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> 翻译任务 | ||
* 目前该页面无人翻译,期待你的加入 | ||
* 翻译奖励: https://github.com/orgs/apachecn/discussions/243 | ||
* 任务认领: https://github.com/apachecn/pytorch-doc-zh/discussions/583 | ||
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请参考这个模版来写内容: | ||
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# PyTorch 某某页面 | ||
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> 译者:[片刻小哥哥](https://github.com/jiangzhonglian) | ||
> | ||
> 项目地址:<https://pytorch.apachecn.org/2.0/tutorials/advanced/pendulum> | ||
> | ||
> 原始地址:<https://pytorch.org/tutorials//advanced/pendulum.html> | ||
开始写原始页面的翻译内容 | ||
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注意事项: | ||
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1. 代码参考: | ||
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```py | ||
import torch | ||
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x = torch.ones(5) # input tensor | ||
y = torch.zeros(3) # expected output | ||
w = torch.randn(5, 3, requires_grad=True) | ||
b = torch.randn(3, requires_grad=True) | ||
z = torch.matmul(x, w)+b | ||
loss = torch.nn.functional.binary_cross_entropy_with_logits(z, y) | ||
``` | ||
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||
2. 公式参考: | ||
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||
1) 无需换行的写法: | ||
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$\sqrt{w^T*w}$ | ||
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||
2) 需要换行的写法: | ||
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||
$$ | ||
\sqrt{w^T*w} | ||
$$ | ||
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||
3. 图片参考(用图片的实际地址就行): | ||
|
||
<img src='http://data.apachecn.org/img/logo/logo_green.png' width=20% /> | ||
|
||
4. **翻译完后请删除上面所有模版内容就行** |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,53 @@ | ||
> 翻译任务 | ||
* 目前该页面无人翻译,期待你的加入 | ||
* 翻译奖励: https://github.com/orgs/apachecn/discussions/243 | ||
* 任务认领: https://github.com/apachecn/pytorch-doc-zh/discussions/583 | ||
|
||
请参考这个模版来写内容: | ||
|
||
|
||
# PyTorch 某某页面 | ||
|
||
> 译者:[片刻小哥哥](https://github.com/jiangzhonglian) | ||
> | ||
> 项目地址:<https://pytorch.apachecn.org/2.0/tutorials/beginner/hta_intro_tutorial> | ||
> | ||
> 原始地址:<https://pytorch.org/tutorials//beginner/hta_intro_tutorial.html> | ||
开始写原始页面的翻译内容 | ||
|
||
|
||
|
||
注意事项: | ||
|
||
1. 代码参考: | ||
|
||
```py | ||
import torch | ||
|
||
x = torch.ones(5) # input tensor | ||
y = torch.zeros(3) # expected output | ||
w = torch.randn(5, 3, requires_grad=True) | ||
b = torch.randn(3, requires_grad=True) | ||
z = torch.matmul(x, w)+b | ||
loss = torch.nn.functional.binary_cross_entropy_with_logits(z, y) | ||
``` | ||
|
||
2. 公式参考: | ||
|
||
1) 无需换行的写法: | ||
|
||
$\sqrt{w^T*w}$ | ||
|
||
2) 需要换行的写法: | ||
|
||
$$ | ||
\sqrt{w^T*w} | ||
$$ | ||
|
||
3. 图片参考(用图片的实际地址就行): | ||
|
||
<img src='http://data.apachecn.org/img/logo/logo_green.png' width=20% /> | ||
|
||
4. **翻译完后请删除上面所有模版内容就行** |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,53 @@ | ||
> 翻译任务 | ||
* 目前该页面无人翻译,期待你的加入 | ||
* 翻译奖励: https://github.com/orgs/apachecn/discussions/243 | ||
* 任务认领: https://github.com/apachecn/pytorch-doc-zh/discussions/583 | ||
|
||
请参考这个模版来写内容: | ||
|
||
|
||
# PyTorch 某某页面 | ||
|
||
> 译者:[片刻小哥哥](https://github.com/jiangzhonglian) | ||
> | ||
> 项目地址:<https://pytorch.apachecn.org/2.0/tutorials/beginner/hta_trace_diff_tutorial> | ||
> | ||
> 原始地址:<https://pytorch.org/tutorials//beginner/hta_trace_diff_tutorial.html> | ||
开始写原始页面的翻译内容 | ||
|
||
|
||
|
||
注意事项: | ||
|
||
1. 代码参考: | ||
|
||
```py | ||
import torch | ||
|
||
x = torch.ones(5) # input tensor | ||
y = torch.zeros(3) # expected output | ||
w = torch.randn(5, 3, requires_grad=True) | ||
b = torch.randn(3, requires_grad=True) | ||
z = torch.matmul(x, w)+b | ||
loss = torch.nn.functional.binary_cross_entropy_with_logits(z, y) | ||
``` | ||
|
||
2. 公式参考: | ||
|
||
1) 无需换行的写法: | ||
|
||
$\sqrt{w^T*w}$ | ||
|
||
2) 需要换行的写法: | ||
|
||
$$ | ||
\sqrt{w^T*w} | ||
