mxnet.ndarray.NDArray.__getitem__¶
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NDArray.__getitem__(key)[source]¶ x.__getitem__(i) <=> x[i]
Returns a sliced view of this array if the elements fetched are contiguous in memory; otherwise, returns a newly created NDArray. This functions supports advanced indexing defined in the following reference with some restrictions.
If key is a list type, only a list of integers is supported, e.g. key=[1, 2] is supported, while not for key=[[1, 2]].
Ellipsis (…) and np.newaxis are not supported.
Boolean array indexing is not supported.
- Parameters
key (int, mxnet.ndarray.slice, list, np.ndarray, NDArray, or tuple of all previous types) – Indexing key.
Examples
>>> x = mx.nd.arange(0,6).reshape((2,3)) >>> x.asnumpy() array([[ 0., 1., 2.], [ 3., 4., 5.]], dtype=float32) >>> x[1].asnumpy() array([ 3., 4., 5.], dtype=float32) >>> y = x[0:1] >>> y[:] = 2 >>> x.asnumpy() array([[ 2., 2., 2.], [ 3., 4., 5.]], dtype=float32) >>> x = mx.nd.arange(0, 8, dtype='int32').reshape((2, 2, 2)) >>> x[[0, 1]] [[[0 1] [2 3]] [[4 5] [6 7]]] >>> x[1:, [0, 1]] [[[4 5] [6 7]]] >>> y = np.array([0, 1], dtype='int32') >>> x[1:, y] [[[4 5] [6 7]]] >>> y = mx.nd.array([0, 1], dtype='int32') >>> x[1:, y] [[[4 5] [6 7]]]