forked from mindspore-Ecosystem/mindspore
42 lines
1.5 KiB
ReStructuredText
42 lines
1.5 KiB
ReStructuredText
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mindspore.ops.Gather
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======================
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.. py:class:: mindspore.ops.Gather(*args, **kwargs)
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返回输入Tensor在指定 `axis` 上 `input_indices` 索引对应的元素组成的切片。
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**输入：**
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- **input_params** (Tensor) - 原始Tensor，shape为 :math:`(x_1, x_2, ..., x_R)` 。
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- **input_indices** (Tensor) - 要切片的索引Tensor，shape为 :math:`(y_1, y_2, ..., y_S)` 。指定原始Tensor中要切片的索引。其值必须在 `[0, input_param.shape[axis])` 范围内，该校验仅在CPU上生效。在Ascend和GPU上超出该范围时，对应的值会置为0。数据类型可以是int32或int64。
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- **axis** (int) - 指定要切片的维度索引。
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**输出：**
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Tensor，shape为 :math:`input\_params.shape[:axis] + input\_indices.shape + input\_params.shape[axis + 1:]` 。
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**异常：**
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- **TypeError** - `axis` 不是int。
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- **TypeError** - `input_params` 或 `input_indices` 不是Tensor。
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**支持平台：**
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``Ascend`` ``GPU`` ``CPU``
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**样例：**
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>>> input_params = Tensor(np.array([[1, 2, 7, 42], [3, 4, 54, 22], [2, 2, 55, 3]]), mindspore.float32)
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>>> input_indices = Tensor(np.array([1, 2]), mindspore.int32)
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>>> axis = 1
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>>> output = ops.Gather()(input_params, input_indices, axis)
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>>> print(output)
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[[ 2. 7.]
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[ 4. 54.]
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[ 2. 55.]]
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>>> axis = 0
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>>> output = ops.Gather()(input_params, input_indices, axis)
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>>> print(output)
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[[3. 4. 54. 22.]
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[2. 2. 55. 3.]]
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