| from __future__ import absolute_import
|
|
|
| import copy
|
|
|
| from . import (ExprNodes, PyrexTypes, MemoryView,
|
| ParseTreeTransforms, StringEncoding, Errors,
|
| Naming)
|
| from .ExprNodes import CloneNode, ProxyNode, TupleNode
|
| from .Nodes import FuncDefNode, CFuncDefNode, StatListNode, DefNode
|
| from ..Utils import OrderedSet
|
| from .Errors import error, CannotSpecialize
|
|
|
|
|
| class FusedCFuncDefNode(StatListNode):
|
| """
|
| This node replaces a function with fused arguments. It deep-copies the
|
| function for every permutation of fused types, and allocates a new local
|
| scope for it. It keeps track of the original function in self.node, and
|
| the entry of the original function in the symbol table is given the
|
| 'fused_cfunction' attribute which points back to us.
|
| Then when a function lookup occurs (to e.g. call it), the call can be
|
| dispatched to the right function.
|
|
|
| node FuncDefNode the original function
|
| nodes [FuncDefNode] list of copies of node with different specific types
|
| py_func DefNode the fused python function subscriptable from
|
| Python space
|
| __signatures__ A DictNode mapping signature specialization strings
|
| to PyCFunction nodes
|
| resulting_fused_function PyCFunction for the fused DefNode that delegates
|
| to specializations
|
| fused_func_assignment Assignment of the fused function to the function name
|
| defaults_tuple TupleNode of defaults (letting PyCFunctionNode build
|
| defaults would result in many different tuples)
|
| specialized_pycfuncs List of synthesized pycfunction nodes for the
|
| specializations
|
| code_object CodeObjectNode shared by all specializations and the
|
| fused function
|
|
|
| fused_compound_types All fused (compound) types (e.g. floating[:])
|
| """
|
|
|
| __signatures__ = None
|
| resulting_fused_function = None
|
| fused_func_assignment = None
|
| defaults_tuple = None
|
| decorators = None
|
|
|
| child_attrs = StatListNode.child_attrs + [
|
| '__signatures__', 'resulting_fused_function', 'fused_func_assignment']
|
|
|
| def __init__(self, node, env):
|
| super(FusedCFuncDefNode, self).__init__(node.pos)
|
|
|
| self.nodes = []
|
| self.node = node
|
|
|
| is_def = isinstance(self.node, DefNode)
|
| if is_def:
|
|
|
| self.copy_def(env)
|
| else:
|
| self.copy_cdef(env)
|
|
|
|
|
| for n in self.nodes:
|
| assert not n.entry.type.is_fused
|
| assert not n.local_scope.return_type.is_fused
|
| if node.return_type.is_fused:
|
| assert not n.return_type.is_fused
|
|
|
| if not is_def and n.cfunc_declarator.optional_arg_count:
|
| assert n.type.op_arg_struct
|
|
|
| node.entry.fused_cfunction = self
|
|
|
|
|
|
|
| self.stats = self.nodes[:]
|
|
|
| def copy_def(self, env):
|
| """
|
| Create a copy of the original def or lambda function for specialized
|
| versions.
|
| """
|
| fused_compound_types = PyrexTypes.unique(
|
| [arg.type for arg in self.node.args if arg.type.is_fused])
|
| fused_types = self._get_fused_base_types(fused_compound_types)
|
| permutations = PyrexTypes.get_all_specialized_permutations(fused_types)
|
|
|
| self.fused_compound_types = fused_compound_types
|
|
|
| if self.node.entry in env.pyfunc_entries:
|
| env.pyfunc_entries.remove(self.node.entry)
|
|
|
| for cname, fused_to_specific in permutations:
|
| copied_node = copy.deepcopy(self.node)
|
|
|
| copied_node.entry.signature = self.node.entry.signature
|
|
|
| self._specialize_function_args(copied_node.args, fused_to_specific)
|
| copied_node.return_type = self.node.return_type.specialize(
|
| fused_to_specific)
|
|
|
| copied_node.analyse_declarations(env)
|
|
|
|
|
| self.create_new_local_scope(copied_node, env, fused_to_specific)
|
| self.specialize_copied_def(copied_node, cname, self.node.entry,
|
| fused_to_specific, fused_compound_types)
|
|
|
| PyrexTypes.specialize_entry(copied_node.entry, cname)
|
| copied_node.entry.used = True
|
| env.entries[copied_node.entry.name] = copied_node.entry
|
|
|
| if not self.replace_fused_typechecks(copied_node):
|
| break
|
|
|
| self.orig_py_func = self.node
|
| self.py_func = self.make_fused_cpdef(self.node, env, is_def=True)
|
|
|
| def copy_cdef(self, env):
|
| """
|
| Create a copy of the original c(p)def function for all specialized
|
| versions.
