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fix histogram weights shape

This commit is contained in:
huangmengxi 2021-06-16 17:10:45 +08:00
parent e7e1e421bc
commit 9f48b0a347
1 changed files with 16 additions and 10 deletions
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26
mindspore/numpy/math_ops.py
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@ -4253,11 +4253,11 @@ def _get_sort_range(size):
def searchsorted(a, v, side='left', sorter=None):
"""
Finds indices where elements should be inserted to maintain order.
Finds the indices into a sorted array a such that, if the corresponding elements
in v were inserted before the indices, the order of a would be preserved.
Finds the indices into a sorted array `a` such that, if the corresponding elements
in `v` were inserted before the indices, the order of `a` would be preserved.
Args:
a (Union[int, float, bool, list, tuple, Tensor]): 1-D input array. If `sorter` is
a (Union[list, tuple, Tensor]): 1-D input array. If `sorter` is
None, then it must be sorted in ascending order, otherwise `sorter` must be
an array of indices that sort it.
v (Union[int, float, bool, list, tuple, Tensor]): Values to insert into `a`.
@ -4289,6 +4289,8 @@ def searchsorted(a, v, side='left', sorter=None):
if side not in ('left', 'right'):
_raise_value_error('invalid value for keyword "side"')
a = _to_tensor(a).astype(mstype.float32)
if F.rank(a) != 1:
_raise_value_error('`a` should be 1-D array')
v = _to_tensor(v)
shape = F.shape(v)
if sorter is not None:
@ -4671,13 +4673,17 @@ def histogram(a, bins=10, range=None, weights=None, density=False): # pylint: di
(Tensor(shape=[3], dtype=Float32, value= [1, 4, 1]),
Tensor(shape=[4], dtype=Int32, value= [0, 1, 2, 3]))
"""
a = _to_tensor(a).ravel()
a = _to_tensor(a)
if weights is not None:
weights = _to_tensor(weights)
if F.shape(a) != F.shape(weights):
_raise_value_error('weights should have the same shape as a')
weights = weights.ravel()
a = a.ravel()
bin_edges = histogram_bin_edges(a, bins, range, weights)
data_to_bins = searchsorted(bin_edges, a, 'right')
bin_size = _type_convert(int, bin_edges.size)
data_to_bins = where_(a == bin_edges[-1], _to_tensor(bin_size - 1), data_to_bins)
if weights is not None:
weights = _to_tensor(weights).ravel()
count = bincount(data_to_bins, weights, length=bin_size)[1:]
if count.size == 0:
return count, bin_edges
@ -5003,8 +5009,8 @@ def polyadd(a1, a2):
Numpy object poly1d is currently not supported.
Args:
a1 (Union[int, float, bool, list, tuple, Tensor): Input polynomial.
a2 (Union[int, float, bool, list, tuple, Tensor): Input polynomial.
a1 (Union[int, float, list, tuple, Tensor): Input polynomial.
a2 (Union[int, float, list, tuple, Tensor): Input polynomial.
Returns:
Tensor, the sum of the inputs.
@ -5039,8 +5045,8 @@ def polysub(a1, a2):
Numpy object poly1d is currently not supported.
Args:
a1 (Union[int, float, bool, list, tuple, Tensor): Minuend polynomial.
a2 (Union[int, float, bool, list, tuple, Tensor): Subtrahend polynomial.
a1 (Union[int, float, list, tuple, Tensor): Minuend polynomial.
a2 (Union[int, float, list, tuple, Tensor): Subtrahend polynomial.
Returns:
Tensor, the difference of the inputs.