forked from M-Labs/artiq
800 lines
34 KiB
Python
800 lines
34 KiB
Python
"""
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The :class:`Stitcher` class allows to transparently combine compiled
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Python code and Python code executed on the host system: it resolves
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the references to the host objects and translates the functions
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annotated as ``@kernel`` when they are referenced.
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"""
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import sys, os, re, linecache, inspect, textwrap
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from collections import OrderedDict, defaultdict
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from pythonparser import ast, algorithm, source, diagnostic, parse_buffer
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from pythonparser import lexer as source_lexer, parser as source_parser
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from Levenshtein import ratio as similarity, jaro_winkler
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from ..language import core as language_core
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from . import types, builtins, asttyped, prelude
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from .transforms import ASTTypedRewriter, Inferencer, IntMonomorphizer
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from .transforms.asttyped_rewriter import LocalExtractor
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def coredevice_print(x): print(x)
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class ObjectMap:
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def __init__(self):
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self.current_key = 0
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self.forward_map = {}
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self.reverse_map = {}
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def store(self, obj_ref):
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obj_id = id(obj_ref)
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if obj_id in self.reverse_map:
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return self.reverse_map[obj_id]
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self.current_key += 1
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self.forward_map[self.current_key] = obj_ref
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self.reverse_map[obj_id] = self.current_key
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return self.current_key
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def retrieve(self, obj_key):
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return self.forward_map[obj_key]
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def has_rpc(self):
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return any(filter(lambda x: inspect.isfunction(x) or inspect.ismethod(x),
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self.forward_map.values()))
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def __iter__(self):
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return iter(self.forward_map.keys())
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class ASTSynthesizer:
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def __init__(self, object_map, type_map, value_map, quote_function=None, expanded_from=None):
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self.source = ""
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self.source_buffer = source.Buffer(self.source, "<synthesized>")
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self.object_map, self.type_map, self.value_map = object_map, type_map, value_map
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self.quote_function = quote_function
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self.expanded_from = expanded_from
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def finalize(self):
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self.source_buffer.source = self.source
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return self.source_buffer
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def _add(self, fragment):
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range_from = len(self.source)
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self.source += fragment
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range_to = len(self.source)
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return source.Range(self.source_buffer, range_from, range_to,
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expanded_from=self.expanded_from)
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def quote(self, value):
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"""Construct an AST fragment equal to `value`."""
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if value is None:
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typ = builtins.TNone()
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return asttyped.NameConstantT(value=value, type=typ,
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loc=self._add(repr(value)))
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elif value is True or value is False:
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typ = builtins.TBool()
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return asttyped.NameConstantT(value=value, type=typ,
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loc=self._add(repr(value)))
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elif isinstance(value, (int, float)):
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if isinstance(value, int):
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typ = builtins.TInt()
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elif isinstance(value, float):
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typ = builtins.TFloat()
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return asttyped.NumT(n=value, ctx=None, type=typ,
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loc=self._add(repr(value)))
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elif isinstance(value, language_core.int):
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typ = builtins.TInt(width=types.TValue(value.width))
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return asttyped.NumT(n=int(value), ctx=None, type=typ,
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loc=self._add(repr(value)))
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elif isinstance(value, str):
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return asttyped.StrT(s=value, ctx=None, type=builtins.TStr(),
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loc=self._add(repr(value)))
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elif isinstance(value, list):
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begin_loc = self._add("[")
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elts = []
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for index, elt in enumerate(value):
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elts.append(self.quote(elt))
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if index < len(value) - 1:
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self._add(", ")
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end_loc = self._add("]")
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return asttyped.ListT(elts=elts, ctx=None, type=builtins.TList(),
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begin_loc=begin_loc, end_loc=end_loc,
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loc=begin_loc.join(end_loc))
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elif inspect.isfunction(value) or inspect.ismethod(value):
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quote_loc = self._add('`')
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repr_loc = self._add(repr(value))
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unquote_loc = self._add('`')