|
| """
|
| permutations = self.node.type.get_all_specialized_permutations()
|
|
|
|
|
|
|
|
|
|
|
| self.orig_py_func = orig_py_func = self.node.py_func
|
| self.node.py_func = None
|
| if orig_py_func:
|
| env.pyfunc_entries.remove(orig_py_func.entry)
|
|
|
| fused_types = self.node.type.get_fused_types()
|
| self.fused_compound_types = fused_types
|
|
|
| new_cfunc_entries = []
|
| for cname, fused_to_specific in permutations:
|
| copied_node = copy.deepcopy(self.node)
|
|
|
|
|
| try:
|
| type = copied_node.type.specialize(fused_to_specific)
|
| except CannotSpecialize:
|
|
|
| error(copied_node.pos, "Return type is a fused type that cannot "
|
| "be determined from the function arguments")
|
| self.py_func = None
|
| return
|
| entry = copied_node.entry
|
| type.specialize_entry(entry, cname)
|
|
|
|
|
| for i, orig_entry in enumerate(env.cfunc_entries):
|
| if entry.cname == orig_entry.cname and type.same_as_resolved_type(orig_entry.type):
|
| copied_node.entry = env.cfunc_entries[i]
|
| if not copied_node.entry.func_cname:
|
| copied_node.entry.func_cname = entry.func_cname
|
| entry = copied_node.entry
|
| type = entry.type
|
| break
|
| else:
|
| new_cfunc_entries.append(entry)
|
|
|
| copied_node.type = type
|
| entry.type, type.entry = type, entry
|
|
|
| entry.used = (entry.used or
|
| self.node.entry.defined_in_pxd or
|
| env.is_c_class_scope or
|
| entry.is_cmethod)
|
|
|
| if self.node.cfunc_declarator.optional_arg_count:
|
| self.node.cfunc_declarator.declare_optional_arg_struct(
|
| type, env, fused_cname=cname)
|
|
|
| copied_node.return_type = type.return_type
|
| self.create_new_local_scope(copied_node, env, fused_to_specific)
|
|
|
|
|
| self._specialize_function_args(copied_node.cfunc_declarator.args,
|
| fused_to_specific)
|
|
|
|
|
|
|
| copied_node.declare_cpdef_wrapper(env)
|
| if copied_node.py_func:
|
| env.pyfunc_entries.remove(copied_node.py_func.entry)
|
|
|
| self.specialize_copied_def(
|
| copied_node.py_func, cname, self.node.entry.as_variable,
|
| fused_to_specific, fused_types)
|
|
|
| if not self.replace_fused_typechecks(copied_node):
|
| break
|
|
|
|
|
| if self.node.entry in env.cfunc_entries:
|
| cindex = env.cfunc_entries.index(self.node.entry)
|
| env.cfunc_entries[cindex:cindex+1] = new_cfunc_entries
|
| else:
|
| env.cfunc_entries.extend(new_cfunc_entries)
|
|
|
| if orig_py_func:
|
| self.py_func = self.make_fused_cpdef(orig_py_func, env,
|
| is_def=False)
|
| else:
|
| self.py_func = orig_py_func
|
|
|
| def _get_fused_base_types(self, fused_compound_types):
|
| """
|
| Get a list of unique basic fused types, from a list of
|
| (possibly) compound fused types.
|
| """
|
| base_types = []
|
| seen = set()
|
| for fused_type in fused_compound_types:
|
| fused_type.get_fused_types(result=base_types, seen=seen)
|
| return base_types
|
|
|
| def _specialize_function_args(self, args, fused_to_specific):
|
| for arg in args:
|
| if arg.type.is_fused:
|
| arg.type = arg.type.specialize(fused_to_specific)
|
| if arg.type.is_memoryviewslice:
|
| arg.type.validate_memslice_dtype(arg.pos)
|
| if arg.annotation:
|
|
|
|
|
| arg.annotation.untyped = True
|
|
|
| def create_new_local_scope(self, node, env, f2s):
|
| """
|
| Create a new local scope for the copied node and append it to
|
| self.nodes. A new local scope is needed because the arguments with the
|
| fused types are already in the local scope, and we need the specialized
|
| entries created after analyse_declarations on each specialized version
|
| of the (CFunc)DefNode.
|
| f2s is a dict mapping each fused type to its specialized version
|
| """
|
| node.create_local_scope(env)
|
| node.local_scope.fused_to_specific = f2s
|
|
|
|
|
|
|
| node.has_fused_arguments = False
|
| self.nodes.append(node)
|
|
|
| def specialize_copied_def(self, node, cname, py_entry, f2s, fused_compound_types):
|
| """Specialize the copy of a DefNode given the copied node,
|
| the specialization cname and the original DefNode entry"""
|
| fused_types = self._get_fused_base_types(fused_compound_types)
|
| type_strings = [
|
| PyrexTypes.specialization_signature_string(fused_type, f2s)
|
| for fused_type in fused_types
|
| ]
|
|
|
| node.specialized_signature_string = '|'.join(type_strings)
|
|
|
| node.entry.pymethdef_cname = PyrexTypes.get_fused_cname(
|
| cname, node.entry.pymethdef_cname)
|
| node.entry.doc = py_entry.doc
|
| node.entry.doc_cname = py_entry.doc_cname
|
|
|
| def replace_fused_typechecks(self, copied_node):
|
| """
|
| Branch-prune fused type checks like
|
|
|
| if fused_t is int:
|
| ...
