Projekt_AI-Automatyczny_saper/venv/Lib/site-packages/scipy/sparse/generate_sparsetools.py

427 lines
12 KiB
Python

"""
python generate_sparsetools.py
Generate manual wrappers for C++ sparsetools code.
Type codes used:
'i': integer scalar
'I': integer array
'T': data array
'B': boolean array
'V': std::vector<integer>*
'W': std::vector<data>*
'*': indicates that the next argument is an output argument
'v': void
'l': 64-bit integer scalar
See sparsetools.cxx for more details.
"""
import optparse
import os
from distutils.dep_util import newer
#
# List of all routines and their argument types.
#
# The first code indicates the return value, the rest the arguments.
#
# bsr.h
BSR_ROUTINES = """
bsr_diagonal v iiiiiIIT*T
bsr_tocsr v iiiiIIT*I*I*T
bsr_scale_rows v iiiiII*TT
bsr_scale_columns v iiiiII*TT
bsr_sort_indices v iiii*I*I*T
bsr_transpose v iiiiIIT*I*I*T
bsr_matmat v iiiiiiIITIIT*I*I*T
bsr_matvec v iiiiIITT*T
bsr_matvecs v iiiiiIITT*T
bsr_elmul_bsr v iiiiIITIIT*I*I*T
bsr_eldiv_bsr v iiiiIITIIT*I*I*T
bsr_plus_bsr v iiiiIITIIT*I*I*T
bsr_minus_bsr v iiiiIITIIT*I*I*T
bsr_maximum_bsr v iiiiIITIIT*I*I*T
bsr_minimum_bsr v iiiiIITIIT*I*I*T
bsr_ne_bsr v iiiiIITIIT*I*I*B
bsr_lt_bsr v iiiiIITIIT*I*I*B
bsr_gt_bsr v iiiiIITIIT*I*I*B
bsr_le_bsr v iiiiIITIIT*I*I*B
bsr_ge_bsr v iiiiIITIIT*I*I*B
"""
# csc.h
CSC_ROUTINES = """
csc_diagonal v iiiIIT*T
csc_tocsr v iiIIT*I*I*T
csc_matmat_maxnnz l iiIIII
csc_matmat v iiIITIIT*I*I*T
csc_matvec v iiIITT*T
csc_matvecs v iiiIITT*T
csc_elmul_csc v iiIITIIT*I*I*T
csc_eldiv_csc v iiIITIIT*I*I*T
csc_plus_csc v iiIITIIT*I*I*T
csc_minus_csc v iiIITIIT*I*I*T
csc_maximum_csc v iiIITIIT*I*I*T
csc_minimum_csc v iiIITIIT*I*I*T
csc_ne_csc v iiIITIIT*I*I*B
csc_lt_csc v iiIITIIT*I*I*B
csc_gt_csc v iiIITIIT*I*I*B
csc_le_csc v iiIITIIT*I*I*B
csc_ge_csc v iiIITIIT*I*I*B
"""
# csr.h
CSR_ROUTINES = """
csr_matmat_maxnnz l iiIIII
csr_matmat v iiIITIIT*I*I*T
csr_diagonal v iiiIIT*T
csr_tocsc v iiIIT*I*I*T
csr_tobsr v iiiiIIT*I*I*T
csr_todense v iiIIT*T
csr_matvec v iiIITT*T
csr_matvecs v iiiIITT*T
csr_elmul_csr v iiIITIIT*I*I*T
csr_eldiv_csr v iiIITIIT*I*I*T
csr_plus_csr v iiIITIIT*I*I*T
csr_minus_csr v iiIITIIT*I*I*T
csr_maximum_csr v iiIITIIT*I*I*T
csr_minimum_csr v iiIITIIT*I*I*T
csr_ne_csr v iiIITIIT*I*I*B
csr_lt_csr v iiIITIIT*I*I*B
csr_gt_csr v iiIITIIT*I*I*B
csr_le_csr v iiIITIIT*I*I*B
csr_ge_csr v iiIITIIT*I*I*B
csr_scale_rows v iiII*TT
csr_scale_columns v iiII*TT
csr_sort_indices v iI*I*T
csr_eliminate_zeros v ii*I*I*T
csr_sum_duplicates v ii*I*I*T
get_csr_submatrix v iiIITiiii*V*V*W
csr_row_index v iIIIT*I*T
csr_row_slice v iiiIIT*I*T
csr_column_index1 v iIiiII*I*I
csr_column_index2 v IIiIT*I*T
csr_sample_values v iiIITiII*T
csr_count_blocks i iiiiII
csr_sample_offsets i iiIIiII*I
expandptr v iI*I
test_throw_error i
csr_has_sorted_indices i iII
csr_has_canonical_format i iII
"""
# coo.h, dia.h, csgraph.h
OTHER_ROUTINES = """
