artiq/artiq/compiler/embedding.py
2017-03-02 15:28:24 +00:00

1094 lines
48 KiB
Python

"""
The :class:`Stitcher` class allows to transparently combine compiled
Python code and Python code executed on the host system: it resolves
the references to the host objects and translates the functions
annotated as ``@kernel`` when they are referenced.
"""
import sys, os, re, linecache, inspect, textwrap, types as pytypes, numpy
from collections import OrderedDict, defaultdict
from pythonparser import ast, algorithm, source, diagnostic, parse_buffer
from pythonparser import lexer as source_lexer, parser as source_parser
from Levenshtein import ratio as similarity, jaro_winkler
from ..language import core as language_core
from . import types, builtins, asttyped, prelude
from .transforms import ASTTypedRewriter, Inferencer, IntMonomorphizer, TypedtreePrinter
from .transforms.asttyped_rewriter import LocalExtractor
class SpecializedFunction:
def __init__(self, instance_type, host_function):
self.instance_type = instance_type
self.host_function = host_function
def __eq__(self, other):
if isinstance(other, tuple):
return (self.instance_type == other[0] or
self.host_function == other[1])
else:
return (self.instance_type == other.instance_type or
self.host_function == other.host_function)
def __ne__(self, other):
return not self == other
def __hash__(self):
return hash((self.instance_type, self.host_function))
class EmbeddingMap:
def __init__(self):
self.object_current_key = 0
self.object_forward_map = {}
self.object_reverse_map = {}
self.module_map = {}
self.type_map = {}
self.function_map = {}
# Modules
def store_module(self, module, module_type):
self.module_map[module] = module_type
def retrieve_module(self, module):
return self.module_map[module]
def has_module(self, module):
return module in self.module_map
# Types
def store_type(self, host_type, instance_type, constructor_type):
self._rename_type(instance_type)
self.type_map[host_type] = (instance_type, constructor_type)
def retrieve_type(self, host_type):
return self.type_map[host_type]
def has_type(self, host_type):
return host_type in self.type_map
def _rename_type(self, new_instance_type):
# Generally, user-defined types that have exact same name (which is to say, classes
# defined inside functions) do not pose a problem to the compiler. The two places which
# cannot handle this are:
# 1. {TInstance,TConstructor}.__hash__
# 2. LLVM type names
# Since handling #2 requires renaming on ARTIQ side anyway, it's more straightforward
# to do it once when embedding (since non-embedded code cannot define classes in
# functions). Also, easier to debug.
n = 0
for host_type in self.type_map:
instance_type, constructor_type = self.type_map[host_type]
if instance_type.name == new_instance_type.name:
n += 1
new_instance_type.name = "{}.{}".format(new_instance_type.name, n)
def attribute_count(self):
count = 0
for host_type in self.type_map:
instance_type, constructor_type = self.type_map[host_type]
count += len(instance_type.attributes)
count += len(constructor_type.attributes)
return count
# Functions
def store_function(self, function, ir_function_name):
self.function_map[function] = ir_function_name
def retrieve_function(self, function):
return self.function_map[function]
def specialize_function(self, instance_type, host_function):
return SpecializedFunction(instance_type, host_function)
# Objects
def store_object(self, obj_ref):
obj_id = id(obj_ref)
if obj_id in self.object_reverse_map:
return self.object_reverse_map[obj_id]
self.object_current_key += 1
self.object_forward_map[self.object_current_key] = obj_ref
self.object_reverse_map[obj_id] = self.object_current_key
return self.object_current_key
def retrieve_object(self, obj_key):
return self.object_forward_map[obj_key]
def iter_objects(self):
for obj_id in self.object_forward_map.keys():
obj_ref = self.object_forward_map[obj_id]
if isinstance(obj_ref, (pytypes.FunctionType, pytypes.MethodType,
pytypes.BuiltinFunctionType, pytypes.ModuleType,
SpecializedFunction)):
continue
elif isinstance(obj_ref, type):
_, obj_typ = self.type_map[obj_ref]
else:
obj_typ, _ = self.type_map[type(obj_ref)]
yield obj_id, obj_ref, obj_typ
def has_rpc(self):
return any(filter(lambda x: inspect.isfunction(x) or inspect.ismethod(x),
self.object_forward_map.values()))
class ASTSynthesizer:
def __init__(self, embedding_map, value_map, quote_function=None, expanded_from=None):
self.source = ""
self.source_buffer = source.Buffer(self.source, "<synthesized>")
self.embedding_map = embedding_map
self.value_map = value_map
self.quote_function = quote_function
self.expanded_from = expanded_from
self.diagnostics = []
def finalize(self):
self.source_buffer.source = self.source
return self.source_buffer
def _add(self, fragment):
range_from = len(self.source)
self.source += fragment
range_to = len(self.source)
return source.Range(self.source_buffer, range_from, range_to,
expanded_from=self.expanded_from)
def quote(self, value):
"""Construct an AST fragment equal to `value`."""