|
|
|
| Returns whether an error was issued and whether we should stop in
|
| in order to prevent a flood of errors.
|
| """
|
| num_errors = Errors.get_errors_count()
|
| transform = ParseTreeTransforms.ReplaceFusedTypeChecks(
|
| copied_node.local_scope)
|
| transform(copied_node)
|
|
|
| if Errors.get_errors_count() > num_errors:
|
| return False
|
|
|
| return True
|
|
|
| def _fused_instance_checks(self, normal_types, pyx_code, env):
|
| """
|
| Generate Cython code for instance checks, matching an object to
|
| specialized types.
|
| """
|
| for specialized_type in normal_types:
|
|
|
| py_type_name = specialized_type.py_type_name()
|
| if py_type_name == 'int':
|
|
|
| py_type_name = '(int, long)'
|
| pyx_code.context.update(
|
| py_type_name=py_type_name,
|
| specialized_type_name=specialized_type.specialization_string,
|
| )
|
| pyx_code.put_chunk(
|
| u"""
|
| if isinstance(arg, {{py_type_name}}):
|
| dest_sig[{{dest_sig_idx}}] = '{{specialized_type_name}}'; break
|
| """)
|
|
|
| def _dtype_name(self, dtype):
|
| name = str(dtype).replace('_', '__').replace(' ', '_')
|
| if dtype.is_typedef:
|
| name = Naming.fused_dtype_prefix + name
|
| return name
|
|
|
| def _dtype_type(self, dtype):
|
| if dtype.is_typedef:
|
| return self._dtype_name(dtype)
|
| return str(dtype)
|
|
|
| def _sizeof_dtype(self, dtype):
|
| if dtype.is_pyobject:
|
| return 'sizeof(void *)'
|
| else:
|
| return "sizeof(%s)" % self._dtype_type(dtype)
|
|
|
| def _buffer_check_numpy_dtype_setup_cases(self, pyx_code):
|
| "Setup some common cases to match dtypes against specializations"
|
| with pyx_code.indenter("if kind in u'iu':"):
|
| pyx_code.putln("pass")
|
| pyx_code.named_insertion_point("dtype_int")
|
|
|
| with pyx_code.indenter("elif kind == u'f':"):
|
| pyx_code.putln("pass")
|
| pyx_code.named_insertion_point("dtype_float")
|
|
|
| with pyx_code.indenter("elif kind == u'c':"):
|
| pyx_code.putln("pass")
|
| pyx_code.named_insertion_point("dtype_complex")
|
|
|
| with pyx_code.indenter("elif kind == u'O':"):
|
| pyx_code.putln("pass")
|
| pyx_code.named_insertion_point("dtype_object")
|
|
|
| match = "dest_sig[{{dest_sig_idx}}] = '{{specialized_type_name}}'"
|
| no_match = "dest_sig[{{dest_sig_idx}}] = None"
|
| def _buffer_check_numpy_dtype(self, pyx_code, specialized_buffer_types, pythran_types):
|
| """
|
| Match a numpy dtype object to the individual specializations.
|
| """
|
| self._buffer_check_numpy_dtype_setup_cases(pyx_code)
|
|
|
| for specialized_type in pythran_types+specialized_buffer_types:
|
| final_type = specialized_type
|
| if specialized_type.is_pythran_expr:
|
| specialized_type = specialized_type.org_buffer
|
| dtype = specialized_type.dtype
|
| pyx_code.context.update(
|
| itemsize_match=self._sizeof_dtype(dtype) + " == itemsize",
|
| signed_match="not (%s_is_signed ^ dtype_signed)" % self._dtype_name(dtype),
|
| dtype=dtype,
|
| specialized_type_name=final_type.specialization_string)
|
|
|
| dtypes = [
|
| (dtype.is_int, pyx_code.dtype_int),
|
| (dtype.is_float, pyx_code.dtype_float),
|
| (dtype.is_complex, pyx_code.dtype_complex)
|
| ]
|
|
|
| for dtype_category, codewriter in dtypes:
|
| if not dtype_category:
|
| continue
|
| cond = '{{itemsize_match}} and (<Py_ssize_t>arg.ndim) == %d' % (
|
| specialized_type.ndim,)
|
| if dtype.is_int:
|
| cond += ' and {{signed_match}}'
|
|
|
| if final_type.is_pythran_expr:
|
| cond += ' and arg_is_pythran_compatible'
|
|
|
| with codewriter.indenter("if %s:" % cond):
|
|
|
| codewriter.putln(self.match)
|
| codewriter.putln("break")
|
|
|
| def _buffer_parse_format_string_check(self, pyx_code, decl_code,
|
| specialized_type, env):
|
| """
|
| For each specialized type, try to coerce the object to a memoryview
|
| slice of that type. This means obtaining a buffer and parsing the
|
| format string.