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loc = quote_loc.join(unquote_loc)
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function_type = self.quote_function(value, self.expanded_from)
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return asttyped.QuoteT(value=value, type=function_type, loc=loc)
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else:
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quote_loc = self._add('`')
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repr_loc = self._add(repr(value))
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unquote_loc = self._add('`')
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loc = quote_loc.join(unquote_loc)
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if isinstance(value, type):
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typ = value
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else:
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typ = type(value)
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if typ in self.type_map:
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instance_type, constructor_type = self.type_map[typ]
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else:
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if issubclass(typ, BaseException):
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if hasattr(typ, 'artiq_builtin'):
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exception_id = 0
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else:
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exception_id = self.object_map.store(typ)
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instance_type = builtins.TException("{}.{}".format(typ.__module__,
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typ.__qualname__),
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id=exception_id)
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constructor_type = types.TExceptionConstructor(instance_type)
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else:
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instance_type = types.TInstance("{}.{}".format(typ.__module__, typ.__qualname__),
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OrderedDict())
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instance_type.attributes['__objectid__'] = builtins.TInt32()
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if hasattr(typ, 'kernel_invariants'):
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assert isinstance(typ.kernel_invariants, set)
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instance_type.constant_attributes = typ.kernel_invariants
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constructor_type = types.TConstructor(instance_type)
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constructor_type.attributes['__objectid__'] = builtins.TInt32()
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instance_type.constructor = constructor_type
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self.type_map[typ] = instance_type, constructor_type
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if isinstance(value, type):
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self.value_map[constructor_type].append((value, loc))
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return asttyped.QuoteT(value=value, type=constructor_type,
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loc=loc)
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else:
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self.value_map[instance_type].append((value, loc))
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return asttyped.QuoteT(value=value, type=instance_type,
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loc=loc)
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def call(self, callee, args, kwargs, callback=None):
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"""
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Construct an AST fragment calling a function specified by
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an AST node `function_node`, with given arguments.
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"""
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if callback is not None:
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callback_node = self.quote(callback)
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cb_begin_loc = self._add("(")
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callee_node = self.quote(callee)
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arg_nodes = []
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kwarg_nodes = []
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kwarg_locs = []
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begin_loc = self._add("(")
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for index, arg in enumerate(args):
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arg_nodes.append(self.quote(arg))
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if index < len(args) - 1:
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self._add(", ")
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if any(args) and any(kwargs):
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self._add(", ")
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for index, kw in enumerate(kwargs):
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arg_loc = self._add(kw)
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equals_loc = self._add("=")
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kwarg_locs.append((arg_loc, equals_loc))
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kwarg_nodes.append(self.quote(kwargs[kw]))
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if index < len(kwargs) - 1:
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self._add(", ")
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end_loc = self._add(")")
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if callback is not None:
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cb_end_loc = self._add(")")
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node = asttyped.CallT(
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func=callee_node,
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args=arg_nodes,
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keywords=[ast.keyword(arg=kw, value=value,
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arg_loc=arg_loc, equals_loc=equals_loc,
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loc=arg_loc.join(value.loc))
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for kw, value, (arg_loc, equals_loc)
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in zip(kwargs, kwarg_nodes, kwarg_locs)],
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starargs=None, kwargs=None,
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type=types.TVar(), iodelay=None, arg_exprs={},
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begin_loc=begin_loc, end_loc=end_loc, star_loc=None, dstar_loc=None,
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loc=callee_node.loc.join(end_loc))
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if callback is not None:
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node = asttyped.CallT(
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func=callback_node,
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args=[node], keywords=[], starargs=None, kwargs=None,
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type=builtins.TNone(), iodelay=None, arg_exprs={},
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begin_loc=cb_begin_loc, end_loc=cb_end_loc, star_loc=None, dstar_loc=None,
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loc=callback_node.loc.join(cb_end_loc))
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return node
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def assign_attribute(self, obj, attr_name, value):
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obj_node = self.quote(obj)
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dot_loc = self._add(".")
