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| ``mx.nd.scatter.nd`` |
| ======================================== |
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| Description |
| ---------------------- |
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| Scatters data into a new tensor according to indices. |
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| Given `data` with shape `(Y_0, ..., Y_{K-1}, X_M, ..., X_{N-1})` and indices with shape |
| `(M, Y_0, ..., Y_{K-1})`, the output will have shape `(X_0, X_1, ..., X_{N-1})`, |
| where `M <= N`. If `M == N`, data shape should simply be `(Y_0, ..., Y_{K-1})`. |
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| The elements in output is defined as follows:: |
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| output[indices[0, y_0, ..., y_{K-1}], |
| ..., |
| indices[M-1, y_0, ..., y_{K-1}], |
| x_M, ..., x_{N-1}] = data[y_0, ..., y_{K-1}, x_M, ..., x_{N-1}] |
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| all other entries in output are 0. |
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| .. warning:: |
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| If the indices have duplicates, the result will be non-deterministic and |
| the gradient of `scatter_nd` will not be correct!! |
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| **Example**:: |
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| data = [2, 3, 0] |
| indices = [[1, 1, 0], [0, 1, 0]] |
| shape = (2, 2) |
| scatter_nd(data, indices, shape) = [[0, 0], [2, 3]] |
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| data = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]] |
| indices = [[0, 1], [1, 1]] |
| shape = (2, 2, 2, 2) |
| scatter_nd(data, indices, shape) = [[[[0, 0], |
| [0, 0]], |
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| [[1, 2], |
| [3, 4]]], |
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| [[[0, 0], |
| [0, 0]], |
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| [[5, 6], |
| [7, 8]]]] |
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| Arguments |
| ------------------ |
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| +----------------------------------------+------------------------------------------------------------+ |
| | Argument | Description | |
| +========================================+============================================================+ |
| | ``data`` | NDArray-or-Symbol | |
| | | data | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``indices`` | NDArray-or-Symbol | |
| | | indices | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``shape`` | Shape(tuple), required. | |
| | | | |
| | | Shape of output. | |
| +----------------------------------------+------------------------------------------------------------+ |
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| Value |
| ---------- |
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| ``out`` The result mx.ndarray |
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