|
| TODO: separate buffer acquisition from format parsing
|
| """
|
| dtype = specialized_type.dtype
|
| if specialized_type.is_buffer:
|
| axes = [('direct', 'strided')] * specialized_type.ndim
|
| else:
|
| axes = specialized_type.axes
|
|
|
| memslice_type = PyrexTypes.MemoryViewSliceType(dtype, axes)
|
| memslice_type.create_from_py_utility_code(env)
|
| pyx_code.context.update(
|
| coerce_from_py_func=memslice_type.from_py_function,
|
| dtype=dtype)
|
| decl_code.putln(
|
| "{{memviewslice_cname}} {{coerce_from_py_func}}(object, int)")
|
|
|
| pyx_code.context.update(
|
| specialized_type_name=specialized_type.specialization_string,
|
| sizeof_dtype=self._sizeof_dtype(dtype),
|
| ndim_dtype=specialized_type.ndim,
|
| dtype_is_struct_obj=int(dtype.is_struct or dtype.is_pyobject))
|
|
|
|
|
|
|
| pyx_code.put_chunk(
|
| u"""
|
| # try {{dtype}}
|
| if (((itemsize == -1 and arg_as_memoryview.itemsize == {{sizeof_dtype}})
|
| or itemsize == {{sizeof_dtype}})
|
| and arg_as_memoryview.ndim == {{ndim_dtype}}):
|
| {{if dtype_is_struct_obj}}
|
| if __PYX_IS_PYPY2:
|
| # I wasn't able to diagnose why, but PyPy2 fails to convert a
|
| # memoryview to a Cython memoryview in this case
|
| memslice = {{coerce_from_py_func}}(arg, 0)
|
| else:
|
| {{else}}
|
| if True:
|
| {{endif}}
|
| memslice = {{coerce_from_py_func}}(arg_as_memoryview, 0)
|
| if memslice.memview:
|
| __PYX_XCLEAR_MEMVIEW(&memslice, 1)
|
| # print 'found a match for the buffer through format parsing'
|
| %s
|
| break
|
| else:
|
| __pyx_PyErr_Clear()
|
| """ % self.match)
|
|
|
| def _buffer_checks(self, buffer_types, pythran_types, pyx_code, decl_code, accept_none, env):
|
| """
|
| Generate Cython code to match objects to buffer specializations.
|
| First try to get a numpy dtype object and match it against the individual
|
| specializations. If that fails, try naively to coerce the object
|
| to each specialization, which obtains the buffer each time and tries
|
| to match the format string.
|
| """
|
|
|
| pyx_code.put_chunk(
|
| u"""
|
| """ + (u"arg_is_pythran_compatible = False" if pythran_types else u"") + u"""
|
| if ndarray is not None:
|
| if isinstance(arg, ndarray):
|
| dtype = arg.dtype
|
| """ + (u"arg_is_pythran_compatible = True" if pythran_types else u"") + u"""
|
| elif __pyx_memoryview_check(arg):
|
| arg_base = arg.base
|
| if isinstance(arg_base, ndarray):
|
| dtype = arg_base.dtype
|
| else:
|
| dtype = None
|
| else:
|
| dtype = None
|
|
|
| itemsize = -1
|
| if dtype is not None:
|
| itemsize = dtype.itemsize
|
| kind = ord(dtype.kind)
|
| dtype_signed = kind == u'i'
|
| """)
|
| pyx_code.indent(2)
|
| if pythran_types:
|
| pyx_code.put_chunk(
|
| u"""
|
| # Pythran only supports the endianness of the current compiler
|
| byteorder = dtype.byteorder
|
| if byteorder == "<" and not __Pyx_Is_Little_Endian():
|
| arg_is_pythran_compatible = False
|
| elif byteorder == ">" and __Pyx_Is_Little_Endian():
|
| arg_is_pythran_compatible = False
|
| if arg_is_pythran_compatible:
|
| cur_stride = itemsize
|
| shape = arg.shape
|
| strides = arg.strides
|
| for i in range(arg.ndim-1, -1, -1):
|
| if (<Py_ssize_t>strides[i]) != cur_stride:
|
| arg_is_pythran_compatible = False
|
| break
|
| cur_stride *= <Py_ssize_t> shape[i]
|
| else:
|
| arg_is_pythran_compatible = not (arg.flags.f_contiguous and (<Py_ssize_t>arg.ndim) > 1)
|
| """)
|
| pyx_code.named_insertion_point("numpy_dtype_checks")
|
| self._buffer_check_numpy_dtype(pyx_code, buffer_types, pythran_types)
|
| pyx_code.dedent(2)
|
|
|
| if accept_none:
|
|
|
|
|
|
|
|
|
| pyx_code.context.update(
|
| specialized_type_name=buffer_types[0].specialization_string
|
| )
|
| pyx_code.put_chunk(
|
| """
|
| if arg is None:
|
| %s
|
| break
|
| """ % self.match)
|
|
|
|
|
|
|
|
|
| pyx_code.put_chunk(
|
| """
|
| try:
|
| arg_as_memoryview = memoryview(arg)
|
| except (ValueError, TypeError):
|
| pass
|
| """)
|
| with pyx_code.indenter("else:"):
|
| for specialized_type in buffer_types:
|
| self._buffer_parse_format_string_check(
|
| pyx_code, decl_code, specialized_type, env)
|
|
|
| def _buffer_declarations(self, pyx_code, decl_code, all_buffer_types, pythran_types):
|
| """
|
| If we have any buffer specializations, write out some variable
|
| declarations and imports.
