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fix typo and doc
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@hgt312
hgt312 committed Dec 6, 2019
1 parent ae472c2 commit 001842e
Showing 1 changed file with 30 additions and 30 deletions.
60 changes: 30 additions & 30 deletions python/mxnet/symbol/numpy/_symbol.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1028,7 +1028,7 @@ def ones(shape, dtype=_np.float32, order='C', ctx=None):
Returns
-------
out : ndarray
out : _Symbol
Array of ones with the given shape, dtype, and ctx.
"""
if order != 'C':
Expand Down Expand Up @@ -1270,7 +1270,7 @@ def divide(x1, x2, out=None, **kwargs):
_npi.rtrue_divide_scalar, out)


@set_module('mxnet.ndarray.numpy')
@set_module('mxnet.symbol.numpy')
def true_divide(x1, x2, out=None):
return _ufunc_helper(x1, x2, _npi.true_divide, _np.divide, _npi.true_divide_scalar,
_npi.rtrue_divide_scalar, out)
Expand Down Expand Up @@ -1302,19 +1302,19 @@ def lcm(x1, x2, out=None, **kwargs):
Parameters
----------
x1, x2 : ndarrays or scalar values
x1, x2 : _Symbols or scalar values
The arrays for computing lowest common multiple. If x1.shape != x2.shape,
they must be broadcastable to a common shape (which may be the shape of
one or the other).
out : ndarray or None, optional
out : _Symbol or None, optional
A location into which the result is stored. If provided, it must have a shape
that the inputs broadcast to. If not provided or None, a freshly-allocated array
is returned.
Returns
-------
y : ndarray or scalar
y : _Symbol or scalar
The lowest common multiple of the absolute value of the inputs
This is a scalar if both `x1` and `x2` are scalars.
Expand Down Expand Up @@ -1447,7 +1447,7 @@ def eye(N, M=None, k=0, dtype=_np.float32, **kwargs):
Returns
-------
I : ndarray of shape (N,M)
I : _Symbol of shape (N,M)
An array where all elements are equal to zero,
except for the k-th diagonal, whose values are equal to one.
"""
Expand Down Expand Up @@ -1778,7 +1778,7 @@ def cosh(x, out=None, **kwargs):
----------
x : _Symbol or scalar
Input array or scalar.
out : ndarray or None
out : _Symbol or None
Dummy parameter to keep the consistency with the ndarray counterpart.
Returns
Expand Down Expand Up @@ -2290,7 +2290,7 @@ def log2(x, out=None, **kwargs):
----------
x : _Symbol
Input values.
out : ndarray or None
out : _Symbol or None
A location into which the result is stored.
If provided, it must have the same shape and type as the input.
If not provided or None, a freshly-allocated array is returned.
Expand Down Expand Up @@ -2876,7 +2876,7 @@ def arange(start, stop=None, step=1, dtype=None, ctx=None):
Returns
-------
arange : ndarray
arange : _Symbol
Array of evenly spaced values.
For floating point arguments, the length of the result is
Expand Down Expand Up @@ -2907,7 +2907,7 @@ def split(ary, indices_or_sections, axis=0):
Parameters
----------
ary : ndarray
ary : _Symbol
Array to be divided into sub-arrays.
indices_or_sections : int or 1-D python tuple, list or set.
If `indices_or_sections` is an integer, N, the array will be divided
Expand All @@ -2926,7 +2926,7 @@ def split(ary, indices_or_sections, axis=0):
Returns
-------
sub-arrays : list of ndarrays
sub-arrays : _Symbol
A list of sub-arrays.
Raises
Expand All @@ -2948,7 +2948,7 @@ def split(ary, indices_or_sections, axis=0):