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name_loc = self._add(attr_name)
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_ = self._add(" ")
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equals_loc = self._add("=")
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_ = self._add(" ")
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value_node = self.quote(value)
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attr_node = asttyped.AttributeT(value=obj_node, attr=attr_name, ctx=None,
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type=value_node.type,
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dot_loc=dot_loc, attr_loc=name_loc,
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loc=obj_node.loc.join(name_loc))
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return ast.Assign(targets=[attr_node], value=value_node,
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op_locs=[equals_loc], loc=name_loc.join(value_node.loc))
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def suggest_identifier(id, names):
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sorted_names = sorted(names, key=lambda other: jaro_winkler(id, other), reverse=True)
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if len(sorted_names) > 0:
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if jaro_winkler(id, sorted_names[0]) > 0.0 and similarity(id, sorted_names[0]) > 0.5:
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return sorted_names[0]
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class StitchingASTTypedRewriter(ASTTypedRewriter):
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def __init__(self, engine, prelude, globals, host_environment, quote):
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super().__init__(engine, prelude)
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self.globals = globals
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self.env_stack.append(self.globals)
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self.host_environment = host_environment
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self.quote = quote
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def visit_quoted_function(self, node, function):
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extractor = LocalExtractor(env_stack=self.env_stack, engine=self.engine)
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extractor.visit(node)
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# We quote the defaults so they end up in the global data in LLVM IR.
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# This way there is no "life before main", i.e. they do not have to be
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# constructed before the main translated call executes; but the Python
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# semantics is kept.
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defaults = function.__defaults__ or ()
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quoted_defaults = []
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for default, default_node in zip(defaults, node.args.defaults):
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quoted_defaults.append(self.quote(default, default_node.loc))
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node.args.defaults = quoted_defaults
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node = asttyped.QuotedFunctionDefT(
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typing_env=extractor.typing_env, globals_in_scope=extractor.global_,
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signature_type=types.TVar(), return_type=types.TVar(),
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name=node.name, args=node.args, returns=node.returns,
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body=node.body, decorator_list=node.decorator_list,
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keyword_loc=node.keyword_loc, name_loc=node.name_loc,
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arrow_loc=node.arrow_loc, colon_loc=node.colon_loc, at_locs=node.at_locs,
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loc=node.loc)
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try:
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self.env_stack.append(node.typing_env)
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return self.generic_visit(node)
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finally:
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self.env_stack.pop()
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def visit_Name(self, node):
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typ = super()._try_find_name(node.id)
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if typ is not None:
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# Value from device environment.
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return asttyped.NameT(type=typ, id=node.id, ctx=node.ctx,
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loc=node.loc)
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else:
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# Try to find this value in the host environment and quote it.
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if node.id == "print":
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return self.quote(coredevice_print, node.loc)
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elif node.id in self.host_environment:
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return self.quote(self.host_environment[node.id], node.loc)
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else:
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names = set()
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names.update(self.host_environment.keys())
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for typing_env in reversed(self.env_stack):
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names.update(typing_env.keys())
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suggestion = suggest_identifier(node.id, names)
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if suggestion is not None:
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diag = diagnostic.Diagnostic("fatal",
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"name '{name}' is not bound to anything; did you mean '{suggestion}'?",
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{"name": node.id, "suggestion": suggestion},
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node.loc)
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self.engine.process(diag)
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else:
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diag = diagnostic.Diagnostic("fatal",
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"name '{name}' is not bound to anything", {"name": node.id},
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node.loc)
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self.engine.process(diag)
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class StitchingInferencer(Inferencer):
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def __init__(self, engine, value_map, quote):
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super().__init__(engine)
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self.value_map = value_map
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self.quote = quote
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self.attr_type_cache = {}
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def _compute_value_type(self, object_value, object_type, object_loc, attr_name, loc):
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if not hasattr(object_value, attr_name):
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if attr_name.startswith('_'):
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names = set(filter(lambda name: not name.startswith('_'),
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dir(object_value)))
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else:
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names = set(dir(object_value))
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suggestion = suggest_identifier(attr_name, names)
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note = diagnostic.Diagnostic("note",
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"attribute accessed here", {},
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loc)
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if suggestion is not None:
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diag = diagnostic.Diagnostic("error",
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"host object does not have an attribute '{attr}'; "
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"did you mean '{suggestion}'?",
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{"attr": attr_name, "suggestion": suggestion},
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object_loc, notes=[note])
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else:
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diag = diagnostic.Diagnostic("error",
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"host object does not have an attribute '{attr}'",
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{"attr": attr_name},
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object_loc, notes=[note])
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self.engine.process(diag)
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return
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# Figure out what ARTIQ type does the value of the attribute have.
