@@ -341,7 +341,7 @@ def __getitem__(self, key):
341341
342342 Parameters
343343 ----------
344- key : int or slice
344+ key : int or mxnet.ndarray.NDArray. slice
345345 Indexing key.
346346
347347 Examples
@@ -389,7 +389,7 @@ def __setitem__(self, key, value):
389389
390390 Parameters
391391 ----------
392- key : slice
392+ key : mxnet.ndarray.NDArray. slice
393393 The indexing key.
394394 value : NDArray or CSRNDArray or numpy.ndarray
395395 The value to set.
@@ -626,7 +626,7 @@ def __getitem__(self, key):
626626
627627 Parameters
628628 ----------
629- key : slice
629+ key : mxnet.ndarray.NDArray. slice
630630 Indexing key.
631631
632632 Examples
@@ -654,7 +654,7 @@ def __setitem__(self, key, value):
654654
655655 Parameters
656656 ----------
657- key : slice
657+ key : mxnet.ndarray.NDArray. slice
658658 The indexing key.
659659 value : NDArray or numpy.ndarray
660660 The value to set.
@@ -1025,28 +1025,28 @@ def row_sparse_array(arg1, shape=None, ctx=None, dtype=None):
10251025
10261026 - row_sparse_array(D):
10271027 to construct a RowSparseNDArray with a dense ndarray ``D``
1028- - **D** (*array_like*) - An object exposing the array interface, an object whose \
1029- `__array__` method returns an array, or any (nested) sequence.
1030- - **ctx** (*Context, optional*) - Device context \
1031- (default is the current default context).
1032- - **dtype** (*str or numpy.dtype, optional*) - The data type of the output array. \
1033- The default dtype is ``D.dtype`` if ``D`` is an NDArray or numpy.ndarray, \
1034- float32 otherwise.
1028+ - **D** (*array_like*) - An object exposing the array interface, an object whose \
1029+ `__array__` method returns an array, or any (nested) sequence.
1030+ - **ctx** (*Context, optional*) - Device context \
1031+ (default is the current default context).
1032+ - **dtype** (*str or numpy.dtype, optional*) - The data type of the output array. \
1033+ The default dtype is ``D.dtype`` if ``D`` is an NDArray or numpy.ndarray, \
1034+ float32 otherwise.
10351035
10361036 - row_sparse_array(S)
10371037 to construct a RowSparseNDArray with a sparse ndarray ``S``
1038- - **S** (*RowSparseNDArray*) - A sparse ndarray.
1039- - **ctx** (*Context, optional*) - Device context \
1040- (default is the current default context).
1041- - **dtype** (*str or numpy.dtype, optional*) - The data type of the output array. \
1042- The default dtype is ``S.dtype``.
1038+ - **S** (*RowSparseNDArray*) - A sparse ndarray.
1039+ - **ctx** (*Context, optional*) - Device context \
1040+ (default is the current default context).
1041+ - **dtype** (*str or numpy.dtype, optional*) - The data type of the output array. \
1042+ The default dtype is ``S.dtype``.
10431043
10441044 - row_sparse_array((D0, D1 .. Dn))
10451045 to construct an empty RowSparseNDArray with shape ``(D0, D1, ... Dn)``
1046- - **D0, D1 .. Dn** (*int*) - The shape of the ndarray
1047- - **ctx** (*Context, optional*) - Device context \
1048- (default is the current default context).
1049- - **dtype** (*str or numpy.dtype, optional*) - The data type of the output array. \
1046+ - **D0, D1 .. Dn** (*int*) - The shape of the ndarray
1047+ - **ctx** (*Context, optional*) - Device context \
1048+ (default is the current default context).
1049+ - **dtype** (*str or numpy.dtype, optional*) - The data type of the output array. \
10501050 The default dtype is float32.
10511051
10521052 - row_sparse_array((data, indices))
@@ -1057,35 +1057,35 @@ def row_sparse_array(arg1, shape=None, ctx=None, dtype=None):
10571057 represented by RowSparseNDArray ``rsp`` has \
10581058 ``dense[rsp.indices[i], :, :, :, ...] = rsp.data[i, :, :, :, ...]``
10591059 The row indices for are expected to be **sorted in ascending order.** \
1060- - **data** (*array_like*) - An object exposing the array interface, which \
1061- holds all the non-zero row slices of the array.
1062- - **indices** (*array_like*) - An object exposing the array interface, which \
1063- stores the row index for each row slice with non-zero elements.
1064- - **shape** (*tuple of int, optional*) - The shape of the array. The default \
1065- shape is inferred from the indices and indptr arrays.
1066- - **ctx** (*Context, optional*) - Device context \
1067- (default is the current default context).
1068- - **dtype** (*str or numpy.dtype, optional*) - The data type of the output array. \
1069- The default dtype is float32.
1060+ - **data** (*array_like*) - An object exposing the array interface, which \
1061+ holds all the non-zero row slices of the array.
1062+ - **indices** (*array_like*) - An object exposing the array interface, which \
1063+ stores the row index for each row slice with non-zero elements.
1064+ - **shape** (*tuple of int, optional*) - The shape of the array. The default \
1065+ shape is inferred from the indices and indptr arrays.
1066+ - **ctx** (*Context, optional*) - Device context \
1067+ (default is the current default context).
1068+ - **dtype** (*str or numpy.dtype, optional*) - The data type of the output array. \
1069+ The default dtype is float32.
10701070
10711071 Parameters
10721072 ----------
1073- arg1: NDArray, numpy.ndarray, RowSparseNDArray, tuple of int or tuple of array_like
1073+ arg1 : NDArray, numpy.ndarray, RowSparseNDArray, tuple of int or tuple of array_like
10741074 The argument to help instantiate the row sparse ndarray. See above for further details.
10751075 shape : tuple of int, optional
1076- The shape of the row sparse ndarray.
1076+ The shape of the row sparse ndarray. (Default value = None)
10771077 ctx : Context, optional
10781078 Device context (default is the current default context).
10791079 dtype : str or numpy.dtype, optional
1080- The data type of the output array.
1080+ The data type of the output array. (Default value = None)
10811081
10821082 Returns
10831083 -------
10841084 RowSparseNDArray
10851085 An `RowSparseNDArray` with the `row_sparse` storage representation.
10861086
1087- Example
1088- -------
1087+ Examples
1088+ --------
10891089 >>> a = mx.nd.sparse.row_sparse_array(([[1, 2], [3, 4]], [1, 4]), shape=(6, 2))
10901090 >>> a.asnumpy()
10911091 array([[ 0., 0.],
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