if value is None:
typ = builtins.TNone()
return asttyped.NameConstantT(value=value, type=typ,
loc=self._add(repr(value)))
elif value is True or value is False:
typ = builtins.TBool()
return asttyped.NameConstantT(value=value, type=typ,
loc=self._add(repr(value)))
elif value is numpy.int32:
typ = builtins.fn_int32()
return asttyped.NameConstantT(value=None, type=typ,
loc=self._add("numpy.int32"))
elif value is numpy.int64:
typ = builtins.fn_int64()
return asttyped.NameConstantT(value=None, type=typ,
loc=self._add("numpy.int64"))
elif value is numpy.array:
typ = builtins.fn_array()
return asttyped.NameConstantT(value=None, type=typ,
loc=self._add("numpy.array"))
elif value is numpy.full:
typ = builtins.fn_make_array()
return asttyped.NameConstantT(value=None, type=typ,
loc=self._add("numpy.full"))
elif isinstance(value, (int, float)):
if isinstance(value, int):
typ = builtins.TInt()
elif isinstance(value, float):
typ = builtins.TFloat()
return asttyped.NumT(n=value, ctx=None, type=typ,
loc=self._add(repr(value)))
elif isinstance(value, numpy.int32):
typ = builtins.TInt32()
return asttyped.NumT(n=int(value), ctx=None, type=typ,
loc=self._add(repr(value)))
elif isinstance(value, numpy.int64):
typ = builtins.TInt64()
return asttyped.NumT(n=int(value), ctx=None, type=typ,
loc=self._add(repr(value)))
elif isinstance(value, str):
return asttyped.StrT(s=value, ctx=None, type=builtins.TStr(),
loc=self._add(repr(value)))
elif isinstance(value, list):
begin_loc = self._add("[")
elts = []
for index, elt in enumerate(value):
elts.append(self.quote(elt))
if index < len(value) - 1:
self._add(", ")
end_loc = self._add("]")
return asttyped.ListT(elts=elts, ctx=None, type=builtins.TList(),
begin_loc=begin_loc, end_loc=end_loc,
loc=begin_loc.join(end_loc))
elif isinstance(value, numpy.ndarray):
begin_loc = self._add("numpy.array([")
elts = []
for index, elt in enumerate(value):
elts.append(self.quote(elt))
if index < len(value) - 1:
self._add(", ")
end_loc = self._add("])")
return asttyped.ListT(elts=elts, ctx=None, type=builtins.TArray(),
begin_loc=begin_loc, end_loc=end_loc,
loc=begin_loc.join(end_loc))
elif inspect.isfunction(value) or inspect.ismethod(value) or \
isinstance(value, pytypes.BuiltinFunctionType) or \
isinstance(value, SpecializedFunction):
if inspect.ismethod(value):
quoted_self = self.quote(value.__self__)
function_type = self.quote_function(value.__func__, self.expanded_from)
method_type = types.TMethod(quoted_self.type, function_type)
dot_loc = self._add('.')