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# We do this by quoting it, as if to serialize. This has some
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# overhead (i.e. synthesizing a source buffer), but has the advantage
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# of having the host-to-ARTIQ mapping code in only one place and
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# also immediately getting proper diagnostics on type errors.
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attr_value = getattr(object_value, attr_name)
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if inspect.ismethod(attr_value) and types.is_instance(object_type):
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# In cases like:
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# class c:
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# @kernel
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# def f(self): pass
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# we want f to be defined on the class, not on the instance.
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attributes = object_type.constructor.attributes
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attr_value = attr_value.__func__
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else:
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attributes = object_type.attributes
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attr_value_type = None
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if isinstance(attr_value, list):
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# Fast path for lists of scalars.
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IS_FLOAT = 1
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IS_INT32 = 2
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IS_INT64 = 4
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state = 0
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for elt in attr_value:
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if elt.__class__ == float:
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state |= IS_FLOAT
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elif elt.__class__ == int:
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if -2**31 < elt < 2**31-1:
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state |= IS_INT32
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elif -2**63 < elt < 2**63-1:
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state |= IS_INT64
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else:
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state = -1
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break
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else:
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state = -1
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if state == IS_FLOAT:
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attr_value_type = builtins.TList(builtins.TFloat())
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elif state == IS_INT32:
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attr_value_type = builtins.TList(builtins.TInt32())
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elif state == IS_INT64:
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attr_value_type = builtins.TList(builtins.TInt64())
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if attr_value_type is None:
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# Slow path. We don't know what exactly is the attribute value,
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# so we quote it only for the error message that may possibly result.
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ast = self.quote(attr_value, object_loc.expanded_from)
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def proxy_diagnostic(diag):
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note = diagnostic.Diagnostic("note",
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"while inferring a type for an attribute '{attr}' of a host object",
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{"attr": attr_name},
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loc)
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diag.notes.append(note)
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self.engine.process(diag)
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proxy_engine = diagnostic.Engine()
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proxy_engine.process = proxy_diagnostic
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Inferencer(engine=proxy_engine).visit(ast)
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IntMonomorphizer(engine=proxy_engine).visit(ast)
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attr_value_type = ast.type
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return attributes, attr_value_type
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def _unify_attribute(self, result_type, value_node, attr_name, attr_loc, loc):
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# The inferencer can only observe types, not values; however,
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# when we work with host objects, we have to get the values
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# somewhere, since host interpreter does not have types.
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# Since we have categorized every host object we quoted according to
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# its type, we now interrogate every host object we have to ensure
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# that we can successfully serialize the value of the attribute we
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# are now adding at the code generation stage.
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object_type = value_node.type.find()
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for object_value, object_loc in self.value_map[object_type]:
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attr_type_key = (id(object_value), attr_name)
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try:
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attributes, attr_value_type = self.attr_type_cache[attr_type_key]
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except KeyError:
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attributes, attr_value_type = \
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self._compute_value_type(object_value, object_type, object_loc, attr_name, loc)
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self.attr_type_cache[attr_type_key] = attributes, attr_value_type
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if attr_name not in attributes:
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# We just figured out what the type should be. Add it.
