【PPSCI Doc No.12、13、14、15、16、17】ppsci.arch.Arch #752
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HydrogenSulfate requested changes Jan 15, 2024
ppsci/arch/base.py Outdated
Comment on lines 77 to 92
| >>> import paddle | ||
| >>> import ppsci | ||
| >>> model = ppsci.arch.Arch() | ||
| >>> # fetch one tensor | ||
| >>> out = model.concat_to_tensor({'x':paddle.to_tensor(123)}, ('x',)) | ||
| >>> print(out) | ||
| Tensor(shape=[], dtype=int64, place=Place(gpu:0), stop_gradient=True, | ||
| 123) | ||
| >>> # fetch more tensors | ||
| >>> out = model.concat_to_tensor( | ||
| ... {'x1':paddle.to_tensor([123]), 'x2':paddle.to_tensor([234])}, | ||
| ... ('x1', 'x2'), | ||
| ... axis=0) | ||
| >>> print(out) | ||
| Tensor(shape=[2], dtype=int64, place=Place(gpu:0), stop_gradient=True, | ||
| [123, 234]) |
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- 感觉改成2D的Tensor能更好，因为2D更符合实际场景，用paddle.randn([8, 1])这种形状就行
- 输出改成这样：
print(out.dtype, out.shape)，这样能避免cpu设备运行的问题，也重点展示了数据类型和数据形状。
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这个 pydoctest 不太好用 ... ... 可以试试 xdoctest，或者用 paddle 前段时间的 doctester 来验证示例代码会比较好 ～
单纯的提个建议 ～～～ 😅
https://github.com/PaddlePaddle/Paddle/blob/develop/tools/sampcd_processor.py
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这个 pydoctest 不太好用 ... ... 可以试试 xdoctest，或者用 paddle 前段时间的 doctester 来验证示例代码会比较好 ～
单纯的提个建议 ～～～ 😅
https://github.com/PaddlePaddle/Paddle/blob/develop/tools/sampcd_processor.py
谢谢大佬的建议，我研究一下，如果好用的话我就尽快换上
ppsci/arch/base.py Outdated
Comment on lines 113 to 127
| Examples: | ||
| >>> import paddle | ||
| >>> import ppsci | ||
| >>> model = ppsci.arch.Arch() | ||
| >>> # split one tensor | ||
| >>> out = model.split_to_dict(paddle.to_tensor(123), ('x',)) | ||
| >>> print(out) | ||
| {'x': Tensor(shape=[], dtype=int64, place=Place(gpu:0), stop_gradient=True, | ||
| 123)} | ||
| >>> # split more tensors | ||
| >>> out = model.split_to_dict(paddle.to_tensor([123, 234]), ('x1', 'x2'), axis=0) | ||
| >>> print(out) | ||
| {'x1': Tensor(shape=[1], dtype=int64, place=Place(gpu:0), stop_gradient=True, | ||
| [123]), 'x2': Tensor(shape=[1], dtype=int64, place=Place(gpu:0), stop_gradient=True, | ||
| [234])} |
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同上，并且输出代码可以改成
for k, v in out.items(): print(f"{k} {v.dtype} {v.shape}") ppsci/arch/base.py Outdated
Comment on lines 145 to 153
| Examples: | ||
| >>> import ppsci | ||
| >>> def transform_fn(in_): | ||
| ... x = in_["x"] | ||
| ... x = 2.0 * x | ||
| ... input_trans = {"x": x} | ||
| ... return input_trans | ||
| >>> model = ppsci.arch.Arch() | ||
| >>> model.register_input_transform(transform_fn) |
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这个example讲清楚了如何注册，但没有很好地展示transform_fn是如何作用的，所以：
- 可以使用MLP这个类作为model，并且接受"x"和"2x"这两个key作为输入关键字，输出y
- 然后register一个transform_in，它接受原始输入
input = {"x": paddle.randn([4, 1])}，然后根据原始输入"x"，生成"2x"（=2*x）， - 运行model(input)，然后打印输出的y的类型和形状。
ppsci/arch/base.py Outdated
Comment on lines 173 to 181
| >>> import ppsci | ||
| >>> def transform_fn(in_, out): | ||
| ... x = in_["x"] | ||
| ... y = out["y"] | ||
| ... u = 2.0 * x * y | ||
| ... output_trans = {"u": u} | ||
| ... return output_trans | ||
| >>> model = ppsci.arch.Arch() | ||
| >>> model.register_output_transform(transform_fn) |
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- 函数名改成transform_out
- 可以通过transform_out往输出dict中加入额外的内容，然后将结果打印出来，这样更容易让人理解
Comment on lines +189 to +193
| Examples: | ||
| >>> import ppsci | ||
| >>> model = ppsci.arch.Arch() | ||
| >>> # freeze all parameters and make model `eval` | ||
| >>> model.freeze() |
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末尾加上如下验证代码：
assert p.training is False for p in model.parameters(): assert p.stop_gradient is True Comment on lines 202 to 210
| """Unfreeze all parameters. | ||
| Examples: | ||
| >>> import ppsci | ||
| >>> model = ppsci.arch.Arch() | ||
| >>> # unfreeze all parameters and make model `train` | ||
| >>> model.unfreeze() | ||
| """ |
Closed
|
x这个字典会经过transform_in进行处理，所以通过以下方式体现transform_in具备“对x进行修改”这一能力 |
这个有点绕 ～～～ 🤣🤣🤣 帮忙看看现在对不对 ～ 谢谢！ |
HydrogenSulfate requested changes Jan 15, 2024
ppsci/arch/base.py Outdated
| >>> import ppsci | ||
| >>> model = ppsci.arch.Arch() | ||
| >>> # fetch one tensor | ||
| >>> out = model.concat_to_tensor({'x':paddle.to_tensor(123)}, ('x',)) |
There was a problem hiding this comment.
- 这里的输入建议使用2D+float32 Tensor，比如[8,1]这种，0 DTensor不太有代表性
- 构造输入用
paddle.randn(shape)更好
ppsci/arch/base.py Outdated
| paddle.int64 [] | ||
| >>> # fetch more tensors | ||
| >>> out = model.concat_to_tensor( | ||
| ... {'x1':paddle.to_tensor([[1, 2], [2, 3]]), 'x2':paddle.to_tensor([[3, 4], [4, 5]])}, |
ppsci/arch/base.py Outdated
Comment on lines 116 to 125
| >>> out = model.split_to_dict(paddle.to_tensor(123), ('x',)) | ||
| >>> for k, v in out.items(): | ||
| ... print(f"{k} {v.dtype} {v.shape}") | ||
| x paddle.int64 [] | ||
| >>> # split more tensors | ||
| >>> out = model.split_to_dict(paddle.to_tensor([[1, 2], [2, 3]]), ('x1', 'x2'), axis=0) | ||
| >>> for k, v in out.items(): | ||
| ... print(f"{k} {v.dtype} {v.shape}") | ||
| x1 paddle.int64 [1, 2] | ||
| x2 paddle.int64 [1, 2] |
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同上，类型和形状可以改成二维+flaot32
| 已修改输入数据为 paddle.rand ~ |
huohuohuohuohuo123 pushed a commit to huohuohuohuohuo123/PaddleScience that referenced this pull request Aug 12, 2024
* [Add] arch examples * [Change] examples * [Change] examples * [Change] register_input_transform * [Change] data with rand --------- Co-authored-by: HydrogenSulfate <490868991@qq.com>
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补充 ppsci.arch.Arch 中的示例代码
关联 PR #686
@HydrogenSulfate
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