|
| """
|
| decl_code.put_chunk(
|
| u"""
|
| ctypedef struct {{memviewslice_cname}}:
|
| void *memview
|
|
|
| void __PYX_XCLEAR_MEMVIEW({{memviewslice_cname}} *, int have_gil)
|
| bint __pyx_memoryview_check(object)
|
| bint __PYX_IS_PYPY2 "(CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION == 2)"
|
| """)
|
|
|
| pyx_code.local_variable_declarations.put_chunk(
|
| u"""
|
| cdef {{memviewslice_cname}} memslice
|
| cdef Py_ssize_t itemsize
|
| cdef bint dtype_signed
|
| cdef Py_UCS4 kind
|
|
|
| itemsize = -1
|
| """)
|
|
|
| if pythran_types:
|
| pyx_code.local_variable_declarations.put_chunk(u"""
|
| cdef bint arg_is_pythran_compatible
|
| cdef Py_ssize_t cur_stride
|
| """)
|
|
|
| pyx_code.imports.put_chunk(
|
| u"""
|
| cdef type ndarray
|
| ndarray = __Pyx_ImportNumPyArrayTypeIfAvailable()
|
| """)
|
|
|
| pyx_code.imports.put_chunk(
|
| u"""
|
| cdef memoryview arg_as_memoryview
|
| """
|
| )
|
|
|
| seen_typedefs = set()
|
| seen_int_dtypes = set()
|
| for buffer_type in all_buffer_types:
|
| dtype = buffer_type.dtype
|
| dtype_name = self._dtype_name(dtype)
|
| if dtype.is_typedef:
|
| if dtype_name not in seen_typedefs:
|
| seen_typedefs.add(dtype_name)
|
| decl_code.putln(
|
| 'ctypedef %s %s "%s"' % (dtype.resolve(), dtype_name,
|
| dtype.empty_declaration_code()))
|
|
|
| if buffer_type.dtype.is_int:
|
| if str(dtype) not in seen_int_dtypes:
|
| seen_int_dtypes.add(str(dtype))
|
| pyx_code.context.update(dtype_name=dtype_name,
|
| dtype_type=self._dtype_type(dtype))
|
| pyx_code.local_variable_declarations.put_chunk(
|
| u"""
|
| cdef bint {{dtype_name}}_is_signed
|
| {{dtype_name}}_is_signed = not (<{{dtype_type}}> -1 > 0)
|
| """)
|
|
|
| def _split_fused_types(self, arg):
|
| """
|
| Specialize fused types and split into normal types and buffer types.
|
| """
|
| specialized_types = PyrexTypes.get_specialized_types(arg.type)
|
|
|
|
|
| specialized_types.sort()
|
|
|
| seen_py_type_names = set()
|
| normal_types, buffer_types, pythran_types = [], [], []
|
| has_object_fallback = False
|
| for specialized_type in specialized_types:
|
| py_type_name = specialized_type.py_type_name()
|
| if py_type_name:
|
| if py_type_name in seen_py_type_names:
|
| continue
|
| seen_py_type_names.add(py_type_name)
|
| if py_type_name == 'object':
|
| has_object_fallback = True
|
| else:
|
| normal_types.append(specialized_type)
|
| elif specialized_type.is_pythran_expr:
|
| pythran_types.append(specialized_type)
|
| elif specialized_type.is_buffer or specialized_type.is_memoryviewslice:
|
| buffer_types.append(specialized_type)
|
|
|
| return normal_types, buffer_types, pythran_types, has_object_fallback
|
|
|
| def _unpack_argument(self, pyx_code):
|
| pyx_code.put_chunk(
|
| u"""
|
| # PROCESSING ARGUMENT {{arg_tuple_idx}}
|
| if {{arg_tuple_idx}} < len(<tuple>args):
|
| arg = (<tuple>args)[{{arg_tuple_idx}}]
|
| elif kwargs is not None and '{{arg.name}}' in <dict>kwargs:
|
| arg = (<dict>kwargs)['{{arg.name}}']
|
| else:
|
| {{if arg.default}}
|
| arg = (<tuple>defaults)[{{default_idx}}]
|
| {{else}}
|
| {{if arg_tuple_idx < min_positional_args}}
|
| raise TypeError("Expected at least %d argument%s, got %d" % (
|
| {{min_positional_args}}, {{'"s"' if min_positional_args != 1 else '""'}}, len(<tuple>args)))
|
| {{else}}
|
| raise TypeError("Missing keyword-only argument: '%s'" % "{{arg.default}}")
|
| {{endif}}
|
| {{endif}}
|
| """)
|
|
|
| def _fused_signature_index(self, pyx_code):
|
| """
|
| Generate Cython code for constructing a persistent nested dictionary index of
|
| fused type specialization signatures.
