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update doc description for tensorScatterUpdate to mention updating same position is nondeterministic

refined comments
tags/v1.2.0-rc1
Peilin Wang 4 years ago
parent
commit
45db8ff254
1 changed files with 16 additions and 2 deletions
  1. +16
    -2
      mindspore/ops/operations/array_ops.py

+ 16
- 2
mindspore/ops/operations/array_ops.py View File

@@ -3372,11 +3372,25 @@ class GatherNd(PrimitiveWithInfer):

class TensorScatterUpdate(PrimitiveWithInfer):
"""
Updates tensor values using given values, along with the input indices.
Creates a new tensor by updating the positions in `input_x` indicicated by
`indices`, with values from `update`. This operation is almost equivalent to using
ScatterNd, except that the updates are applied on `input_x` instead of a zero tensor.

`indices` must have rank atleast 2, the last axis is the depth of each index
vectors. For each index vector, there must be a corresponding value in `update`. If
the depth of each index tensor matches the rank of `input_x`, then each index
vector corresponds to a scalar in `input_x` and each update updates a scalar. If
the depth of each index tensor is less than the rnak of `input_x`, then each index
vector corresponds to a slice in `input_x`, and each update updates a slice.
The order in which updates are applied is nondeterministic, meaning that if there
are multiple index vectors in `indices` that correspond to the same position, the
value of that position in the output will be nondeterministic.

Inputs:
- **input_x** (Tensor) - The target tensor. The dimension of input_x must be no less than indices.shape[-1].
- **indices** (Tensor) - The index of input tensor whose data type is int32 or int64.
The rank must be atleast 2.
- **update** (Tensor) - The tensor to update the input tensor, has the same type as input,
and update.shape = indices.shape[:-1] + input_x.shape[indices.shape[-1]:].

@@ -3388,7 +3402,7 @@ class TensorScatterUpdate(PrimitiveWithInfer):
ValueError: If length of shape of `input_x` is less than the last dimension of shape of `indices`.

Supported Platforms:
``Ascend``
``Ascend`` ``GPU``

Examples:
>>> input_x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mindspore.float32)


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