如何在Tensorflow中复制PyTorch的nn.functional.unfold函数？

Question

我想使用tensorflow重写pytorch的torch.nn.functional.unfold函数：

#input x:[16, 1, 50, 36]
x = torch.nn.functional.unfold(x, kernel_size=(5, 36), stride=3)
#output x:[16, 180, 16]

我尝试使用函数tf.extract_image_patches()：

x = tf.extract_image_patches(x,ksizes=[1, 1,5, 98],strides=[1, 1, 3, 1], rates=[1, 1, 1, 1],padding='VALID')

输入x.shape：[16,1,64,98]

我得到输出x.shape：[16,1,20,490]

然后我将X重塑为[16,490,20]，这是我所期望的

但当我输入数据时，我得到了错误：

UnimplementedError (see above for traceback): Only support ksizes across space.
[[Node:hcn/ExtractImagePatches = ExtractImagePatches[T=DT_FLOAT, ksizes=[1, 1, 5, 98], padding="VALID", rates=[1, 1, 1, 1], strides=[1, 1, 3, 1], _device="/job:localhost/replica:0/task:0/device:GPU:0"](hcn/Reshape)]]

如何使用tensorflow重写pytorchtorch.nn.functional.unfold函数来更改X

Answer 1

x = tf.reshape(x, [16, 50, 36, 1])
x = tf.extract_image_patches(x, ksizes=[1, 4, 98, 1], strides=[1, 4, 1, 1], rates=[1, 1, 1, 1], padding='VALID')