Tensorflow: extract sequential patches from a complex tensor of arbitrary length

I'm trying to figure out how to extract sequential patches from a complex valued tensor where the length is variable. The extraction is being performed as part of a tf.data pipeline.

If the tensor were not complex, I'd use tf.image.extract_image_patches as in this answer.

However, that function does not work with complex tensors. I have tried the following technique, but it fails because the length of the tensor is unknown.

def extract_sequential_patches(image):
    image_length = tf.shape(image)[0]
    num_patches = image_length // (128 // 4)
    patches = []
    for i in range(num_patches):
        start = i * 128
        end = start + 128
        patches.append(image[start:end, ...])
    return tf.stack(patches)

However I get the error:

InaccessibleTensorError: The tensor 'Tensor("strided_slice:0", shape=(None, 512, 2), dtype=complex64)' cannot be accessed here: it is defined in another function or code block. Use return values, explicit Python locals or TensorFlow collections to access it. Defined in: FuncGraph(name=while_body_2100, id=140313967335120)

I have tried liberal decoration with @tf.function

from Tensorflow: extract sequential patches from a complex tensor of arbitrary length