import os
import sys
import numpy as np

import paddle
import paddle.nn as nn
from paddle.nn import Layer
import paddle.nn.functional as F

SRM_npy = np.load('SRM_Kernels.npy')

残差网络卷积2D卷积

class Res_conv2d(nn.Layer):
definit(self):
super(Res_conv2d, self).init()
self.weight = paddle.create_parameter([30,1,5,5],dtype = "float32")
self.bias = paddle.create_parameter([30],dtype = "float32")
self.reset_parameters()

def reset_parameters(self):
    self.weight.shape.numpy()[:] = SRM_npy#报错
    self.bias.shape.zero_()   #报错

def forward(self, input):
    return F.conv2d(input, self.weight, self.bias)

问题：之前self.weight = Parameter(torch.Tensor(30, 1, 5, 5), requires_grad=True)
通过API文档用paddle.create_parameter([30,1,5,5],dtype = "float32")替换，但在替换之后不确定新生成的shape和原来的torch.Tensor(30, 1, 5, 5)是不是同一格式，也就是不确定shape是不是Tensor。
假如是Tensor，为什么在报错部分self.weight.shape.numpy()[:] = SRM_npy会显示没有numpy（）。