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attributes[attr_name] = attr_value_type
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else:
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# Does this conflict with an earlier guess?
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try:
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attributes[attr_name].unify(attr_value_type)
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except types.UnificationError as e:
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printer = types.TypePrinter()
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diag = diagnostic.Diagnostic("error",
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"host object has an attribute '{attr}' of type {typea}, which is"
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" different from previously inferred type {typeb} for the same attribute",
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{"typea": printer.name(attr_value_type),
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"typeb": printer.name(attributes[attr_name]),
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"attr": attr_name},
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object_loc)
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self.engine.process(diag)
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super()._unify_attribute(result_type, value_node, attr_name, attr_loc, loc)
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class TypedtreeHasher(algorithm.Visitor):
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def generic_visit(self, node):
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def freeze(obj):
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if isinstance(obj, ast.AST):
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return self.visit(obj)
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elif isinstance(obj, types.Type):
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return hash(obj.find())
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else:
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# We don't care; only types change during inference.
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pass
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fields = node._fields
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if hasattr(node, '_types'):
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fields = fields + node._types
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return hash(tuple(freeze(getattr(node, field_name)) for field_name in fields))
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class Stitcher:
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def __init__(self, core, dmgr, engine=None):
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self.core = core
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self.dmgr = dmgr
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if engine is None:
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self.engine = diagnostic.Engine(all_errors_are_fatal=True)
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else:
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self.engine = engine
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|
|
|
self.name = ""
|
|
self.typedtree = []
|
|
self.inject_at = 0
|
|
self.prelude = prelude.globals()
|
|
self.prelude.pop("print")
|
|
self.globals = {}
|
|
|
|
self.functions = {}
|
|
|
|
self.function_map = {}
|
|
self.object_map = ObjectMap()
|
|
self.type_map = {}
|
|
self.value_map = defaultdict(lambda: [])
|
|
|
|
def stitch_call(self, function, args, kwargs, callback=None):
|
|
# We synthesize source code for the initial call so that
|
|
# diagnostics would have something meaningful to display to the user.
|
|
synthesizer = self._synthesizer(self._function_loc(function.artiq_embedded.function))
|
|
call_node = synthesizer.call(function, args, kwargs, callback)
|
|
synthesizer.finalize()
|
|
self.typedtree.append(call_node)
|
|
|
|
def finalize(self):
|
|
inferencer = StitchingInferencer(engine=self.engine,
|
|
value_map=self.value_map,
|
|
quote=self._quote)
|
|
hasher = TypedtreeHasher()
|
|
|
|
# Iterate inference to fixed point.
|
|
old_typedtree_hash = None
|
|
while True:
|
|
inferencer.visit(self.typedtree)
|
|
typedtree_hash = hasher.visit(self.typedtree)
|
|
|
|
if old_typedtree_hash == typedtree_hash:
|
|
break
|
|
old_typedtree_hash = typedtree_hash
|
|
|
|
# For every host class we embed, fill in the function slots
|
|
# with their corresponding closures.
|
|
for instance_type, constructor_type in list(self.type_map.values()):
|
|
# Do we have any direct reference to a constructor?
|
|
if len(self.value_map[constructor_type]) > 0:
|
|
# Yes, use it.
|
|
constructor, _constructor_loc = self.value_map[constructor_type][0]
|
|
else:
|
|
# No, extract one from a reference to an instance.
|
|
instance, _instance_loc = self.value_map[instance_type][0]
|
|
constructor = type(instance)
|
|
|
|
for attr in constructor_type.attributes:
|
|
if types.is_function(constructor_type.attributes[attr]):
|
|
synthesizer = self._synthesizer()
|
|
ast = synthesizer.assign_attribute(constructor, attr,
|
|
getattr(constructor, attr))
|
|
synthesizer.finalize()
|
|
self._inject(ast)