# pylint: disable=redefined-outer-name
@set_module('mxnet.ndarray.numpy')
@set_module('mxnet.symbol.numpy')
def hsplit(ary, indices_or_sections):
"""Split an array into multiple sub-arrays horizontally (column-wise).
Expand Down Expand Up @@ -3110,7 +3110,7 @@ def concatenate(seq, axis=0, out=None):
Parameters
----------
a1, a2, ... : sequence of array_like
a1, a2, ... : sequence of _Symbols
The arrays must have the same shape, except in the dimension
corresponding to `axis` (the first, by default).
axis : int, optional
Expand All @@ -3123,7 +3123,7 @@ def concatenate(seq, axis=0, out=None):
Returns
-------
res : ndarray
res : _Symbol
The concatenated array.
Examples
Expand Down Expand Up @@ -3152,9 +3152,9 @@ def append(arr, values, axis=None): # pylint: disable=redefined-outer-name
Parameters
----------
arr : ndarray
arr : _Symbol
Values are appended to a copy of this array.
values : ndarray
values : _Symbol
These values are appended to a copy of `arr`. It must be of the
correct shape (the same shape as `arr`, excluding `axis`). If
`axis` is not specified, `values` can be any shape and will be
Expand All @@ -3165,7 +3165,7 @@ def append(arr, values, axis=None): # pylint: disable=redefined-outer-name
Returns
-------
append : ndarray
append : _Symbol
A copy of `arr` with `values` appended to `axis`. Note that
`append` does not occur in-place: a new array is allocated and
filled. If `axis` is None, `out` is a flattened array.
Expand All @@ -3192,16 +3192,16 @@ def stack(arrays, axis=0, out=None):
For example, if `axis=0` it will be the first dimension and if `axis=-1` it will be the last dimension.
Parameters
----------
arrays : sequence of array_like
arrays : sequence of _Symbols
Each array must have the same shape.
axis : int, optional
The axis in the result array along which the input arrays are stacked.
out : ndarray, optional
out : _Symbol, optional
If provided, the destination to place the result. The shape must be correct,
matching that of what stack would have returned if no out argument were specified.
Returns
-------
stacked : ndarray
stacked : _Symbol
The stacked array has one more dimension than the input arrays."""
def get_list(arrays):
if not hasattr(arrays, '__getitem__') and hasattr(arrays, '__iter__'):
Expand Down Expand Up @@ -3744,15 +3744,15 @@ def ravel(x, order='C'):
Parameters
----------
x : ndarray
x : _Symbol
Input array. The elements in `x` are read in row-major, C-style order and
packed as a 1-D array.
order : `C`, optional
Only support row-major, C-style order.
Returns
-------
y : ndarray
y : _Symbol
y is an array of the same subtype as `x`, with shape ``(x.size,)``.
Note that matrices are special cased for backward compatibility, if `x`
is a matrix, then y is a 1-D ndarray.
Expand All @@ -3778,15 +3778,15 @@ def unravel_index(indices, shape, order='C'): # pylint: disable=redefined-outer-
Parameters:
-------------
indices : array_like
indices : _Symbol
An integer array whose elements are indices into the flattened version of an array of dimensions shape.
Before version 1.6.0, this function accepted just one index value.
shape : tuple of ints
The shape of the array to use for unraveling indices.
Returns:
-------------
unraveled_coords : ndarray
unraveled_coords : _Symbol
Each row in the ndarray has the same shape as the indices array.
Each column in the ndarray represents the unravelled index
Expand Down Expand Up @@ -4434,16 +4434,16 @@ def outer(a, b):
Parameters
----------
a : (M,) ndarray
a : (M,) _Symbol
First input vector. Input is flattened if
not already 1-dimensional.
b : (N,) ndarray
b : (N,) _Symbol
Second input vector. Input is flattened if
not already 1-dimensional.
Returns
-------
out : (M, N) ndarray
out : (M, N) _Symbol
``out[i, j] = a[i] * b[j]``
See also
Expand Down Expand Up @@ -4924,18 +4924,18 @@ def diff(a, n=1, axis=-1, prepend=None, append=None): # pylint: disable=redefin
Parameters
----------
a : ndarray
a : _Symbol
Input array
n : int, optional
The number of times values are differenced. If zero, the input is returned as-is.
axis : int, optional
The axis along which the difference is taken, default is the last axis.
prepend, append : ndarray, optional
prepend, append : _Symbol, optional
Not supported yet
Returns
-------
diff : ndarray
diff : _Symbol
The n-th differences.
The shape of the output is the same as a except along axis where the dimension is smaller by n.
The type of the output is the same as the type of the difference between any two elements of a.
Expand Down

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