name_loc = self._add(value.__func__.__name__)
loc = quoted_self.loc.join(name_loc)
return asttyped.QuoteT(value=value, type=method_type,
self_loc=quoted_self.loc, loc=loc)
else: # function
function_type = self.quote_function(value, self.expanded_from)
quote_loc = self._add('`')
repr_loc = self._add(repr(value))
unquote_loc = self._add('`')
loc = quote_loc.join(unquote_loc)
return asttyped.QuoteT(value=value, type=function_type, loc=loc)
elif isinstance(value, pytypes.ModuleType):
if self.embedding_map.has_module(value):
module_type = self.embedding_map.retrieve_module(value)
else:
module_type = types.TModule(value.__name__, OrderedDict())
module_type.attributes['__objectid__'] = builtins.TInt32()
self.embedding_map.store_module(value, module_type)
quote_loc = self._add('`')
repr_loc = self._add(repr(value))
unquote_loc = self._add('`')
loc = quote_loc.join(unquote_loc)
self.value_map[module_type].append((value, loc))
return asttyped.QuoteT(value=value, type=module_type, loc=loc)
else:
quote_loc = self._add('`')
repr_loc = self._add(repr(value))
unquote_loc = self._add('`')
loc = quote_loc.join(unquote_loc)
if isinstance(value, type):
typ = value
else:
typ = type(value)
if self.embedding_map.has_type(typ):
instance_type, constructor_type = self.embedding_map.retrieve_type(typ)
if hasattr(value, 'kernel_invariants') and \
value.kernel_invariants != instance_type.constant_attributes:
attr_diff = value.kernel_invariants.difference(
instance_type.constant_attributes)
if len(attr_diff) > 0:
diag = diagnostic.Diagnostic("warning",
"object {value} of type {typ} declares attribute(s) {attrs} as "
"kernel invariant, but other objects of the same type do not; "
"the invariant annotation on this object will be ignored",
{"value": repr(value),
"typ": types.TypePrinter().name(instance_type, max_depth=0),
"attrs": ", ".join(["'{}'".format(attr) for attr in attr_diff])},
loc)
self.diagnostics.append(diag)
attr_diff = instance_type.constant_attributes.difference(
value.kernel_invariants)
if len(attr_diff) > 0:
diag = diagnostic.Diagnostic("warning",
"object {value} of type {typ} does not declare attribute(s) {attrs} as "
"kernel invariant, but other objects of the same type do; "
"the invariant annotation on other objects will be ignored",
{"value": repr(value),
"typ": types.TypePrinter().name(instance_type, max_depth=0),
"attrs": ", ".join(["'{}'".format(attr) for attr in attr_diff])},
loc)
self.diagnostics.append(diag)
value.kernel_invariants = value.kernel_invariants.intersection(
instance_type.constant_attributes)
else:
if issubclass(typ, BaseException):
if hasattr(typ, 'artiq_builtin'):
exception_id = 0
else:
exception_id = self.embedding_map.store_object(typ)
instance_type = builtins.TException("{}.{}".format(typ.__module__,
typ.__qualname__),
id=exception_id)
constructor_type = types.TExceptionConstructor(instance_type)
else:
instance_type = types.TInstance("{}.{}".format(typ.__module__, typ.__qualname__),
OrderedDict())
instance_type.attributes['__objectid__'] = builtins.TInt32()
constructor_type = types.TConstructor(instance_type)
constructor_type.attributes['__objectid__'] = builtins.TInt32()
instance_type.constructor = constructor_type
self.embedding_map.store_type(typ, instance_type, constructor_type)
if hasattr(value, 'kernel_invariants'):
assert isinstance(value.kernel_invariants, set)
instance_type.constant_attributes = value.kernel_invariants
if isinstance(value, type):
self.value_map[constructor_type].append((value, loc))
return asttyped.QuoteT(value=value, type=constructor_type,
loc=loc)
else:
self.value_map[instance_type].append((value, loc))
return asttyped.QuoteT(value=value, type=instance_type,
loc=loc)
def call(self, callee, args, kwargs, callback=None):
"""
Construct an AST fragment calling a function specified by
an AST node `function_node`, with given arguments.
"""
if callback is not None:
callback_node = self.quote(callback)
cb_begin_loc = self._add("(")
callee_node = self.quote(callee)
arg_nodes = []
kwarg_nodes = []
kwarg_locs = []
begin_loc = self._add("(")
for index, arg in enumerate(args):
arg_nodes.append(self.quote(arg))
if index < len(args) - 1:
self._add(", ")
if any(args) and any(kwargs):
self._add(", ")
for index, kw in enumerate(kwargs):
arg_loc = self._add(kw)
equals_loc = self._add("=")
kwarg_locs.append((arg_loc, equals_loc))
kwarg_nodes.append(self.quote(kwargs[kw]))
if index < len(kwargs) - 1:
self._add(", ")
end_loc = self._add(")")
if callback is not None:
cb_end_loc = self._add(")")
node = asttyped.CallT(
func=callee_node,
args=arg_nodes,
keywords=[ast.keyword(arg=kw, value=value,
arg_loc=arg_loc, equals_loc=equals_loc,
loc=arg_loc.join(value.loc))
for kw, value, (arg_loc, equals_loc)
in zip(kwargs, kwarg_nodes, kwarg_locs)],
starargs=None, kwargs=None,
type=types.TVar(), iodelay=None, arg_exprs={},
begin_loc=begin_loc, end_loc=end_loc, star_loc=None, dstar_loc=None,
loc=callee_node.loc.join(end_loc))
if callback is not None:
node = asttyped.CallT(
func=callback_node,
args=[node], keywords=[], starargs=None, kwargs=None,
type=builtins.TNone(), iodelay=None, arg_exprs={},
begin_loc=cb_begin_loc, end_loc=cb_end_loc, star_loc=None, dstar_loc=None,
loc=callback_node.loc.join(cb_end_loc))
return node
def assign_attribute(self, obj, attr_name, value):
obj_node = self.quote(obj)
dot_loc = self._add(".")
