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【Hackathon 5th No.61】Skillful nowcasting of extreme precipitation with NowcastNet #593
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Thanks for your contribution! |
input_frames = frames[:, : self.input_length] | ||
input_frames = input_frames.reshape((batch, self.input_length, height, width)) | ||
# Evolution Network | ||
intensity, motion = self.evo_net(input_frames) |
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发现推理结果的图片与参考代码的有些差异,应该是某处没有对齐导致的,我这边帮忙查了下发现这个网络给定相同输入时输出存在2e-4左右的差异,需要在详细查一下,修改后建议再对整个网络整体检查下对齐情况
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从其他模型复现遇到的问题比较,可能是初始化随机数不同结果有差异,如果是网络问题会模型不能运行或结果差异会较大。
模型是按源码复现的,那如果不大明确,就不在这上面花时间了
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当前情况:paddle的grid_sample的CPU结果跟torch的GPU结果能对齐,GPU结果跟torch的CPU结果能对齐,但是把这个运算改到cpu上,后面仍然有没对齐的地方。by @HydrogenSulfate @zhiminzhang0830
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后面仍然有没对齐
@luotao1 @HydrogenSulfate 这边check过了,后面没对齐仍然是grid_sample的问题,这个PR除了grid_sample外基本OK了,还有几处格式问题需要辛苦 @co63oc 再优化一下就可以合入了。
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class Generative_Decoder(paddle.nn.Layer): | ||
def __init__(self, opt): |
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Generative_Decoder 可以直接改为使用多个入参么,类似这样
def __init__(self, ngf, evo_ic, gen_oc, ic_feature):
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其他子层需要使用opt,如果拆开其他子层也要拆开,代码参数变量较多
NowCastNet需要用到 OpenCV, 需要在requirements.txt里添加该库 opencv-python |
已修改 |
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LGTM
…h NowcastNet (PaddlePaddle#593) * Add nowcastnet * Fix
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Describe
No.61:Skillful nowcasting of extreme precipitation with NowcastNet
论文链接:
https://www.nature.com/articles/s41586-023-06184-4#Abs1
参考代码链接:
https://codeocean.com/capsule/3935105/tree/v1
RFC PaddlePaddle/community#705
使用预训练模型生成图
torch测试图
paddle测试图
运行命令
预训练模型和数据集下载