|
| """
|
| pyx_code.put_chunk(
|
| u"""
|
| if not _fused_sigindex:
|
| for sig in <dict> signatures:
|
| sigindex_node = <dict> _fused_sigindex
|
| *sig_series, last_type = sig.strip('()').split('|')
|
| for sig_type in sig_series:
|
| if sig_type not in sigindex_node:
|
| sigindex_node[sig_type] = sigindex_node = {}
|
| else:
|
| sigindex_node = <dict> sigindex_node[sig_type]
|
| sigindex_node[last_type] = sig
|
| """
|
| )
|
|
|
| def make_fused_cpdef(self, orig_py_func, env, is_def):
|
| """
|
| This creates the function that is indexable from Python and does
|
| runtime dispatch based on the argument types. The function gets the
|
| arg tuple and kwargs dict (or None) and the defaults tuple
|
| as arguments from the Binding Fused Function's tp_call.
|
| """
|
| from . import TreeFragment, Code, UtilityCode
|
|
|
| fused_types = self._get_fused_base_types([
|
| arg.type for arg in self.node.args if arg.type.is_fused])
|
|
|
| context = {
|
| 'memviewslice_cname': MemoryView.memviewslice_cname,
|
| 'func_args': self.node.args,
|
| 'n_fused': len(fused_types),
|
| 'min_positional_args':
|
| self.node.num_required_args - self.node.num_required_kw_args
|
| if is_def else
|
| sum(1 for arg in self.node.args if arg.default is None),
|
| 'name': orig_py_func.entry.name,
|
| }
|
|
|
| pyx_code = Code.PyxCodeWriter(context=context)
|
| decl_code = Code.PyxCodeWriter(context=context)
|
| decl_code.put_chunk(
|
| u"""
|
| cdef extern from *:
|
| void __pyx_PyErr_Clear "PyErr_Clear" ()
|
| type __Pyx_ImportNumPyArrayTypeIfAvailable()
|
| int __Pyx_Is_Little_Endian()
|
| """)
|
| decl_code.indent()
|
|
|
| pyx_code.put_chunk(
|
| u"""
|
| def __pyx_fused_cpdef(signatures, args, kwargs, defaults, _fused_sigindex={}):
|
| # FIXME: use a typed signature - currently fails badly because
|
| # default arguments inherit the types we specify here!
|
|
|
| cdef list search_list
|
| cdef dict sigindex_node
|
|
|
| dest_sig = [None] * {{n_fused}}
|
|
|
| if kwargs is not None and not kwargs:
|
| kwargs = None
|
|
|
| cdef Py_ssize_t i
|
|
|
| # instance check body
|
| """)
|
|
|
| pyx_code.indent()
|
| pyx_code.named_insertion_point("imports")
|
| pyx_code.named_insertion_point("func_defs")
|
| pyx_code.named_insertion_point("local_variable_declarations")
|
|
|
| fused_index = 0
|
| default_idx = 0
|
| all_buffer_types = OrderedSet()
|
| seen_fused_types = set()
|
| for i, arg in enumerate(self.node.args):
|
| if arg.type.is_fused:
|
| arg_fused_types = arg.type.get_fused_types()
|
| if len(arg_fused_types) > 1:
|
| raise NotImplementedError("Determination of more than one fused base "
|
| "type per argument is not implemented.")
|
| fused_type = arg_fused_types[0]
|
|
|
| if arg.type.is_fused and fused_type not in seen_fused_types:
|
| seen_fused_types.add(fused_type)
|
|
|
| context.update(
|
| arg_tuple_idx=i,
|
| arg=arg,
|
| dest_sig_idx=fused_index,
|
| default_idx=default_idx,
|
| )
|
|
|
| normal_types, buffer_types, pythran_types, has_object_fallback = self._split_fused_types(arg)
|
| self._unpack_argument(pyx_code)
|
|
|
|
|
| with pyx_code.indenter("while 1:"):
|
| if normal_types:
|
| self._fused_instance_checks(normal_types, pyx_code, env)
|
| if buffer_types or pythran_types:
|
| env.use_utility_code(Code.UtilityCode.load_cached("IsLittleEndian", "ModuleSetupCode.c"))
|
| self._buffer_checks(
|
| buffer_types, pythran_types, pyx_code, decl_code,
|
| arg.accept_none, env)
|
| if has_object_fallback:
|
| pyx_code.context.update(specialized_type_name='object')
|
| pyx_code.putln(self.match)
|
| else:
|
| pyx_code.putln(self.no_match)
|
| pyx_code.putln("break")
|
|
|
| fused_index += 1
|
| all_buffer_types.update(buffer_types)
|
| all_buffer_types.update(ty.org_buffer for ty in pythran_types)
|
|
|
| if arg.default:
|
| default_idx += 1
|
|
|
| if all_buffer_types:
|
| self._buffer_declarations(pyx_code, decl_code, all_buffer_types, pythran_types)
|
| env.use_utility_code(Code.UtilityCode.load_cached("Import", "ImportExport.c"))
|
| env.use_utility_code(Code.UtilityCode.load_cached("ImportNumPyArray", "ImportExport.c"))
|
|
|
| self._fused_signature_index(pyx_code)
|
|
|
| pyx_code.put_chunk(
|
| u"""
|
| sigindex_matches = []
|
| sigindex_candidates = [_fused_sigindex]
|
|
|
| for dst_type in dest_sig:
|
| found_matches = []
|
| found_candidates = []
|
| # Make two separate lists: One for signature sub-trees
|
| # with at least one definite match, and another for
|
| # signature sub-trees with only ambiguous matches
|
| # (where `dest_sig[i] is None`).