$$ | ||
|
||
3. 图片参考(用图片的实际地址就行): | ||
|
||
<img src='http://data.apachecn.org/img/logo/logo_green.png' width=20% /> | ||
|
||
4. **翻译完后请删除上面所有模版内容就行** |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,53 @@ | ||
> 翻译任务 | ||
* 目前该页面无人翻译,期待你的加入 | ||
* 翻译奖励: https://github.com/orgs/apachecn/discussions/243 | ||
* 任务认领: https://github.com/apachecn/pytorch-doc-zh/discussions/583 | ||
|
||
请参考这个模版来写内容: | ||
|
||
|
||
# PyTorch 某某页面 | ||
|
||
> 译者:[片刻小哥哥](https://github.com/jiangzhonglian) | ||
> | ||
> 项目地址:<https://pytorch.apachecn.org/2.0/tutorials/intermediate/TP_tutorial> | ||
> | ||
> 原始地址:<https://pytorch.org/tutorials//intermediate/TP_tutorial.html> | ||
开始写原始页面的翻译内容 | ||
|
||
|
||
|
||
注意事项: | ||
|
||
1. 代码参考: | ||
|
||
```py | ||
import torch | ||
|
||
x = torch.ones(5) # input tensor | ||
y = torch.zeros(3) # expected output | ||
w = torch.randn(5, 3, requires_grad=True) | ||
b = torch.randn(3, requires_grad=True) | ||
z = torch.matmul(x, w)+b | ||
loss = torch.nn.functional.binary_cross_entropy_with_logits(z, y) | ||
``` | ||
|
||
2. 公式参考: | ||
|
||
1) 无需换行的写法: | ||
|
||
$\sqrt{w^T*w}$ | ||
|
||
2) 需要换行的写法: | ||
|
||
$$ | ||
\sqrt{w^T*w} | ||
$$ | ||
|
||
3. 图片参考(用图片的实际地址就行): | ||
|
||
<img src='http://data.apachecn.org/img/logo/logo_green.png' width=20% /> | ||
|
||
4. **翻译完后请删除上面所有模版内容就行** |
53 changes: 53 additions & 0 deletions
53
...e/scaled_dot_product_attention_tutorial#using-sdpa-with-attn-bias-subclasses.md
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,53 @@ | ||
> 翻译任务 | ||
* 目前该页面无人翻译,期待你的加入 | ||
* 翻译奖励: https://github.com/orgs/apachecn/discussions/243 | ||
* 任务认领: https://github.com/apachecn/pytorch-doc-zh/discussions/583 | ||
|
||
请参考这个模版来写内容: | ||
|
||
|
||
# PyTorch 某某页面 | ||
|
||
> 译者:[片刻小哥哥](https://github.com/jiangzhonglian) | ||
> | ||
> 项目地址:<https://pytorch.apachecn.org/2.0/tutorials/intermediate/scaled_dot_product_attention_tutorial#using-sdpa-with-attn-bias-subclasses> | ||
> | ||
> 原始地址:<https://pytorch.org/tutorials//intermediate/scaled_dot_product_attention_tutorial#using-sdpa-with-attn-bias-subclasses.html> | ||
开始写原始页面的翻译内容 | ||
|
||
|
||
|
||
注意事项: | ||
|
||
1. 代码参考: | ||
|
||
```py | ||
import torch | ||
|
||
x = torch.ones(5) # input tensor | ||
y = torch.zeros(3) # expected output | ||
w = torch.randn(5, 3, requires_grad=True) | ||
b = torch.randn(3, requires_grad=True) | ||
z = torch.matmul(x, w)+b | ||
loss = torch.nn.functional.binary_cross_entropy_with_logits(z, y) | ||
``` | ||
|
||
2. 公式参考: | ||
|
||
1) 无需换行的写法: | ||
|
||
$\sqrt{w^T*w}$ | ||
|
||
2) 需要换行的写法: | ||
|
||
$$ | ||
\sqrt{w^T*w} | ||
$$ | ||
|
||
3. 图片参考(用图片的实际地址就行): | ||
|
||
<img src='http://data.apachecn.org/img/logo/logo_green.png' width=20% /> | ||
|
||
4. **翻译完后请删除上面所有模版内容就行** |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,53 @@ | ||
> 翻译任务 | ||
* 目前该页面无人翻译,期待你的加入 | ||
* 翻译奖励: https://github.com/orgs/apachecn/discussions/243 | ||
* 任务认领: https://github.com/apachecn/pytorch-doc-zh/discussions/583 | ||
|
||
请参考这个模版来写内容: | ||
|
||
|
||
# PyTorch 某某页面 | ||
|
||
> 译者:[片刻小哥哥](https://github.com/jiangzhonglian) | ||
> | ||
> 项目地址:<https://pytorch.apachecn.org/2.0/tutorials/intermediate/tiatoolbox_tutorial> | ||
> | ||
> 原始地址:<https://pytorch.org/tutorials//intermediate/tiatoolbox_tutorial.html> | ||
开始写原始页面的翻译内容 | ||
|
||
|
||
|
||
注意事项: | ||
|
||
1. 代码参考: | ||
|
||
```py | ||
import torch | ||
|
||
x = torch.ones(5) # input tensor | ||
y = torch.zeros(3) # expected output | ||
w = torch.randn(5, 3, requires_grad=True) | ||
b = torch.randn(3, requires_grad=True) | ||
z = torch.matmul(x, w)+b | ||
loss = torch.nn.functional.binary_cross_entropy_with_logits(z, y) | ||
``` | ||
|
||
2. 公式参考: | ||
|
||
1) 无需换行的写法: | ||
|
||
$\sqrt{w^T*w}$ | ||
|
||
2) 需要换行的写法: | ||
|
||
$$ | ||
\sqrt{w^T*w} | ||
$$ | ||
|
||
3. 图片参考(用图片的实际地址就行): | ||
|
||
<img src='http://data.apachecn.org/img/logo/logo_green.png' width=20% /> | ||
|
||
4. **翻译完后请删除上面所有模版内容就行** |
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