|
|
|
|
# After we have found all functions, synthesize a module to hold them.
|
|
source_buffer = source.Buffer("", "<synthesized>")
|
|
self.typedtree = asttyped.ModuleT(
|
|
typing_env=self.globals, globals_in_scope=set(),
|
|
body=self.typedtree, loc=source.Range(source_buffer, 0, 0))
|
|
|
|
def _inject(self, node):
|
|
self.typedtree.insert(self.inject_at, node)
|
|
self.inject_at += 1
|
|
|
|
def _synthesizer(self, expanded_from=None):
|
|
return ASTSynthesizer(expanded_from=expanded_from,
|
|
object_map=self.object_map,
|
|
type_map=self.type_map,
|
|
value_map=self.value_map,
|
|
quote_function=self._quote_function)
|
|
|
|
def _quote_embedded_function(self, function, flags):
|
|
if not hasattr(function, "artiq_embedded"):
|
|
raise ValueError("{} is not an embedded function".format(repr(function)))
|
|
|
|
# Extract function source.
|
|
embedded_function = function.artiq_embedded.function
|
|
source_code = inspect.getsource(embedded_function)
|
|
filename = embedded_function.__code__.co_filename
|
|
module_name = embedded_function.__globals__['__name__']
|
|
first_line = embedded_function.__code__.co_firstlineno
|
|
|
|
# Extract function environment.
|
|
host_environment = dict()
|
|
host_environment.update(embedded_function.__globals__)
|
|
cells = embedded_function.__closure__
|
|
cell_names = embedded_function.__code__.co_freevars
|
|
host_environment.update({var: cells[index] for index, var in enumerate(cell_names)})
|
|
|
|
# Find out how indented we are.
|
|
initial_whitespace = re.search(r"^\s*", source_code).group(0)
|
|
initial_indent = len(initial_whitespace.expandtabs())
|
|
|
|
# Parse.
|
|
source_buffer = source.Buffer(source_code, filename, first_line)
|
|
lexer = source_lexer.Lexer(source_buffer, version=sys.version_info[0:2],
|
|
diagnostic_engine=self.engine)
|
|
lexer.indent = [(initial_indent,
|
|
source.Range(source_buffer, 0, len(initial_whitespace)),
|
|
initial_whitespace)]
|
|
parser = source_parser.Parser(lexer, version=sys.version_info[0:2],
|
|
diagnostic_engine=self.engine)
|
|
function_node = parser.file_input().body[0]
|
|
|
|
# Mangle the name, since we put everything into a single module.
|
|
function_node.name = "{}.{}".format(module_name, function.__qualname__)
|
|
|
|
# Record the function in the function map so that LLVM IR generator
|
|
# can handle quoting it.
|
|
self.function_map[function] = function_node.name
|
|
|
|
# Memoize the function type before typing it to handle recursive
|
|
# invocations.
|
|
self.functions[function] = types.TVar()
|
|
|
|
# Rewrite into typed form.
|
|
asttyped_rewriter = StitchingASTTypedRewriter(
|
|
engine=self.engine, prelude=self.prelude,
|
|
globals=self.globals, host_environment=host_environment,
|
|
quote=self._quote)
|
|
function_node = asttyped_rewriter.visit_quoted_function(function_node, embedded_function)
|
|
function_node.flags = flags
|
|
|
|
# Add it into our typedtree so that it gets inferenced and codegen'd.
|
|
self._inject(function_node)