coo_tocsr v iiiIIT*I*I*T
coo_todense v iilIIT*Ti
coo_matvec v lIITT*T
dia_matvec v iiiiITT*T
cs_graph_components i iII*I
"""
# List of compilation units
COMPILATION_UNITS = [
('bsr', BSR_ROUTINES),
('csr', CSR_ROUTINES),
('csc', CSC_ROUTINES),
('other', OTHER_ROUTINES),
]
#
# List of the supported index typenums and the corresponding C++ types
#
I_TYPES = [
('NPY_INT32', 'npy_int32'),
('NPY_INT64', 'npy_int64'),
]
#
# List of the supported data typenums and the corresponding C++ types
#
T_TYPES = [
('NPY_BOOL', 'npy_bool_wrapper'),
('NPY_BYTE', 'npy_byte'),
('NPY_UBYTE', 'npy_ubyte'),
('NPY_SHORT', 'npy_short'),
('NPY_USHORT', 'npy_ushort'),
('NPY_INT', 'npy_int'),
('NPY_UINT', 'npy_uint'),
('NPY_LONG', 'npy_long'),
('NPY_ULONG', 'npy_ulong'),
('NPY_LONGLONG', 'npy_longlong'),
('NPY_ULONGLONG', 'npy_ulonglong'),
('NPY_FLOAT', 'npy_float'),
('NPY_DOUBLE', 'npy_double'),
('NPY_LONGDOUBLE', 'npy_longdouble'),
('NPY_CFLOAT', 'npy_cfloat_wrapper'),
('NPY_CDOUBLE', 'npy_cdouble_wrapper'),
('NPY_CLONGDOUBLE', 'npy_clongdouble_wrapper'),
]
#
# Code templates
#
THUNK_TEMPLATE = """
static PY_LONG_LONG %(name)s_thunk(int I_typenum, int T_typenum, void **a)
{
%(thunk_content)s
}
"""
METHOD_TEMPLATE = """
NPY_VISIBILITY_HIDDEN PyObject *
%(name)s_method(PyObject *self, PyObject *args)
{
return call_thunk('%(ret_spec)s', "%(arg_spec)s", %(name)s_thunk, args);
}
"""
GET_THUNK_CASE_TEMPLATE = """
static int get_thunk_case(int I_typenum, int T_typenum)
{
%(content)s;
return -1;
}
"""
#
# Code generation
#
def get_thunk_type_set():
"""
Get a list containing cartesian product of data types, plus a getter routine.
Returns
-------
i_types : list [(j, I_typenum, None, I_type, None), ...]
Pairing of index type numbers and the corresponding C++ types,
and an unique index `j`. This is for routines that are parameterized
only by I but not by T.
it_types : list [(j, I_typenum, T_typenum, I_type, T_type), ...]
Same as `i_types`, but for routines parameterized both by T and I.
getter_code : str
C++ code for a function that takes I_typenum, T_typenum and returns
the unique index corresponding to the lists, or -1 if no match was
found.
"""
it_types = []
i_types = []
j = 0
getter_code = " if (0) {}"
for I_typenum, I_type in I_TYPES:
piece = """
else if (I_typenum == %(I_typenum)s) {
if (T_typenum == -1) { return %(j)s; }"""
getter_code += piece % dict(I_typenum=I_typenum, j=j)
i_types.append((j, I_typenum, None, I_type, None))
j += 1
for T_typenum, T_type in T_TYPES:
piece = """
else if (T_typenum == %(T_typenum)s) { return %(j)s; }"""
getter_code += piece % dict(T_typenum=T_typenum, j=j)
it_types.append((j, I_typenum, T_typenum, I_type, T_type))
j += 1
getter_code += """
}"""
return i_types, it_types, GET_THUNK_CASE_TEMPLATE % dict(content=getter_code)
def parse_routine(name, args, types):
"""
Generate thunk and method code for a given routine.
