mxnet.ndarray.slice¶
-
mxnet.ndarray.
slice
(data=None, begin=_Null, end=_Null, step=_Null, out=None, name=None, **kwargs)¶ Slices a region of the array.
Note
crop
is deprecated. Useslice
instead.This function returns a sliced array between the indices given by begin and end with the corresponding step.
For an input array of
shape=(d_0, d_1, ..., d_n-1)
, slice operation withbegin=(b_0, b_1...b_m-1)
,end=(e_0, e_1, ..., e_m-1)
, andstep=(s_0, s_1, ..., s_m-1)
, where m <= n, results in an array with the shape(|e_0-b_0|/|s_0|, ..., |e_m-1-b_m-1|/|s_m-1|, d_m, ..., d_n-1)
.The resulting array’s k-th dimension contains elements from the k-th dimension of the input array starting from index
b_k
(inclusive) with steps_k
until reachinge_k
(exclusive).If the k-th elements are None in the sequence of begin, end, and step, the following rule will be used to set default values. If s_k is None, set s_k=1. If s_k > 0, set b_k=0, e_k=d_k; else, set b_k=d_k-1, e_k=-1.
The storage type of
slice
output depends on storage types of inputsslice(csr) = csr
otherwise,
slice
generates output with default storage
Note
When input data storage type is csr, it only supports step=(), or step=(None,), or step=(1,) to generate a csr output. For other step parameter values, it falls back to slicing a dense tensor.
Example:
x = [[ 1., 2., 3., 4.], [ 5., 6., 7., 8.], [ 9., 10., 11., 12.]] slice(x, begin=(0,1), end=(2,4)) = [[ 2., 3., 4.], [ 6., 7., 8.]] slice(x, begin=(None, 0), end=(None, 3), step=(-1, 2)) = [[9., 11.], [5., 7.], [1., 3.]]
Defined in src/operator/tensor/matrix_op.cc:L470
- Parameters
data (NDArray) – Source input
begin (Shape(tuple), required) – starting indices for the slice operation, supports negative indices.
end (Shape(tuple), required) – ending indices for the slice operation, supports negative indices.
step (Shape(tuple), optional, default=[]) – step for the slice operation, supports negative values.
out (NDArray, optional) – The output NDArray to hold the result.
- Returns
out – The output of this function.
- Return type
NDArray or list of NDArrays