shink

if __name__ == '__main__':
    import torch

    torch.set_default_device('cuda')

    t1 = torch.tensor([1, 2, 3, 3, 4, 5, 6, 7, 8], dtype=torch.float)
    res1 = torch.histc(t1, 5, 7, 7)
    print(res1)

    t2 = torch.tensor([7], dtype=torch.float)

shink

if __name__ == '__main__':
    from kan import *
    import torch
    import torchvision

    # create a KAN: 2D inputs, 1D output, and 5 hidden neurons. cubic spline (k=3), 5 grid intervals (grid=5).
    model = KAN(width=[2, 5, 1], grid=5, k=3, device='cpu', seed=0)

    # create dataset f(x,y) = exp(sin(pix)+y^2)
    f = lambda x: torch.exp(torch.sin(torch.pi * x[:, [0]]) + x[:, [1]] ** 2)

shink

<mirror>
  <id>confluent</id>
  <mirrorOf>confluent</mirrorOf>
  <name>Confluent</name>
  <url>https://packages.confluent.io/maven/</url>
</mirror>

shink

# device info
CONFIG_TARGET_ramips=y
CONFIG_TARGET_ramips_mt7621=y
CONFIG_TARGET_ramips_mt7621_DEVICE_phicomm_k2p=y

# mips fpu
CONFIG_KERNEL_MIPS_FPU_EMULATOR=y

# package
CONFIG_PACKAGE_curl=y