|
| if dst_type is None:
|
| for sn in sigindex_matches:
|
| found_matches.extend((<dict> sn).values())
|
| for sn in sigindex_candidates:
|
| found_candidates.extend((<dict> sn).values())
|
| else:
|
| for search_list in (sigindex_matches, sigindex_candidates):
|
| for sn in search_list:
|
| type_match = (<dict> sn).get(dst_type)
|
| if type_match is not None:
|
| found_matches.append(type_match)
|
| sigindex_matches = found_matches
|
| sigindex_candidates = found_candidates
|
| if not (found_matches or found_candidates):
|
| break
|
|
|
| candidates = sigindex_matches
|
|
|
| if not candidates:
|
| raise TypeError("No matching signature found")
|
| elif len(candidates) > 1:
|
| raise TypeError("Function call with ambiguous argument types")
|
| else:
|
| return (<dict>signatures)[candidates[0]]
|
| """)
|
|
|
| fragment_code = pyx_code.getvalue()
|
|
|
|
|
| from .Optimize import ConstantFolding
|
| fragment = TreeFragment.TreeFragment(
|
| fragment_code, level='module', pipeline=[ConstantFolding()])
|
| ast = TreeFragment.SetPosTransform(self.node.pos)(fragment.root)
|
| UtilityCode.declare_declarations_in_scope(
|
| decl_code.getvalue(), env.global_scope())
|
| ast.scope = env
|
|
|
| ast.analyse_declarations(env)
|
| py_func = ast.stats[-1]
|
| self.fragment_scope = ast.scope
|
|
|
| if isinstance(self.node, DefNode):
|
| py_func.specialized_cpdefs = self.nodes[:]
|
| else:
|
| py_func.specialized_cpdefs = [n.py_func for n in self.nodes]
|
|
|
| return py_func
|
|
|
| def update_fused_defnode_entry(self, env):
|
| copy_attributes = (
|
| 'name', 'pos', 'cname', 'func_cname', 'pyfunc_cname',
|
| 'pymethdef_cname', 'doc', 'doc_cname', 'is_member',
|
| 'scope'
|
| )
|
|
|
| entry = self.py_func.entry
|
|
|
| for attr in copy_attributes:
|
| setattr(entry, attr,
|
| getattr(self.orig_py_func.entry, attr))
|
|
|
| self.py_func.name = self.orig_py_func.name
|
| self.py_func.doc = self.orig_py_func.doc
|
|
|
| env.entries.pop('__pyx_fused_cpdef', None)
|
| if isinstance(self.node, DefNode):
|
| env.entries[entry.name] = entry
|
| else:
|
| env.entries[entry.name].as_variable = entry
|
|
|
| env.pyfunc_entries.append(entry)
|
|
|
| self.py_func.entry.fused_cfunction = self
|
| for node in self.nodes:
|
| if isinstance(self.node, DefNode):
|
| node.fused_py_func = self.py_func
|
| else:
|
| node.py_func.fused_py_func = self.py_func
|
| node.entry.as_variable = entry
|
|
|
| self.synthesize_defnodes()
|
| self.stats.append(self.__signatures__)
|
|
|
| def analyse_expressions(self, env):
|
| """
|
| Analyse the expressions. Take care to only evaluate default arguments
|
| once and clone the result for all specializations
|
| """
|
| for fused_compound_type in self.fused_compound_types:
|
| for fused_type in fused_compound_type.get_fused_types():
|
| for specialization_type in fused_type.types:
|
| if specialization_type.is_complex:
|
| specialization_type.create_declaration_utility_code(env)
|
|
|
| if self.py_func:
|
| self.__signatures__ = self.__signatures__.analyse_expressions(env)
|
| self.py_func = self.py_func.analyse_expressions(env)
|
| self.resulting_fused_function = self.resulting_fused_function.analyse_expressions(env)
|
| self.fused_func_assignment = self.fused_func_assignment.analyse_expressions(env)
|
|
|
| self.defaults = defaults = []
|
|
|
| for arg in self.node.args:
|
| if arg.default:
|
| arg.default = arg.default.analyse_expressions(env)
|
| if arg.default.is_literal:
|
| defaults.append(copy.copy(arg.default))
|
| else:
|
|
|
| defaults.append(ProxyNode(arg.default.coerce_to_temp(env)))
|
| else:
|
| defaults.append(None)
|
|
|
| for i, stat in enumerate(self.stats):
|
| stat = self.stats[i] = stat.analyse_expressions(env)
|
| if isinstance(stat, FuncDefNode) and stat is not self.py_func:
|
|
|
| for arg, default in zip(stat.args, defaults):
|
