Tensorflow: Slicing a Tensor into overlapping blocks

Question

I have a 1D tensor that I wish to partition into overlapping blocks. I\'m thinking of something like: tensor = tf.constant([1, 2, 3, 4, 5, 6, 7])

Answer 1

Here is a relatively straight forward approach using your example:

def overlapping_blocker(tensor,block_size,stride):
    blocks = []
    n = tensor.get_shape().as_list()[0]
    ilo = range(0, n, stride)
    ihi = range(block_size, n+1, stride)
    ilohi = zip(ilo, ihi).
    for ilo, ihi in ilohi:
        blocks.append(tensor[ilo:ihi])
    return(tf.pack(blocks, 0))

with tf.Session() as sess:
    tensor = tf.constant([1., 2., 3., 4., 5., 6., 7.])
    block_tensor = overlapping_blocker(tensor, 3, 2)
    print(sess.run(block_tensor))

Output:

[[ 1.  2.  3.]
 [ 3.  4.  5.]
 [ 5.  6.  7.]]