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【PPSCI Doc No.10、11、30】 #724

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Dec 29, 2023
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【PPSCI Doc No.10、11、30】 #724

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39193b3
refine comments of ppsci.data.dataset.MeshAirfoilDataset, ppsci.data.…
MayYouBeProsperous Dec 27, 2023
bff4cb5
fix
MayYouBeProsperous Dec 29, 2023
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MayYouBeProsperous Dec 29, 2023
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17 changes: 17 additions & 0 deletions ppsci/arch/cfdgcn.py
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Expand Up @@ -201,6 +201,23 @@ class CFDGCN(nn.Layer):
hidden_channel (int, optional): Number of channels of hidden layer. Defaults to 512.
out_channel (int, optional): Number of channels of output. Defaults to 3.
su2_module (Optional[Callable]): SU2Module Object. Defaults to None.

Examples:
>>> import ppsci
>>> import su2paddle # doctest: +SKIP
>>> model = ppsci.arch.CFDGCN(
... input_keys=("input"),
... output_keys=("pred"),
... config_file="/path/to/file.cfg",
... coarse_mesh="/path/to/file.su2",
... process_sim=None,
... freeze_mesh=False,
... num_convs=6,
... num_end_convs=3,
... hidden_channel=512,
... out_channel=3,
... su2_module=su2paddle.SU2Module,
... ) # doctest: +SKIP
"""

def __init__(
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23 changes: 20 additions & 3 deletions ppsci/arch/unetex.py
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Expand Up @@ -174,9 +174,9 @@ def create_decoder(


class UNetEx(base.Arch):
"""U-Net
"""U-Net Extension for CFD.

[Ribeiro M D, Rehman A, Ahmed S, et al. DeepCFD: Efficient steady-state laminar flow approximation with deep convolutional neural networks[J]. arXiv preprint arXiv:2004.08826, 2020.](https://arxiv.org/abs/2004.08826)
Reference: [Ribeiro M D, Rehman A, Ahmed S, et al. DeepCFD: Efficient steady-state laminar flow approximation with deep convolutional neural networks[J]. arXiv preprint arXiv:2004.08826, 2020.](https://arxiv.org/abs/2004.08826)

Args:
input_key (str): Name of function data for input.
Expand All @@ -193,7 +193,24 @@ class UNetEx(base.Arch):

Examples:
>>> import ppsci
>>> model = ppsci.arch.ppsci.arch.UNetEx("input", "output", 3, 3, (8, 16, 32, 32), 5, False, False)
>>> model = ppsci.arch.UNetEx(
... input_key="input",
... output_key="output",
... in_channel=3,
... out_channel=3,
... kernel_size=5,
... filters=(4, 4, 4, 4),
... layers=3,
... weight_norm=False,
... batch_norm=False,
... activation=None,
... final_activation=None,
... )
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这里是否可以构造一个input_dict，然后输入到该model里，然后得到output_dict,再打印output_dict["output"]呢？上面那个CFDGCN不太方便加这个测试，但是UNetEx应该可以吧

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@HydrogenSulfate HydrogenSulfate Dec 27, 2023 •
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如果可以的话形状可以用128x128或者64x64啥的，不用太大否则有的机器测试都跑不了

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好的，UNetEx 增加测试。output_dict["output"] 需要打印对比吗？数据比较多。

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好的，UNetEx 增加测试。output_dict["output"] 需要打印对比吗？数据比较多。

不用，只需要打印并校验输出数据的形状即可

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Done.

>>> input_dict = {'input': paddle.rand([4, 3, 4, 4])}
>>> output_dict = model(input_dict)
>>> print(output_dict['output']) # doctest: +SKIP
>>> print(output_dict['output'].shape)
[4, 3, 4, 4]
"""

def __init__(
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10 changes: 10 additions & 0 deletions ppsci/data/dataset/airfoil_dataset.py
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Expand Up @@ -97,6 +97,16 @@ class MeshAirfoilDataset(io.Dataset):
data_dir (str): Directory of MeshAirfoil data.
mesh_graph_path (str): Path of mesh graph.
transpose_edges (bool, optional): Whether transpose the edges array from (2, num_edges) to (num_edges, 2) for convenient of slicing.

Examples:
>>> import ppsci
>>> dataset = ppsci.data.dataset.MeshAirfoilDataset(
... "input_keys": ("input",),
... "label_keys": ("output",),
... "data_dir": "/path/to/MeshAirfoilDataset",
... "mesh_graph_path": "/path/to/file.su2",
... "transpose_edges": False,
... ) # doctest: +SKIP
"""

use_pgl: bool = True
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9 changes: 9 additions & 0 deletions ppsci/data/dataset/cylinder_dataset.py
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Expand Up @@ -44,6 +44,15 @@ class MeshCylinderDataset(io.Dataset):
label_keys (Tuple[str, ...]): Name of label data.
data_dir (str): Directory of MeshCylinder data.
mesh_graph_path (str): Path of mesh graph.

Examples:
>>> import ppsci
>>> dataset = ppsci.data.dataset.MeshAirfoilDataset(
... "input_keys": ("input",),
... "label_keys": ("output",),
... "data_dir": "/path/to/MeshAirfoilDataset",
... "mesh_graph_path": "/path/to/file.su2",
... ) # doctest: +SKIP
"""

use_pgl: bool = True
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