Updated from tensor_scatter_add to tensor_scatter_nd_add
PiperOrigin-RevId: 427064144
Change-Id: I09b0075e379695462200c84f151f3dd182153e38
diff --git a/tensorflow/core/api_def/base_api/api_def_TensorScatterAdd.pbtxt b/tensorflow/core/api_def/base_api/api_def_TensorScatterAdd.pbtxt
index ddec1ce..0bddf12 100644
--- a/tensorflow/core/api_def/base_api/api_def_TensorScatterAdd.pbtxt
+++ b/tensorflow/core/api_def/base_api/api_def_TensorScatterAdd.pbtxt
@@ -45,23 +45,18 @@
indices.shape[:-1] + tensor.shape[indices.shape[-1]:]
-The simplest form of tensor_scatter_add is to add individual elements to a
+The simplest form of `tensor_scatter_nd_add` is to add individual elements to a
tensor by index. For example, say we want to add 4 elements in a rank-1
tensor with 8 elements.
In Python, this scatter add operation would look like this:
-```python
- indices = tf.constant([[4], [3], [1], [7]])
- updates = tf.constant([9, 10, 11, 12])
- tensor = tf.ones([8], dtype=tf.int32)
- updated = tf.tensor_scatter_nd_add(tensor, indices, updates)
- print(updated)
-```
-
-The resulting tensor would look like this:
-
- [1, 12, 1, 11, 10, 1, 1, 13]
+>>> indices = tf.constant([[4], [3], [1], [7]])
+>>> updates = tf.constant([9, 10, 11, 12])
+>>> tensor = tf.ones([8], dtype=tf.int32)
+>>> updated = tf.tensor_scatter_nd_add(tensor, indices, updates)
+<tf.Tensor: shape=(8,), dtype=int32,
+numpy=array([ 1, 12, 1, 11, 10, 1, 1, 13], dtype=int32)>
We can also, insert entire slices of a higher rank tensor all at once. For
example, if we wanted to insert two slices in the first dimension of a
@@ -69,25 +64,20 @@
In Python, this scatter add operation would look like this:
-```python
- indices = tf.constant([[0], [2]])
- updates = tf.constant([[[5, 5, 5, 5], [6, 6, 6, 6],
+>>> indices = tf.constant([[0], [2]])
+>>> updates = tf.constant([[[5, 5, 5, 5], [6, 6, 6, 6],
[7, 7, 7, 7], [8, 8, 8, 8]],
[[5, 5, 5, 5], [6, 6, 6, 6],
[7, 7, 7, 7], [8, 8, 8, 8]]])
- tensor = tf.ones([4, 4, 4],dtype=tf.int32)
- updated = tf.tensor_scatter_nd_add(tensor, indices, updates)
- print(updated)
-```
+>>> tensor = tf.ones([4, 4, 4],dtype=tf.int32)
+>>> updated = tf.tensor_scatter_nd_add(tensor, indices, updates)
+<tf.Tensor: shape=(4, 4, 4), dtype=int32,
+numpy=array([[[6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8], [9, 9, 9, 9]],
+ [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]],
+ [[6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8], [9, 9, 9, 9]],
+ [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]]], dtype=int32)>
-The resulting tensor would look like this:
-
- [[[6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8], [9, 9, 9, 9]],
- [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]],
- [[6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8], [9, 9, 9, 9]],
- [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]]]
-
-Note that on CPU, if an out of bound index is found, an error is returned.
+Note: on CPU, if an out of bound index is found, an error is returned.
On GPU, if an out of bound index is found, the index is ignored.
END
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