com.microsoft - GatherND#

GatherND - 1 (com.microsoft)#

Version

name: GatherND (GitHub)
domain: com.microsoft
since_version: 1
function:
support_level:
shape inference:

This version of the operator has been available since version 1 of domain com.microsoft.

Summary

Given data tensor of rank r >= 1, and indices tensor of rank q >= 1, gather slices of data into an output tensor of rank q - 1 + r - indices[-1]. Example 1:

data = [[0,1],[2,3]] indices = [[0,0],[1,1]] output = [0,3]

Example 2:: data = [[0,1],[2,3]] indices = [[1],[0]] output = [[2,3],[0,1]]
Example 3:: data = [[[0,1],[2,3]],[[4,5],[6,7]]] indices = [[0,1],[1,0]] output = [[2,3],[4,5]]
Example 4:: data = [[[0,1],[2,3]],[[4,5],[6,7]]] indices = [[[0,1]],[[1,0]]] output = [[[2,3]],[[4,5]]]

Inputs

data (heterogeneous) - T: Tensor of rank r >= 1.
indices (heterogeneous) - Tind: Tensor of rank q >= 1.

Outputs

output (heterogeneous) - T: Tensor of rank q-1+r-indices[-1].

Examples

_int32

node = onnx.helper.make_node(
    "GatherND",
    inputs=["data", "indices"],
    outputs=["output"],
)

data = np.array([[0, 1], [2, 3]], dtype=np.int32)
indices = np.array([[0, 0], [1, 1]], dtype=np.int64)
output = gather_nd_impl(data, indices, 0)
expected_output = np.array([0, 3], dtype=np.int32)
assert np.array_equal(output, expected_output)
expect(
    node,
    inputs=[data, indices],
    outputs=[output],
    name="test_gathernd_example_int32",
)

_float32

node = onnx.helper.make_node(
    "GatherND",
    inputs=["data", "indices"],
    outputs=["output"],
)

data = np.array([[[0, 1], [2, 3]], [[4, 5], [6, 7]]], dtype=np.float32)
indices = np.array([[[0, 1]], [[1, 0]]], dtype=np.int64)
output = gather_nd_impl(data, indices, 0)
expected_output = np.array([[[2, 3]], [[4, 5]]], dtype=np.float32)
assert np.array_equal(output, expected_output)
expect(
    node,
    inputs=[data, indices],
    outputs=[output],
    name="test_gathernd_example_float32",
)

_int32_batchdim_1

node = onnx.helper.make_node(
    "GatherND",
    inputs=["data", "indices"],
    outputs=["output"],
    batch_dims=1,
)

data = np.array([[[0, 1], [2, 3]], [[4, 5], [6, 7]]], dtype=np.int32)
indices = np.array([[1], [0]], dtype=np.int64)
output = gather_nd_impl(data, indices, 1)
expected_output = np.array([[2, 3], [4, 5]], dtype=np.int32)
assert np.array_equal(output, expected_output)
expect(
    node,
    inputs=[data, indices],
    outputs=[output],
    name="test_gathernd_example_int32_batch_dim1",
)