name_loc = self._add(attr_name)
_ = self._add(" ")
equals_loc = self._add("=")
_ = self._add(" ")
value_node = self.quote(value)
attr_node = asttyped.AttributeT(value=obj_node, attr=attr_name, ctx=None,
type=value_node.type,
dot_loc=dot_loc, attr_loc=name_loc,
loc=obj_node.loc.join(name_loc))
return ast.Assign(targets=[attr_node], value=value_node,
op_locs=[equals_loc], loc=name_loc.join(value_node.loc))
def suggest_identifier(id, names):
sorted_names = sorted(names, key=lambda other: jaro_winkler(id, other), reverse=True)
if len(sorted_names) > 0:
if jaro_winkler(id, sorted_names[0]) > 0.0 and similarity(id, sorted_names[0]) > 0.5:
return sorted_names[0]
class StitchingASTTypedRewriter(ASTTypedRewriter):
def __init__(self, engine, prelude, globals, host_environment, quote):
super().__init__(engine, prelude)
self.globals = globals
self.env_stack.append(self.globals)
self.host_environment = host_environment
self.quote = quote
def match_annotation(self, annot):
if isinstance(annot, ast.Name):
if annot.id == "TNone":
return builtins.TNone()
if annot.id == "TBool":
return builtins.TBool()
if annot.id == "TInt32":
return builtins.TInt(types.TValue(32))
if annot.id == "TInt64":
return builtins.TInt(types.TValue(64))
if annot.id == "TFloat":
return builtins.TFloat()
if annot.id == "TStr":
return builtins.TStr()
if annot.id == "TRange32":
return builtins.TRange(builtins.TInt(types.TValue(32)))
if annot.id == "TRange64":
return builtins.TRange(builtins.TInt(types.TValue(64)))
if annot.id == "TVar":
return types.TVar()
elif (isinstance(annot, ast.Call) and
annot.keywords == [] and
annot.starargs is None and
annot.kwargs is None and
isinstance(annot.func, ast.Name)):
if annot.func.id == "TList" and len(annot.args) == 1:
elttyp = self.match_annotation(annot.args[0])
if elttyp is not None:
return builtins.TList(elttyp)
else:
return None
if annot is not None:
diag = diagnostic.Diagnostic("error",
"unrecognized type annotation", {},
annot.loc)
self.engine.process(diag)
def visit_arg(self, node):
typ = self._find_name(node.arg, node.loc)
annottyp = self.match_annotation(node.annotation)
if annottyp is not None:
typ.unify(annottyp)
return asttyped.argT(type=typ,
arg=node.arg, annotation=None,
arg_loc=node.arg_loc, colon_loc=node.colon_loc, loc=node.loc)
def visit_quoted_function(self, node, function):
extractor = LocalExtractor(env_stack=self.env_stack, engine=self.engine)
extractor.visit(node)
# We quote the defaults so they end up in the global data in LLVM IR.
# This way there is no "life before main", i.e. they do not have to be
# constructed before the main translated call executes; but the Python
# semantics is kept.
defaults = function.__defaults__ or ()
quoted_defaults = []
for default, default_node in zip(defaults, node.args.defaults):
quoted_defaults.append(self.quote(default, default_node.loc))
node.args.defaults = quoted_defaults
node = asttyped.QuotedFunctionDefT(
typing_env=extractor.typing_env, globals_in_scope=extractor.global_,
signature_type=types.TVar(), return_type=types.TVar(),
name=node.name, args=node.args, returns=node.returns,
body=node.body, decorator_list=node.decorator_list,
keyword_loc=node.keyword_loc, name_loc=node.name_loc,
arrow_loc=node.arrow_loc, colon_loc=node.colon_loc, at_locs=node.at_locs,
loc=node.loc)
try:
self.env_stack.append(node.typing_env)
return self.generic_visit(node)
finally:
self.env_stack.pop()
def visit_Name(self, node):
typ = super()._try_find_name(node.id)
if typ is not None:
