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!41788 [assistant][ops]Add Diff 

Merge pull request !41788 from zy26/Diff
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i-robot 2022-12-08 06:25:53 +00:00 committed by Gitee
parent 27bef30b42 7d518ef07b
commit db4e6b9a22
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GPG Key ID: 173E9B9CA92EEF8F
3 changed files with 90 additions and 4 deletions
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1
mindspore/python/mindspore/ops/function/__init__.py
View File

@ -313,6 +313,7 @@ from .math_func import (
block_diag,
atleast_1d,
dstack,
diff,
atleast_2d,
cartesian_prod,
atleast_3d,

80
mindspore/python/mindspore/ops/function/math_func.py
View File

@ -5541,23 +5541,94 @@ def dstack(inputs):
[3. 6.]]]
"""
if not isinstance(inputs, (tuple, list)):
raise TypeError(f"For 'dstack', 'inputs' must be list or tuple of tensors, but got {type(inputs)}")
raise TypeError(f"For 'dstack', 'diff', 'inputs' must be list or tuple of tensors, but got {type(inputs)}")
if not inputs:
raise TypeError(f"For 'dstack', 'inputs' can not be empty.")
raise TypeError(f"For 'dstack', 'diff', 'inputs' can not be empty.")
trans_inputs = ()
for tensor in inputs:
if not isinstance(tensor, Tensor):
raise TypeError(f"For 'dstack', each elements of 'inputs' must be Tensor, but got {type(tensor)}")
raise TypeError(f"For 'dstack', 'diff', each elements of 'inputs' must be Tensor, but got {type(tensor)}")
if tensor.ndim <= 1:
tensor = _expand(tensor, 2)
if tensor.ndim == 2:
tensor = P.ExpandDims()(tensor, 2)
trans_inputs += (tensor,)
if not trans_inputs:
raise ValueError("For 'dstack', at least one tensor is needed to concatenate.")
raise ValueError("For 'dstack', 'diff', at least one tensor is needed to concatenate.")
return P.Concat(2)(trans_inputs)
def diff(x, n=1, axis=-1, prepend=None, append=None):
r"""
Calculates the n-th discrete difference along the given axis.
The first difference is given by :math:`out[i] = a[i+1] - a[i]` along the given axis,
higher differences are calculated by using `diff` iteratively.
Note:
Zero-shaped Tensor is not supported, a value error is raised if
an empty Tensor is encountered.
Args:
x (Tensor): Input tensor.
Full support for signed integers, partial support for floats and complex numbers
n (int, optional): The number of times values are differenced. If zero,
the input is returned as-is. Default: 1. Currently only 1 is supported.
axis (int, optional): The axis along which the difference is taken, default
is the last axis. Default: -1.
prepend (Tensor, optional): Values to prepend or append to a along
`axis` prior to performing the difference. Scalar values are expanded to
arrays with length 1 in the direction of `axis` and the shape of the input
array in along all other axes. Otherwise the dimension and shape must
match `x` except along `axis`. Default: None.
append (Tensor, optional): Values to prepend or append to a along
`axis` prior to performing the difference. Scalar values are expanded to
arrays with length 1 in the direction of `axis` and the shape of the input
array in along all other axes. Otherwise the dimension and shape must
match `x` except along `axis`. Default: None.
Returns:
Tensor, 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 `x`. This is the same
as the type of `x` in most cases.
Raises:
TypeError: If the data type of the elementes in 'x' is uint16, uint32 or uint64.
TypeError: If `x` is not a tensor.
TypeError: If the dimension 'x' is less than 1.
RuntimeError: If `n` is not 1.
Supported Platforms:
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> x = Tensor([1, 3, -1, 0, 4])
>>> out = ops.diff(x)
>>> print(out.asnumpy())
[ 2 -4 1 4]
"""
if not isinstance(x, Tensor):
raise TypeError(f"For 'diff', 'x' must be a tensor, but got {type(x)}")
if x.ndim < 1:
raise TypeError(f"For 'diff', the dimension 'x' must be at least 1, but got {x.ndim}")
if n != 1:
raise RuntimeError(f"For 'diff', 'n' must be 1, but got {n}")
if x.dtype in (mstype.uint16, mstype.uint32, mstype.uint64):
msg = f"For 'diff', the data type of the elements in 'x' cannot be uint16, uint32, uint64, but got {x.dtype}"
raise TypeError(msg)
if prepend is not None and append is not None:
x = ops.Concat(axis)((prepend, x, append))
elif append is not None:
x = ops.Concat(axis)((x, append))
elif prepend is not None:
x = ops.Concat(axis)((prepend, x))
a = [i for i in range(x.shape[axis])]
a1 = x.gather(Tensor(a[:-1]), axis)
a2 = x.gather(Tensor(a[1:]), axis)
return a2 - a1
def tril_indices(row, col, offset=0, dtype=mstype.int64):
r"""
Returns the indices of the lower triangular part of a row-by- col matrix in a 2-by-N Tensor,
@ -9138,6 +9209,7 @@ __all__ = [
'block_diag',
'atleast_1d',
'dstack',
'diff',
'atleast_2d',
'cartesian_prod',
'atleast_3d',

13
tests/ut/python/ops/test_math_ops.py
View File

@ -450,6 +450,15 @@ class DstackFunc(nn.Cell):
return self.dstack([x1, x2])
class DiffFunc(nn.Cell):
def __init__(self):
super(DiffFunc, self).__init__()
self.diff = ops.diff
def construct(self, x):
return self.diff(x)
class AtLeast2DFunc(nn.Cell):
def __init__(self):
super(AtLeast2DFunc, self).__init__()
@ -874,6 +883,10 @@ test_case_math_ops = [
'desc_inputs': [Tensor(np.array([1, 2, 3]), ms.float32),
Tensor(np.array([4, 5, 6]), ms.float32)]
}),
('Diff', {
'block': DiffFunc(),
'desc_inputs': [Tensor(np.array([1, 3, -1, 0, 4]), ms.int32)]
}),
('AtLeast2D', {
'block': AtLeast2DFunc(),
'desc_inputs': [Tensor(np.array([[1, 1, 1], [1, 1, 1]]), ms.float64),