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rd11 February 2016
### How can we replace a single element in an n-D Tensor in TensorFlow?

If we have a 1-D Tensor, we can replace a single element with a 0-D Tensor by using `tf.scatter_update`

or by unpacking, replacing, packing.

Example:

```
# Pretend x came from somewhere useful.
x = tf.Variable(0)
A = tf.Variable([1, 2, 3])
# Replace the 2 with whatever's in x
A = tf.scatter_update(A, 1, x)
```

`A`

will now produce `[1, 0, 3]`

.

Is it possible to do this with n-D arrays?

Example:

```
# Pretend x came from somewhere useful.
x = tf.Variable(0, dtype=tf.float32)
A = tf.Variable(np.random.rand(3, 3, 3, 3))
# What's the equivalent of A[1, 1, 1, 1] = x ?
```

I think I could get the desired result with a mixture of `tf.unpack`

, `tf.scatter_update`

, and `tf.pack`

, but it'd be verbose, and we'd be replacing a (potentially large) 3-D Tensor instead of just replacing a tiny 0-D Tensor. Is there a better way?

If you want to do this efficiently, I believe you will need to write a new Op or generalize scatter_update.

Asked in February 2016

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Viewed 3,684 times

Voted 12

Answered 1 times