/
internal.pyx
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/
internal.pyx
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# distutils: language = c++
cimport cpython
cimport cython
@cython.profile(False)
cpdef inline Py_ssize_t prod(args, Py_ssize_t init=1) except *:
cdef Py_ssize_t arg
for arg in args:
init *= arg
return init
@cython.profile(False)
cpdef inline Py_ssize_t prod_ssize_t(
vector.vector[Py_ssize_t]& arr, Py_ssize_t init=1):
cdef Py_ssize_t a
for a in arr:
init *= a
return init
@cython.profile(False)
cpdef inline tuple get_size(object size):
if size is None:
return ()
if cpython.PySequence_Check(size):
return tuple(size)
if isinstance(size, int):
return size,
raise ValueError('size should be None, collections.Sequence, or int')
@cython.profile(False)
cpdef inline bint vector_equal(
vector.vector[Py_ssize_t]& x, vector.vector[Py_ssize_t]& y):
cdef Py_ssize_t n = x.size()
if n != <Py_ssize_t>y.size():
return False
for i in range(n):
if x[i] != y[i]:
return False
return True
@cython.profile(False)
cdef void get_reduced_dims(
vector.vector[Py_ssize_t]& shape, vector.vector[Py_ssize_t]& strides,
Py_ssize_t itemsize, vector.vector[Py_ssize_t]& reduced_shape,
vector.vector[Py_ssize_t]& reduced_strides):
cdef vector.vector[Py_ssize_t] tmp_shape, tmp_strides
cdef Py_ssize_t i, ndim, sh, st, prev_st, index
ndim = shape.size()
reduced_shape.clear()
reduced_strides.clear()
if ndim == 0:
return
for i in range(ndim):
sh = shape[i]
if sh == 0:
reduced_shape.push_back(0)
reduced_strides.push_back(itemsize)
return
if sh != 1:
tmp_shape.push_back(sh)
tmp_strides.push_back(strides[i])
if tmp_shape.size() == 0:
return
reduced_shape.push_back(tmp_shape[0])
reduced_strides.push_back(tmp_strides[0])
index = 0
for i in range(<Py_ssize_t>tmp_shape.size() - 1):
sh = tmp_shape[i + 1]
st = tmp_strides[i + 1]
if tmp_strides[i] == sh * st:
reduced_shape[index] *= sh
reduced_strides[index] = st
else:
reduced_shape.push_back(sh)
reduced_strides.push_back(st)
index += 1
@cython.profile(False)
cpdef vector.vector[Py_ssize_t] get_contiguous_strides(
vector.vector[Py_ssize_t]& shape, Py_ssize_t itemsize,
bint is_c_contiguous) except *:
cdef vector.vector[Py_ssize_t] strides
cdef Py_ssize_t st, sh
cdef int i
cdef Py_ssize_t idx
strides.resize(shape.size(), 0)
st = itemsize
for i in range(<int>shape.size()):
if is_c_contiguous:
idx = shape.size() - 1 - i
else:
idx = i
strides[idx] = st
sh = shape[idx]
if sh > 1:
st *= sh
return strides
@cython.profile(False)
cpdef inline bint get_c_contiguity(
vector.vector[Py_ssize_t]& shape, vector.vector[Py_ssize_t]& strides,
Py_ssize_t itemsize) except *:
cdef vector.vector[Py_ssize_t] r_shape, r_strides
cpdef Py_ssize_t ndim
ndim = strides.size()
if ndim == 0 or (ndim == 1 and strides[0] == itemsize):
return True
get_reduced_dims(shape, strides, itemsize, r_shape, r_strides)
ndim = r_strides.size()
return ndim == 0 or (ndim == 1 and r_strides[0] == itemsize)
@cython.profile(False)
cpdef vector.vector[Py_ssize_t] infer_unknown_dimension(
vector.vector[Py_ssize_t]& shape, Py_ssize_t size) except *:
cdef vector.vector[Py_ssize_t] ret = shape
cdef Py_ssize_t cnt=0, index=-1, new_size=1
for i in range(shape.size()):
if shape[i] < 0:
cnt += 1
index = i
else:
new_size *= shape[i]
if cnt == 0:
return ret
if cnt > 1:
raise ValueError('can only specify only one unknown dimension')
if (size != 0 and new_size == 0) or size % new_size != 0:
raise ValueError('total size of new array must be unchanged')
ret[index] = size // new_size
return ret
@cython.profile(False)
cpdef inline Py_ssize_t _extract_slice_element(x) except *:
try:
return x.__index__()
except AttributeError:
return int(x)
@cython.profile(False)
cpdef slice complete_slice(slice slc, Py_ssize_t dim):
cpdef Py_ssize_t start=0, stop=0, step=0
cpdef bint start_none, stop_none
if slc.step is None:
step = 1
else:
try:
step = _extract_slice_element(slc.step)
except TypeError:
raise TypeError(
'slice.step must be int or None or have __index__ method: '
'{}'.format(slc))
if step == 0:
raise ValueError('Slice step must be nonzero.')
start_none = slc.start is None
if not start_none:
try:
start = _extract_slice_element(slc.start)
except TypeError:
raise TypeError(
'slice.start must be int or None or have __index__ method: '
'{}'.format(slc))
if start < 0:
start += dim
stop_none = slc.stop is None
if not stop_none:
try:
stop = _extract_slice_element(slc.stop)
except TypeError:
raise TypeError(
'slice.stop must be int or None or have __index__ method: '
'{}'.format(slc))
if stop < 0:
stop += dim
if step > 0:
start = 0 if start_none else max(0, min(dim, start))
stop = dim if stop_none else max(start, min(dim, stop))
else:
start = dim - 1 if start_none else max(-1, min(dim - 1, start))
stop = -1 if stop_none else max(-1, min(start, stop))
return slice(start, stop, step)
@cython.profile(False)
cpdef tuple complete_slice_list(list slice_list, Py_ssize_t ndim):
cdef Py_ssize_t i, n_newaxes, n_ellipses, ellipsis, n
slice_list = list(slice_list) # copy list
# Expand ellipsis into empty slices
ellipsis = -1
n_newaxes = n_ellipses = 0
for i, s in enumerate(slice_list):
if s is None:
n_newaxes += 1
elif s is Ellipsis:
n_ellipses += 1
ellipsis = i
if n_ellipses > 1:
raise ValueError('Only one Ellipsis is allowed in index')
n = ndim - <Py_ssize_t>len(slice_list) + n_newaxes
if n_ellipses > 0:
slice_list[ellipsis:ellipsis + 1] = [slice(None)] * (n + 1)
elif n > 0:
slice_list += [slice(None)] * n
return slice_list, n_newaxes