| if default is not None:
|
| if default.is_literal:
|
| arg.default = default.coerce_to(arg.type, env)
|
| else:
|
| arg.default = CloneNode(default).analyse_expressions(env).coerce_to(arg.type, env)
|
|
|
| if self.py_func:
|
| args = [CloneNode(default) for default in defaults if default]
|
| self.defaults_tuple = TupleNode(self.pos, args=args)
|
| self.defaults_tuple = self.defaults_tuple.analyse_types(env, skip_children=True).coerce_to_pyobject(env)
|
| self.defaults_tuple = ProxyNode(self.defaults_tuple)
|
| self.code_object = ProxyNode(self.specialized_pycfuncs[0].code_object)
|
|
|
| fused_func = self.resulting_fused_function.arg
|
| fused_func.defaults_tuple = CloneNode(self.defaults_tuple)
|
| fused_func.code_object = CloneNode(self.code_object)
|
|
|
| for i, pycfunc in enumerate(self.specialized_pycfuncs):
|
| pycfunc.code_object = CloneNode(self.code_object)
|
| pycfunc = self.specialized_pycfuncs[i] = pycfunc.analyse_types(env)
|
| pycfunc.defaults_tuple = CloneNode(self.defaults_tuple)
|
| return self
|
|
|
| def synthesize_defnodes(self):
|
| """
|
| Create the __signatures__ dict of PyCFunctionNode specializations.
|
| """
|
| if isinstance(self.nodes[0], CFuncDefNode):
|
| nodes = [node.py_func for node in self.nodes]
|
| else:
|
| nodes = self.nodes
|
|
|
|
|
| for node in nodes:
|
| node.entry.signature.use_fastcall = False
|
|
|
| signatures = [StringEncoding.EncodedString(node.specialized_signature_string)
|
| for node in nodes]
|
| keys = [ExprNodes.StringNode(node.pos, value=sig)
|
| for node, sig in zip(nodes, signatures)]
|
| values = [ExprNodes.PyCFunctionNode.from_defnode(node, binding=True)
|
| for node in nodes]
|
|
|
| self.__signatures__ = ExprNodes.DictNode.from_pairs(self.pos, zip(keys, values))
|
|
|
| self.specialized_pycfuncs = values
|
| for pycfuncnode in values:
|
| pycfuncnode.is_specialization = True
|
|
|
| def generate_function_definitions(self, env, code):
|
| if self.py_func:
|
| self.py_func.pymethdef_required = True
|
| self.fused_func_assignment.generate_function_definitions(env, code)
|
|
|
| from . import Options
|
| for stat in self.stats:
|
| if isinstance(stat, FuncDefNode) and (
|
| stat.entry.used or
|
| (Options.cimport_from_pyx and not stat.entry.visibility == 'extern')):
|
| code.mark_pos(stat.pos)
|
| stat.generate_function_definitions(env, code)
|
|
|
| def generate_execution_code(self, code):
|
|
|
|
|
| for default in self.defaults:
|
| if default is not None:
|
| default.generate_evaluation_code(code)
|
|
|
| if self.py_func:
|
| self.defaults_tuple.generate_evaluation_code(code)
|
| self.code_object.generate_evaluation_code(code)
|
|
|
| for stat in self.stats:
|
| code.mark_pos(stat.pos)
|
| if isinstance(stat, ExprNodes.ExprNode):
|
| stat.generate_evaluation_code(code)
|
| else:
|
| stat.generate_execution_code(code)
|
|
|
| if self.__signatures__:
|
| self.resulting_fused_function.generate_evaluation_code(code)
|
|
|
| code.putln(
|
| "((__pyx_FusedFunctionObject *) %s)->__signatures__ = %s;" %
|
| (self.resulting_fused_function.result(),
|
| self.__signatures__.result()))
|
| self.__signatures__.generate_giveref(code)
|
| self.__signatures__.generate_post_assignment_code(code)
|
| self.__signatures__.free_temps(code)
|
|
|
| self.fused_func_assignment.generate_execution_code(code)
|
|
|
|
|
| self.resulting_fused_function.generate_disposal_code(code)
|
| self.resulting_fused_function.free_temps(code)
|
| self.defaults_tuple.generate_disposal_code(code)
|
| self.defaults_tuple.free_temps(code)
|
| self.code_object.generate_disposal_code(code)
|
| self.code_object.free_temps(code)
|
|
|
| for default in self.defaults:
|
| if default is not None:
|
| default.generate_disposal_code(code)
|
| default.free_temps(code)
|
|
|
| def annotate(self, code):
|
| for stat in self.stats:
|
| stat.annotate(code)
|
|
|