Parameters
----------
name : str
Name of the C++ routine
args : str
Argument list specification (in format explained above)
types : list
List of types to instantiate, as returned `get_thunk_type_set`
"""
ret_spec = args[0]
arg_spec = args[1:]
def get_arglist(I_type, T_type):
"""
Generate argument list for calling the C++ function
"""
args = []
next_is_writeable = False
j = 0
for t in arg_spec:
const = '' if next_is_writeable else 'const '
next_is_writeable = False
if t == '*':
next_is_writeable = True
continue
elif t == 'i':
args.append("*(%s*)a[%d]" % (const + I_type, j))
elif t == 'I':
args.append("(%s*)a[%d]" % (const + I_type, j))
elif t == 'T':
args.append("(%s*)a[%d]" % (const + T_type, j))
elif t == 'B':
args.append("(npy_bool_wrapper*)a[%d]" % (j,))
elif t == 'V':
if const:
raise ValueError("'V' argument must be an output arg")
args.append("(std::vector<%s>*)a[%d]" % (I_type, j,))
elif t == 'W':
if const:
raise ValueError("'W' argument must be an output arg")
args.append("(std::vector<%s>*)a[%d]" % (T_type, j,))
elif t == 'l':
args.append("*(%snpy_int64*)a[%d]" % (const, j))
else:
raise ValueError("Invalid spec character %r" % (t,))
j += 1
return ", ".join(args)
# Generate thunk code: a giant switch statement with different
# type combinations inside.
thunk_content = """int j = get_thunk_case(I_typenum, T_typenum);
switch (j) {"""
for j, I_typenum, T_typenum, I_type, T_type in types:
arglist = get_arglist(I_type, T_type)
piece = """
case %(j)s:"""
if ret_spec == 'v':
piece += """
(void)%(name)s(%(arglist)s);
return 0;"""
else:
piece += """
return %(name)s(%(arglist)s);"""
thunk_content += piece % dict(j=j, I_type=I_type, T_type=T_type,
I_typenum=I_typenum, T_typenum=T_typenum,
arglist=arglist, name=name)
thunk_content += """
default:
throw std::runtime_error("internal error: invalid argument typenums");
}"""
thunk_code = THUNK_TEMPLATE % dict(name=name,
thunk_content=thunk_content)
# Generate method code
method_code = METHOD_TEMPLATE % dict(name=name,
ret_spec=ret_spec,
arg_spec=arg_spec)
return thunk_code, method_code
def main():
p = optparse.OptionParser(usage=(__doc__ or '').strip())
p.add_option("--no-force", action="store_false",
dest="force", default=True)
options, args = p.parse_args()
names = []
i_types, it_types, getter_code = get_thunk_type_set()
# Generate *_impl.h for each compilation unit
for unit_name, routines in COMPILATION_UNITS:
thunks = []
methods = []
# Generate thunks and methods for all routines
for line in routines.splitlines():
line = line.strip()
if not line or line.startswith('#'):
continue
try:
name, args = line.split(None, 1)
except ValueError as e:
raise ValueError("Malformed line: %r" % (line,)) from e
args = "".join(args.split())
if 't' in args or 'T' in args:
thunk, method = parse_routine(name, args, it_types)
else:
thunk, method = parse_routine(name, args, i_types)
if name in names:
raise ValueError("Duplicate routine %r" % (name,))
names.append(name)
thunks.append(thunk)
methods.append(method)
# Produce output
dst = os.path.join(os.path.dirname(__file__),
'sparsetools',
unit_name + '_impl.h')
if newer(__file__, dst) or options.force:
print("[generate_sparsetools] generating %r" % (dst,))
with open(dst, 'w') as f:
write_autogen_blurb(f)
f.write(getter_code)
for thunk in thunks:
f.write(thunk)
for method in methods:
f.write(method)
else:
print("[generate_sparsetools] %r already up-to-date" % (dst,))
# Generate code for method struct
method_defs = ""
for name in names:
method_defs += "NPY_VISIBILITY_HIDDEN PyObject *%s_method(PyObject *, PyObject *);\n" % (name,)
method_struct = """\nstatic struct PyMethodDef sparsetools_methods[] = {"""
for name in names:
method_struct += """
{"%(name)s", (PyCFunction)%(name)s_method, METH_VARARGS, NULL},""" % dict(name=name)
method_struct += """
{NULL, NULL, 0, NULL}
};"""
# Produce sparsetools_impl.h
dst = os.path.join(os.path.dirname(__file__),
'sparsetools',
'sparsetools_impl.h')
if newer(__file__, dst) or options.force:
print("[generate_sparsetools] generating %r" % (dst,))
with open(dst, 'w') as f:
write_autogen_blurb(f)
f.write(method_defs)
f.write(method_struct)
else:
print("[generate_sparsetools] %r already up-to-date" % (dst,))
def write_autogen_blurb(stream):
stream.write("""\
/* This file is autogenerated by generate_sparsetools.py
* Do not edit manually or check into VCS.
*/
""")
if __name__ == "__main__":
main()