|
|
|
|
# Tie the typing knot.
|
|
self.functions[function].unify(function_node.signature_type)
|
|
|
|
return function_node
|
|
|
|
def _function_loc(self, function):
|
|
filename = function.__code__.co_filename
|
|
line = function.__code__.co_firstlineno
|
|
name = function.__code__.co_name
|
|
|
|
source_line = linecache.getline(filename, line)
|
|
while source_line.lstrip().startswith("@"):
|
|
line += 1
|
|
source_line = linecache.getline(filename, line)
|
|
|
|
if "<lambda>" in function.__qualname__:
|
|
column = 0 # can't get column of lambda
|
|
else:
|
|
column = re.search("def", source_line).start(0)
|
|
source_buffer = source.Buffer(source_line, filename, line)
|
|
return source.Range(source_buffer, column, column)
|
|
|
|
def _call_site_note(self, call_loc, is_syscall):
|
|
if call_loc:
|
|
if is_syscall:
|
|
return [diagnostic.Diagnostic("note",
|
|
"in system call here", {},
|
|
call_loc)]
|
|
else:
|
|
return [diagnostic.Diagnostic("note",
|
|
"in function called remotely here", {},
|
|
call_loc)]
|
|
else:
|
|
return []
|
|
|
|
def _extract_annot(self, function, annot, kind, call_loc, is_syscall):
|
|
if not isinstance(annot, types.Type):
|
|
diag = diagnostic.Diagnostic("error",
|
|
"type annotation for {kind}, '{annot}', is not an ARTIQ type",
|
|
{"kind": kind, "annot": repr(annot)},
|
|
self._function_loc(function),
|
|
notes=self._call_site_note(call_loc, is_syscall))
|
|
self.engine.process(diag)
|
|
|
|
return types.TVar()
|
|
else:
|
|
return annot
|
|
|
|
def _type_of_param(self, function, loc, param, is_syscall):
|
|
if param.annotation is not inspect.Parameter.empty:
|
|
# Type specified explicitly.
|
|
return self._extract_annot(function, param.annotation,
|
|
"argument '{}'".format(param.name), loc,
|
|
is_syscall)
|
|
elif is_syscall:
|
|
# Syscalls must be entirely annotated.
|
|
diag = diagnostic.Diagnostic("error",
|
|
"system call argument '{argument}' must have a type annotation",
|
|
{"argument": param.name},
|
|
self._function_loc(function),
|
|
notes=self._call_site_note(loc, is_syscall))
|
|
self.engine.process(diag)
|
|
elif param.default is not inspect.Parameter.empty:
|
|
# Try and infer the type from the default value.
|
|
# This is tricky, because the default value might not have
|
|
# a well-defined type in APython.
|
|
# In this case, we bail out, but mention why we do it.
|
|
ast = self._quote(param.default, None)
|
|
|
|
def proxy_diagnostic(diag):
|
|
note = diagnostic.Diagnostic("note",
|
|
"expanded from here while trying to infer a type for an"
|
|
" unannotated optional argument '{argument}' from its default value",
|
|
{"argument": param.name},
|
|
self._function_loc(function))
|
|
diag.notes.append(note)
|
|
|
|
note = self._call_site_note(loc, is_syscall)
|
|
if note:
|
|
diag.notes += note
|
|
|
|
self.engine.process(diag)
|
|
|
|
proxy_engine = diagnostic.Engine()
|
|
proxy_engine.process = proxy_diagnostic
|
|
Inferencer(engine=proxy_engine).visit(ast)
|
|
IntMonomorphizer(engine=proxy_engine).visit(ast)
|
|
|
|
return ast.type
|
|
else:
