index_sample¶

paddle. index_sample ( x, index ) [source]

IndexSample Layer

IndexSample OP returns the element of the specified location of X, and the location is specified by Index.

Given:

X = [[1, 2, 3, 4, 5],
     [6, 7, 8, 9, 10]]

Index = [[0, 1, 3],
         [0, 2, 4]]

Then:

Out = [[1, 2, 4],
       [6, 8, 10]]

Parameters

• x (Tensor) – The source input tensor with 2-D shape. Supported data type is int32, int64, bfloat16, float16, float32, float64.

• index (Tensor) – The index input tensor with 2-D shape, first dimension should be same with X. Data type is int32 or int64.

Returns

The output is a tensor with the same shape as index.

Return type

output (Tensor)

Examples

import paddle

x = paddle.to_tensor([[1.0, 2.0, 3.0, 4.0],
                      [5.0, 6.0, 7.0, 8.0],
                      [9.0, 10.0, 11.0, 12.0]], dtype='float32')
index = paddle.to_tensor([[0, 1, 2],
                          [1, 2, 3],
                          [0, 0, 0]], dtype='int32')
target = paddle.to_tensor([[100, 200, 300, 400],
                           [500, 600, 700, 800],
                           [900, 1000, 1100, 1200]], dtype='int32')
out_z1 = paddle.index_sample(x, index)
print(out_z1)
#[[1. 2. 3.]
# [6. 7. 8.]
# [9. 9. 9.]]

# Use the index of the maximum value by topk op
# get the value of the element of the corresponding index in other tensors
top_value, top_index = paddle.topk(x, k=2)
out_z2 = paddle.index_sample(target, top_index)
print(top_value)
#[[ 4.  3.]
# [ 8.  7.]
# [12. 11.]]

print(top_index)
#[[3 2]
# [3 2]
# [3 2]]

print(out_z2)
#[[ 400  300]
# [ 800  700]
# [1200 1100]]