centos7版本运行python机器学习模型

2023-12-13 22:30:40

1；下载数据源的问题
在利用conda环境下载pytorch的时候，会遇到网速很慢的情况，可以选用#清华镜像网站
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple/ .

New in version 1.3.0

import torch
from pytorch_wavelets import DWT1DForward, DWT1DInverse  # or simply DWT1D, IDWT1D
dwt = DWT1DForward(wave='db6', J=3)
X = torch.randn(10, 5, 100)
yl, yh = dwt(X)
print(yl.shape)
>>> torch.Size([10, 5, 22])
print(yh[0].shape)
>>> torch.Size([10, 5, 55])
print(yh[1].shape)
>>> torch.Size([10, 5, 33])
print(yh[2].shape)
>>> torch.Size([10, 5, 22])
idwt = DWT1DInverse(wave='db6')
x = idwt((yl, yh))

New in version 1.2.0

import torch
from pytorch_wavelets import ScatLayer
scat = ScatLayer()
X = torch.randn(10,5,64,64)
# A first order scatternet with 6 orientations and one lowpass channels
# gives 7 times the input channel dimension
Z = scat(X)
print(Z.shape)
>>> torch.Size([10, 35, 32, 32])
# A second order scatternet with 6 orientations and one lowpass channels
# gives 7^2 times the input channel dimension
scat2 = torch.nn.Sequential(ScatLayer(), ScatLayer())
Z = scat2(X)
print(Z.shape)
>>> torch.Size([10, 245, 16, 16])
# We also have a slightly more specialized, but slower, second order scatternet
from pytorch_wavelets import ScatLayerj2
scat2a = ScatLayerj2()
Z = scat2a(X)
print(Z.shape)
>>> torch.Size([10, 245, 16, 16])
# These all of course work with cuda
scat2a.cuda()
Z = scat2a(X.cuda())

文章来源:https://blog.csdn.net/qq_41542141/article/details/134902958
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