|
|
# Let the rest of the program decide.
|
|
return types.TVar()
|
|
|
|
def _quote_syscall(self, function, loc):
|
|
signature = inspect.signature(function)
|
|
|
|
arg_types = OrderedDict()
|
|
optarg_types = OrderedDict()
|
|
for param in signature.parameters.values():
|
|
if param.kind != inspect.Parameter.POSITIONAL_OR_KEYWORD:
|
|
diag = diagnostic.Diagnostic("error",
|
|
"system calls must only use positional arguments; '{argument}' isn't",
|
|
{"argument": param.name},
|
|
self._function_loc(function),
|
|
notes=self._call_site_note(loc, is_syscall=True))
|
|
self.engine.process(diag)
|
|
|
|
if param.default is inspect.Parameter.empty:
|
|
arg_types[param.name] = self._type_of_param(function, loc, param, is_syscall=True)
|
|
else:
|
|
diag = diagnostic.Diagnostic("error",
|
|
"system call argument '{argument}' must not have a default value",
|
|
{"argument": param.name},
|
|
self._function_loc(function),
|
|
notes=self._call_site_note(loc, is_syscall=True))
|
|
self.engine.process(diag)
|
|
|
|
if signature.return_annotation is not inspect.Signature.empty:
|
|
ret_type = self._extract_annot(function, signature.return_annotation,
|
|
"return type", loc, is_syscall=True)
|
|
else:
|
|
diag = diagnostic.Diagnostic("error",
|
|
"system call must have a return type annotation", {},
|
|
self._function_loc(function),
|
|
notes=self._call_site_note(loc, is_syscall=True))
|
|
self.engine.process(diag)
|
|
ret_type = types.TVar()
|
|
|
|
function_type = types.TCFunction(arg_types, ret_type,
|
|
name=function.artiq_embedded.syscall,
|
|
flags=function.artiq_embedded.flags)
|
|
self.functions[function] = function_type
|
|
return function_type
|
|
|
|
def _quote_rpc(self, function, loc):
|
|
signature = inspect.signature(function)
|
|
|
|
if signature.return_annotation is not inspect.Signature.empty:
|
|
ret_type = self._extract_annot(function, signature.return_annotation,
|
|
"return type", loc, is_syscall=False)
|
|
else:
|
|
ret_type = builtins.TNone()
|
|
|
|
function_type = types.TRPC(ret_type, service=self.object_map.store(function))
|
|
self.functions[function] = function_type
|
|
return function_type
|
|
|
|
def _quote_function(self, function, loc):
|
|
if function not in self.functions:
|
|
if hasattr(function, "artiq_embedded"):
|
|
if function.artiq_embedded.function is not None:
|
|
if function.__name__ == "<lambda>":
|
|
note = diagnostic.Diagnostic("note",
|
|
"lambda created here", {},
|
|
self._function_loc(function.artiq_embedded.function))
|
|
diag = diagnostic.Diagnostic("fatal",
|
|
"lambdas cannot be used as kernel functions", {},
|
|
loc,
|
|
notes=[note])
|
|
self.engine.process(diag)
|
|
|
|
core_name = function.artiq_embedded.core_name
|
|
if core_name is not None and self.dmgr.get(core_name) != self.core:
|
|
note = diagnostic.Diagnostic("note",
|
|
"called from this function", {},
|
|
loc)
|
|
diag = diagnostic.Diagnostic("fatal",
|
|
"this function runs on a different core device '{name}'",
|
|
{"name": function.artiq_embedded.core_name},
|
|
self._function_loc(function.artiq_embedded.function),
|
|
notes=[note])
|
|
self.engine.process(diag)
|
|
|
|
self._quote_embedded_function(function,
|
|
flags=function.artiq_embedded.flags)
|
|
elif function.artiq_embedded.syscall is not None:
|
|
# Insert a storage-less global whose type instructs the compiler
|
|
# to perform a system call instead of a regular call.
|
|
self._quote_syscall(function, loc)
|
|
elif function.artiq_embedded.forbidden is not None:
|
|
diag = diagnostic.Diagnostic("fatal",
|
|
"this function cannot be called as an RPC", {},
|
|
self._function_loc(function),
|
|
notes=self._call_site_note(loc, is_syscall=True))
|
|
self.engine.process(diag)
|
|
else:
|
|
assert False
|
|
else:
|
|
self._quote_rpc(function, loc)
|
|
|
|
return self.functions[function]
|
|
|
|
def _quote(self, value, loc):
|
|
synthesizer = self._synthesizer(loc)
|
|
node = synthesizer.quote(value)
|
|
synthesizer.finalize()
|
|
return node
|