比较与torch.nn.PReLU的差异

class torch.nn.PReLU(num_parameters=1, init=0.25)(input) -> Tensor

class mindspore.nn.PReLU(channel=1, w=0.25)(x) -> Tensor

# PyTorch
import torch
from torch import tensor
from torch import nn
import numpy as np

x = tensor(np.array([[0.1, -0.6], [-0.9, 0.9]]), dtype=torch.float32)
m = nn.PReLU()
out = m(x)
output = out.detach().numpy()
print(output)
# [[ 0.1   -0.15 ]
#  [-0.225  0.9  ]]

# MindSpore
import mindspore
from mindspore import Tensor
import mindspore.nn as nn
import numpy as np

x = Tensor(np.array([[0.1, -0.6], [-0.9, 0.9]]), mindspore.float32)
prelu = nn.PReLU()
output = prelu(x)
print(output)
# [[ 0.1   -0.15 ]
#  [-0.225  0.9  ]]

# PyTorch
import torch
from torch import tensor
from torch import nn
import numpy as np

x = tensor(np.array([[0.1, -0.6], [-0.5, 0.9]]), dtype=torch.float32)
m = nn.PReLU(num_parameters=1, init=0.5)
out = m(x)
output = out.detach().numpy()
print(output)
# [[ 0.1  -0.3 ]
#  [-0.25  0.9 ]]

# MindSpore
import mindspore
import mindspore.nn as nn
from mindspore import Tensor
import numpy as np

x = Tensor(np.array([[0.1, -0.6], [-0.5, 0.9]]), mindspore.float32)
prelu = nn.PReLU(channel=1, w=0.5)
output = prelu(x)
print(output)
# [[ 0.1  -0.3 ]
#  [-0.25  0.9 ]]