How to roll without periodic boundaries in TensorFlow?

Question

I need a transformation of a tensor which is very similar to roll. The difference is that I do not want the values from the end of the axis to appear in the beginning. In other words I want, for example, the 2nd element to be on 3d place but I do not want the last element to become the first one. Instead, I want the first elements to be zeros.

I have tried this:

prev_xs = tf.roll(xs, shift = 1, axis = 1)
prev_xs[:,0] = 0.0

However, it does not work because

TypeError: 'Tensor' object does not support item assignment

So, what is the proper solution of the problem?

xdurch0 · Accepted Answer · 2019-02-20 09:35:52Z

6

You could use

prev_xs = tf.concat((tf.zeros([tf.shape(xs)[0], 1]), xs[:, :1]), axis=1)

Step-by-step, we discard the last column of xs by indexing like [:, :1]. We create a column of zeros with the appropriate number of rows. Then we concatenate it in front of xs, pushing every column back by 1.

answered Feb 20, 2019 at 9:35

xdurch0

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