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 Superseded by reCTBN.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