# Value from device environment.
return asttyped.NameT(type=typ, id=node.id, ctx=node.ctx,
loc=node.loc)
else:
# Try to find this value in the host environment and quote it.
if node.id == "print":
return self.quote(print, node.loc)
elif node.id in self.host_environment:
return self.quote(self.host_environment[node.id], node.loc)
else:
names = set()
names.update(self.host_environment.keys())
for typing_env in reversed(self.env_stack):
names.update(typing_env.keys())
suggestion = suggest_identifier(node.id, names)
if suggestion is not None:
diag = diagnostic.Diagnostic("fatal",
"name '{name}' is not bound to anything; did you mean '{suggestion}'?",
{"name": node.id, "suggestion": suggestion},
node.loc)
self.engine.process(diag)
else:
diag = diagnostic.Diagnostic("fatal",
"name '{name}' is not bound to anything", {"name": node.id},
node.loc)
self.engine.process(diag)
class StitchingInferencer(Inferencer):
def __init__(self, engine, value_map, quote):
super().__init__(engine)
self.value_map = value_map
self.quote = quote
self.attr_type_cache = {}
def _compute_attr_type(self, object_value, object_type, object_loc, attr_name, loc):
if not hasattr(object_value, attr_name):
if attr_name.startswith('_'):
names = set(filter(lambda name: not name.startswith('_'),
dir(object_value)))
else:
names = set(dir(object_value))
suggestion = suggest_identifier(attr_name, names)
note = diagnostic.Diagnostic("note",
"attribute accessed here", {},
loc)
if suggestion is not None:
diag = diagnostic.Diagnostic("error",
"host object does not have an attribute '{attr}'; "
"did you mean '{suggestion}'?",
{"attr": attr_name, "suggestion": suggestion},
object_loc, notes=[note])
else:
diag = diagnostic.Diagnostic("error",
"host object does not have an attribute '{attr}'",
{"attr": attr_name},
object_loc, notes=[note])
self.engine.process(diag)
return
# Figure out what ARTIQ type does the value of the attribute have.
# We do this by quoting it, as if to serialize. This has some
# overhead (i.e. synthesizing a source buffer), but has the advantage
# of having the host-to-ARTIQ mapping code in only one place and
# also immediately getting proper diagnostics on type errors.
attr_value = getattr(object_value, attr_name)
if (inspect.ismethod(attr_value) and
types.is_instance(object_type) and
# Check that the method is indeed defined on the class,
# and not just this instance. The check is written in
# the inverted form and not as hasattr(type(attr_value))
# since the method may as well be defined on a superclass.
attr_name not in object_value.__dict__):
# In cases like:
# class c:
# @kernel
# def f(self): pass
# we want f to be defined on the class, not on the instance.
attributes = object_type.constructor.attributes
attr_value = SpecializedFunction(object_type, attr_value.__func__)
else:
attributes = object_type.attributes
attr_value_type = None
if isinstance(attr_value, list):
# Fast path for lists of scalars.
IS_FLOAT = 1
IS_INT32 = 2
IS_INT64 = 4
state = 0
for elt in attr_value:
if elt.__class__ == float:
state |= IS_FLOAT
elif elt.__class__ == int:
if -2**31 < elt < 2**31-1:
state |= IS_INT32
elif -2**63 < elt < 2**63-1:
state |= IS_INT64
else:
state = -1
break
else:
state = -1
if state == IS_FLOAT:
attr_value_type = builtins.TList(builtins.TFloat())
elif state == IS_INT32:
attr_value_type = builtins.TList(builtins.TInt32())
elif state == IS_INT64:
attr_value_type = builtins.TList(builtins.TInt64())
if attr_value_type is None:
note = diagnostic.Diagnostic("note",
"while inferring a type for an attribute '{attr}' of a host object",
{"attr": attr_name},
loc)
with self.engine.context(note):
# Slow path. We don't know what exactly is the attribute value,
# so we quote it only for the error message that may possibly result.
ast = self.quote(attr_value, object_loc.expanded_from)
Inferencer(engine=self.engine).visit(ast)
IntMonomorphizer(engine=self.engine).visit(ast)
attr_value_type = ast.type
return attributes, attr_value_type
def _unify_attribute(self, result_type, value_node, attr_name, attr_loc, loc):
