我想用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]我尝试使用该功能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 重塑X为[16,490,20]，这正是我所期望的。但是当我输入数据时出现错误：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)]]我如何使用tensorflow重写pytorchtorch.nn.functional.unfold函数来更改X？
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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')
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