def setUp(self):
if self.stream == 'null':
self.stream = cupy.cuda.Stream.null
elif self.stream == 'new':
self.stream = cupy.cuda.Stream()
self.my_sum = _core.ReductionKernel('T x', 'T out', 'x', 'a + b',
'out = a', '0', 'my_sum')
def getnnz(self, axis=None):
"""Returns the number of stored values, including explicit zeros.
Args:
axis: Not supported yet.
Returns:
int: The number of stored values.
"""
if axis is not None:
raise NotImplementedError(
'getnnz over an axis is not implemented for DIA format')
m, n = self.shape
nnz = _core.ReductionKernel(
'int32 offsets, int32 m, int32 n', 'int32 nnz',
'offsets > 0 ? min(m, n - offsets) : min(m + offsets, n)', 'a + b',
'nnz = a', '0', 'dia_nnz')(self.offsets, m, n)
return int(nnz)
import cupy
import cupyx.scipy.fft
from cupy import _core
from cupy._core import _routines_math as _math
from cupy._core import fusion
from cupy.lib import stride_tricks
import numpy
_dot_kernel = _core.ReductionKernel('T x1, T x2', 'T y', 'x1 * x2', 'a + b',
'y = a', '0', 'dot_product')
def _choose_conv_method(in1, in2, mode):
if in1.ndim != 1 or in2.ndim != 1:
raise NotImplementedError('Only 1d inputs are supported currently')
if in1.dtype.kind in 'bui' or in2.dtype.kind in 'bui':
return 'direct'
if _fftconv_faster(in1, in2, mode):
return 'fft'
return 'direct'
def _fftconv_faster(x, h, mode):
"""
.. seealso:: :func: `scipy.signal._signaltools._fftconv_faster`
data are repeated in the order that they are stored in memory.
.. seealso:: :func:`numpy.resize`
"""
if numpy.isscalar(a):
return cupy.full(new_shape, a)
a = cupy.asarray(a)
if a.size == 0:
return cupy.zeros(new_shape, dtype=a.dtype)
out = cupy.empty(new_shape, a.dtype)
_resize_kernel(a, a.size, out)
return out
_first_nonzero_krnl = _core.ReductionKernel('T data, int64 len', 'int64 y',
'data == T(0) ? len : _j',
'min(a, b)', 'y = a', 'len',
'first_nonzero')
def trim_zeros(filt, trim='fb'):
"""Trim the leading and/or trailing zeros from a 1-D array or sequence.
Returns the trimmed array
Args:
filt(cupy.ndarray): Input array
trim(str, optional):
'fb' default option trims the array from both sides.
'f' option trim zeros from front.
'b' option trim zeros from back.