# The inferencer can only observe types, not values; however,
# when we work with host objects, we have to get the values
# somewhere, since host interpreter does not have types.
# Since we have categorized every host object we quoted according to
# its type, we now interrogate every host object we have to ensure
# that we can successfully serialize the value of the attribute we
# are now adding at the code generation stage.
object_type = value_node.type.find()
for object_value, object_loc in self.value_map[object_type]:
attr_type_key = (id(object_value), attr_name)
try:
attributes, attr_value_type = self.attr_type_cache[attr_type_key]
except KeyError:
attributes, attr_value_type = \
self._compute_attr_type(object_value, object_type, object_loc, attr_name, loc)
self.attr_type_cache[attr_type_key] = attributes, attr_value_type
if attr_name not in attributes:
# We just figured out what the type should be. Add it.
attributes[attr_name] = attr_value_type
else:
# Does this conflict with an earlier guess?
try:
attributes[attr_name].unify(attr_value_type)
except types.UnificationError as e:
printer = types.TypePrinter()
diag = diagnostic.Diagnostic("error",
"host object has an attribute '{attr}' of type {typea}, which is"
" different from previously inferred type {typeb} for the same attribute",
{"typea": printer.name(attr_value_type),
"typeb": printer.name(attributes[attr_name]),
"attr": attr_name},
object_loc)
self.engine.process(diag)
super()._unify_attribute(result_type, value_node, attr_name, attr_loc, loc)
def visit_QuoteT(self, node):
if inspect.ismethod(node.value):
if types.is_rpc(types.get_method_function(node.type)):
return
self._unify_method_self(method_type=node.type,
attr_name=node.value.__func__.__name__,
attr_loc=None,
loc=node.loc,
self_loc=node.self_loc)
class TypedtreeHasher(algorithm.Visitor):
def generic_visit(self, node):
def freeze(obj):
if isinstance(obj, ast.AST):
return self.visit(obj)
elif isinstance(obj, list):
return hash(tuple(freeze(elem) for elem in obj))
elif isinstance(obj, types.Type):
return hash(obj.find())
else:
# We don't care; only types change during inference.
pass
fields = node._fields
if hasattr(node, '_types'):
fields = fields + node._types
return hash(tuple(freeze(getattr(node, field_name)) for field_name in fields))
class Stitcher:
def __init__(self, core, dmgr, engine=None):
self.core = core
self.dmgr = dmgr
if engine is None:
self.engine = diagnostic.Engine(all_errors_are_fatal=True)
else:
self.engine = engine
self.name = ""
self.typedtree = []
self.inject_at = 0
self.globals = {}
# We don't want some things from the prelude as they are provided in
# the host Python namespace and gain special meaning when quoted.
self.prelude = prelude.globals()
self.prelude.pop("print")
self.prelude.pop("array")
self.functions = {}
self.embedding_map = EmbeddingMap()
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)
typedtree_hasher = TypedtreeHasher()
# Iterate inference to fixed point.
old_typedtree_hash = None
old_attr_count = None
while True:
inferencer.visit(self.typedtree)
typedtree_hash = typedtree_hasher.visit(self.typedtree)
attr_count = self.embedding_map.attribute_count()
if old_typedtree_hash == typedtree_hash and old_attr_count == attr_count:
break
old_typedtree_hash = typedtree_hash
old_attr_count = attr_count
# After we've discovered every referenced attribute, check if any kernel_invariant
# specifications refers to ones we didn't encounter.
for host_type in self.embedding_map.type_map:
instance_type, constructor_type = self.embedding_map.type_map[host_type]
if not hasattr(instance_type, "constant_attributes"):
# Exceptions lack user-definable attributes.
continue
for attribute in instance_type.constant_attributes:
if attribute in instance_type.attributes:
# Fast path; if the ARTIQ Python type has the attribute, then every observed
# value is guaranteed to have it too.
continue
for value, loc in self.value_map[instance_type]:
if hasattr(value, attribute):
continue
diag = diagnostic.Diagnostic("warning",
"object {value} of type {typ} declares attribute '{attr}' as "
"kernel invariant, but the instance referenced here does not "
"have this attribute",
{"value": repr(value),
"typ": types.TypePrinter().name(instance_type, max_depth=0),
"attr": attribute},
loc)
self.engine.process(diag)
# 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,
embedding_map=self.embedding_map,
value_map=self.value_map,
quote_function=self._quote_function)
def _quote_embedded_function(self, function, flags):
if isinstance(function, SpecializedFunction):
host_function = function.host_function
else:
host_function = function
if not hasattr(host_function, "artiq_embedded"):
raise ValueError("{} is not an embedded function".format(repr(host_function)))
# Extract function source.
embedded_function = host_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.
