/
erfc.py
67 lines (51 loc) · 1.73 KB
/
erfc.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
import math
import warnings
import numpy
import chainer
from chainer.backends import cuda
from chainer import function_node
from chainer import utils
from chainer.utils import type_check
_erfc_cpu = None
class Erfc(function_node.FunctionNode):
@property
def label(self):
return 'erfc'
def check_type_forward(self, in_types):
type_check.expect(in_types.size() == 1)
type_check.expect(in_types[0].dtype.kind == 'f')
def forward_cpu(self, x):
global _erfc_cpu
if _erfc_cpu is None:
try:
from scipy import special
_erfc_cpu = special.erfc
except ImportError:
warnings.warn(
"SciPy is not available. Forward computation of erfc in"
" CPU can be slow without SciPy.")
_erfc_cpu = numpy.vectorize(math.erfc)
self.retain_inputs((0,))
return utils.force_array(_erfc_cpu(x[0]), dtype=x[0].dtype),
def forward_gpu(self, x):
self.retain_inputs((0,))
return cuda.elementwise(
'T x', 'T y',
'y = erfc(x)',
'elementwise_erfc',
)(x[0]),
def backward(self, indexes, gy):
x = self.get_retained_inputs()[0]
return -2 / numpy.pi ** 0.5 * chainer.functions.exp(-x ** 2) * gy[0],
def erfc(x):
"""Elementwise complementary error function.
.. note::
Forward computation in CPU can be slow if
`SciPy <https://www.scipy.org/>`_ is not available.
Args:
x (:class:`~chainer.Variable` or :class:`numpy.ndarray` or \
:class:`cupy.ndarray`): Input variable.
Returns:
~chainer.Variable: Output variable.
"""
return Erfc().apply((x,))[0]