None) | ||
``` | ||
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### [paddle.Tensor.transpose](https://www.paddlepaddle.org.cn/documentation/docs/zh/api/paddle/device/cuda/get_device_properties_cn.html#get-device-properties) |
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api名称不正确
paddle.CUDAPlace(id) | ||
``` | ||
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Pytorch 的 ``device`` 与 Paddle 的 ``id`` 用法不同,具体如下: |
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用一对 ` ` 包含即可,目前是用了两对
### 参数映射 | ||
| PyTorch | PaddlePaddle | 备注 | | ||
| ------------- | ------------ | ------------------------------------------------------ | | ||
| device | device | torch 的 device 参数类型为 torch.device 或 int 或 str。paddle 的 id 为 paddle.CUDAPlace 或 int 或 str。 | |
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应该是 paddle 的 device 吧
torch.cuda.device(device) | ||
``` | ||
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### [paddle.Tensor.transpose](https://www.paddlepaddle.org.cn/documentation/docs/zh/api/paddle/CUDAPlace_cn.html#cudaplace) |
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api 名称不正确
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## [参数不一致]torch.Tensor.transpose | |||
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### [torch.Tensor.transpose](https://pytorch.org/docs/1.13/generated/torch.Tensor.swapdims.html) |
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链接不正确
paddle.linalg.svd(x, full_matrics=False, name=None) | ||
``` | ||
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两者部分参数用法不同,具体如下: |
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说明一下哪个参数用法不一致吧~
### 参数映射 | ||
| PyTorch | PaddlePaddle | 备注 | | ||
| ------------- | ------------ | ------------------------------------------------------ | | ||
| some | full_matrices | 表示是否计算完整的 U 和 V 矩阵。默认时效果一致。 some 为 True 时, full_matrices 需设置为 False ,反之同理。 | |
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这个参数可以写一个转写示例,some 为 True , full_matrices 设置为 False 。
| PyTorch | PaddlePaddle | 备注 | | ||
| ------------- | ------------ | ------------------------------------------------------ | | ||
| some | full_matrices | 表示是否计算完整的 U 和 V 矩阵。默认时效果一致。 some 为 True 时, full_matrices 需设置为 False ,反之同理。 | | ||
| compute_uv | - | 默认时效果一致。一般直接删除即可,无需转写。 | |
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如果compute_uv 为 False可以进行转写吗,不可以的话备注写 暂不支持转写就可以
paddle.Tensor.reshape(shape, name=None) | ||
``` | ||
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Pytorch 的 ``*shape`` 参数与 Paddle 的 ``shape`` 参数用法不同,具体如下: |
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用一对 ` ` 包含既可~
paddle.Tensor.tile(repeat_times, name=None) | ||
``` | ||
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Pytorch 的 sizes 参数与 Paddle 的 repeat_times 参数用法不同,具体如下: |
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sizes 和 repeat_times 用 `` 强调一下吧~
@Tomoko-hjf 已修改,麻烦再次检查 |
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转写示例部分pytorch和paddle最终的输出变量名统一成y,或者一致的名称吧,现在是不一致的,辛苦修改一下~
### 参数映射 | ||
| PyTorch | PaddlePaddle | 备注 | | ||
| ------------- | ------------ | ------------------------------------------------------ | | ||
| device | id | torch 的 device 参数类型为 torch.device 或 int 。paddle 的 id 为 int。 torch 参数为 int 时无需转写, 参数为 torch.device 时, paddle 暂无转写方式。| |
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当参数为torch.device 时也可以进行转写,转写方法为
# PyTorch 写法
torch.cuda.device(torch.device('cuda:0'))
# Paddle 写法
paddle.CUDAPlace(0)
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# paddle | ||
x = paddle.randn([2, 3, 5]) | ||
x_transposed = x.transpose(perm=[1, 0, 2]) |
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pytorch和paddle转写示例的两个输出变量都统一成y吧,或者名称要一致,现在一个是x_swapdims,一个是x_transposed
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# paddle | ||
x = paddle.randn([2, 3, 5]) | ||
x_transposed = x.transpose(perm=[1, 0, 2]) |
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两个输出变量名要一致
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# paddle | ||
x = paddle.randn([2, 3, 5]) | ||
x_tile_tuple = x.tile((6,5)) |
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输出变量名统一成一致的吧~
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# paddle | ||
x = paddle.randn([2, 3, 5]) | ||
x_tile_tuple = x.tile((4,2,1)) |
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输出变量名统一成一致的吧
paddle.Tensor.transpose(perm, name=None) | ||
``` | ||
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torch 的 `*dims` 与 paddle 的 `perm` 两者部分参数用法不同,具体如下: |
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写完整吧,改为 PyTorch 的 dim
与 paddle 的 perm
两者部分参数用法不同,具体如下:
@Tomoko-hjf 已修改,麻烦再检查一下 |
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LGTM
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# paddle | ||
x = paddle.randn([2, 3, 5]) | ||
y = x.tile((6,5)) |
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这个写错了
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这个应该是x.reshape
### 参数映射 | ||
| PyTorch | PaddlePaddle | 备注 | | ||
| ------------- | ------------ | ------------------------------------------------------ | | ||
| *shape | shape | torch 的 *shape 既可以接收 list 也可接收可变参数。需要转写。| |
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paddle的支持哪些也写下
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torch 的 *shape 既可以是可变参数,也可以是 list/tuple
@zhangtailai 同学你好,有时间的话可以按照意见再修改一下,这样就能尽快合并了~ |
完成 #5691 中No.79的文档映射工作,其中新增10个api映射文档,有问题请联系