full_function_name = "{}.{}".format(module_name, host_function.__qualname__)
if isinstance(function, SpecializedFunction):
instance_type = function.instance_type
function_node.name = "_Z{}{}I{}{}Ezz".format(len(full_function_name), full_function_name,
len(instance_type.name), instance_type.name)
else:
function_node.name = "_Z{}{}zz".format(len(full_function_name), full_function_name)
# Record the function in the function map so that LLVM IR generator
# can handle quoting it.
self.embedding_map.store_function(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).lstrip()
while source_line.startswith("@") or source_line == "":
line += 1
source_line = linecache.getline(filename, line).lstrip()
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:
notes = []
notes.append(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)))
if loc is not None:
notes.append(self._call_site_note(loc, is_syscall))
with self.engine.context(*notes):
# 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)
Inferencer(engine=self.engine).visit(ast)
IntMonomorphizer(engine=self.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):
if isinstance(function, SpecializedFunction):
host_function = function.host_function
else:
host_function = function
ret_type = builtins.TNone()
if isinstance(host_function, pytypes.BuiltinFunctionType):
pass
elif (isinstance(host_function, pytypes.FunctionType) or \
isinstance(host_function, pytypes.MethodType)):
if isinstance(host_function, pytypes.FunctionType):
signature = inspect.signature(host_function)
else:
# inspect bug?
signature = inspect.signature(host_function.__func__)
if signature.return_annotation is not inspect.Signature.empty:
ret_type = self._extract_annot(host_function, signature.return_annotation,
"return type", loc, is_syscall=False)
else:
assert False
is_async = False
if hasattr(host_function, "artiq_embedded") and \
"async" in host_function.artiq_embedded.flags:
is_async = True
if not builtins.is_none(ret_type) and is_async:
note = diagnostic.Diagnostic("note",
"function called here", {},
loc)
diag = diagnostic.Diagnostic("fatal",
"functions that return a value cannot be defined as async RPCs", {},
self._function_loc(host_function.artiq_embedded.function),
notes=[note])
self.engine.process(diag)
function_type = types.TRPC(ret_type,
service=self.embedding_map.store_object(host_function),
async=is_async)
self.functions[function] = function_type
return function_type
def _quote_function(self, function, loc):
if isinstance(function, SpecializedFunction):
host_function = function.host_function
else:
host_function = function
if function in self.functions:
pass
elif not hasattr(host_function, "artiq_embedded") or \
(host_function.artiq_embedded.core_name is None and
host_function.artiq_embedded.portable is False and
host_function.artiq_embedded.syscall is None and
host_function.artiq_embedded.forbidden is False):
self._quote_rpc(function, loc)
elif host_function.artiq_embedded.function is not None:
if host_function.__name__ == "<lambda>":
note = diagnostic.Diagnostic("note",
"lambda created here", {},
self._function_loc(host_function.artiq_embedded.function))
diag = diagnostic.Diagnostic("fatal",
"lambdas cannot be used as kernel functions", {},
loc,
notes=[note])
self.engine.process(diag)
core_name = host_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": host_function.artiq_embedded.core_name},
self._function_loc(host_function.artiq_embedded.function),
notes=[note])
self.engine.process(diag)
self._quote_embedded_function(function,
flags=host_function.artiq_embedded.flags)
elif host_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 host_function.artiq_embedded.forbidden is not None:
diag = diagnostic.Diagnostic("fatal",
"this function cannot be called as an RPC", {},
self._function_loc(host_function),
notes=self._call_site_note(loc, is_syscall=False))
self.engine.process(diag)
else:
assert False
return self.functions[function]
def _quote(self, value, loc):
synthesizer = self._synthesizer(loc)
node = synthesizer.quote(value)
synthesizer.finalize()
if len(synthesizer.diagnostics) > 0:
for warning in synthesizer.diagnostics:
self.engine.process(warning)
return node