int object has no attribute shape while defining convolutions

Question

I am using the following snippet for implementing convolution function in CNN.

def conv(x, in_channels, out_channels, kernel_size, stride, padding, weight, bias):
"""
Args:
    x: torch tensor with size (N, C_in, H_in, W_in),
    in_channels: number of channels in the input image, it is C_in;
    out_channels: number of channels produced by the convolution;
    kernel_size: size of onvolving kernel, 
    stride: stride of the convolution,
    padding: implicit zero padding to be added on both sides of each dimension,
    
Return:
    y: torch tensor of size (N, C_out, H_out, W_out)
"""

y = None
xKernShape = kernel_size
yKernShape = kernel_size
xImgShape = x.shape[2]
yImgShape = x.shape[3]
xOutput = int(((xImgShape - xKernShape + 2 * padding) / stride) + 1)
yOutput = int(((yImgShape - yKernShape + 2 * padding) / stride) + 1)
output = np.zeros((xOutput, yOutput))
if padding != 0:
    imagePadded = np.zeros((x.shape[2] + padding*2, x.shape[3] + padding*2))
    imagePadded[int(padding):int(-1 * padding), int(padding):int(-1 * padding)] = x
    print(imagePadded)
else:
    imagePadded = x
for i in range(x.shape[3]):
    if i > x.shape[3] - yKernShape:
        break
    if i % stride == 0:
        for j in range(x.shape[2]):
            if j > x.shape[2] - xKernShape:
                break
            try:
                if j % stride == 0:
                    output[j, i] = (kernel_size * imagePadded[j: j + xKernShape, i: i + yKernShape]).sum()
                    y = np.array(np.hsplit(output, 1)).reshape((x.shape[0], out_channels, j, i))  
            except:
                break
return y

However, when I run this using call conv(x,in_channels=3,out_channels=6,kernel_size=3,stride=1,padding=0,weight=torch_conv.weight,bias=torch_conv.bias)

I am getting

AttributeError                            Traceback (most recent call last)
<ipython-input-71-f4d6ee7b5fd8> in <module>
      6                       padding=0,
      7                       weight=torch_conv.weight,
----> 8                       bias=torch_conv.bias)

<ipython-input-70-1d0a9f0d9820> in my_conv(x, in_channels, out_channels, kernel_size, stride, padding, weight, bias)
     33         if i % stride == 0:
     34             for x in range(x.shape[2]):
---> 35                 if x > x.shape[2] - xKernShape:
     36                     break
     37                 try:

AttributeError: 'int' object has no attribute 'shape'

My input is 2X3X32X32.

Can anyone please help?

you have `for j` in your code but `for x` in the error message — AndrzejO, Sep 24 '22 at 16:01

score 0 · Answer 1 · answered Sep 24 '22 at 23:03

Instead of this :

for x in range(x.shape[2]):
  if x > x.shape[2] - xKernShape:
    break

Try this :

for j in range(x.shape[2]):
   if j > x.shape[2]-xKernShape:
     break

In general when x in for loop for x in something, it seems like it becomes an integer and then at the next line you request the shape out of it but it has no shape because it is just an integer. I think it is a typo of yours as the function you referred to was a bit different in this loop

int object has no attribute shape while defining convolutions

1 Answers1