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!13845 Update API documentation of MatrixDiag, ScatterND and NMSWithMask 

From: @yuyiyang_3418
Reviewed-by: @liangchenghui,@wuxuejian
Signed-off-by: @liangchenghui
This commit is contained in:
mindspore-ci-bot 2021-03-24 15:52:30 +08:00 committed by Gitee
parent d926e8e4f4 e4cca000cc
commit e4be751742
3 changed files with 23 additions and 12 deletions
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2
mindspore/nn/layer/basic.py
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@ -935,7 +935,7 @@ class MatrixDiag(Cell):
``Ascend``
Examples:
>>> x = Tensor(np.array([1, -1]), mstype.float32)
>>> x = Tensor(np.array([1, -1]), mindspore.float32)
>>> matrix_diag = nn.MatrixDiag()
>>> output = matrix_diag(x)
>>> print(output)

26
mindspore/ops/operations/array_ops.py
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@ -3558,15 +3558,25 @@ class ScatterNdUpdate(_ScatterNdOp):
``Ascend`` ``CPU``
Examples:
>>> np_x = np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]])
>>> input_x = mindspore.Parameter(Tensor(np_x, mindspore.float32), name="x")
>>> indices = Tensor(np.array([[0, 0], [1, 1]]), mindspore.int32)
>>> updates = Tensor(np.array([1.0, 2.2]), mindspore.float32)
>>> op = ops.ScatterNdUpdate()
>>> output = op(input_x, indices, updates)
>>> # Example 1: Scatter [9, 0, 7, 3] by indices [3, 4, 1, 8] in a 1-D tensor
>>> op = ops.ScatterNd()
>>> indices = Tensor(np.array([3, 4, 1, 8]), mindspore.int32)
>>> updates = Tensor(np.array([8, 9, 7, 3]), mindspore.int32)
>>> shape = (10, )
>>> output = op(indices, updates, shape)
>>> print(output)
[[ 1. 0.3 3.6]
[ 0.4 2.2 -3.2]]
[0 7 0 8 9 0 0 0 3 0]
>>> # Example 2: Scatter [3.2, 1.1] by indices [[0, 1], [1, 1]] in a 2-D tensor
>>> op = ops.ScatterNd()
>>> indices = Tensor(np.array([[0, 1], [1, 1]]), mindspore.int32)
>>> updates = Tensor(np.array([3.2, 1.1]), mindspore.float32)
>>> shape = (3, 3)
>>> output = op(indices, updates, shape)
>>> print(output)
[[0. 3.2 0. ]
[0. 1.1 0. ]
[0. 0. 0. ]]
"""
@prim_attr_register

7
mindspore/ops/operations/math_ops.py
View File

@ -3791,15 +3791,16 @@ class NMSWithMask(PrimitiveWithInfer):
``Ascend`` ``GPU``
Examples:
>>> bbox = np.array([[0.4, 0.2, 0.4, 0.3, 0.1], [0.4, 0.3, 0.6, 0.8, 0.7]])
>>> bbox = np.array([[100.0, 100.0, 50.0, 68.0, 0.63], [150.0, 75.0, 165.0, 115.0, 0.55],
[12.0, 190.0, 288.0, 200.0, 0.9], [28.0, 130.0, 106.0, 172.0, 0.3]])
>>> bbox[:, 2] += bbox[:, 0]
>>> bbox[:, 3] += bbox[:, 1]
>>> inputs = Tensor(bbox, mindspore.float32)
>>> nms = ops.NMSWithMask(0.5)
>>> nms = ops.NMSWithMask(0.1)
>>> output_boxes, indices, mask = nms(inputs)
>>> indices_np = indices.asnumpy()
>>> print(indices_np[mask.asnumpy()])
[0 1]
[0 1 2]
"""
@prim_attr_register