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compiler.embedding: cache attribute types (fixes #276).

This commit is contained in:
whitequark 2016-02-25 19:56:45 +00:00
parent d899d7307e
commit f838b8be49
1 changed files with 103 additions and 100 deletions
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203
artiq/compiler/embedding.py
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@ -295,6 +295,102 @@ class StitchingInferencer(Inferencer):
super().__init__(engine)
self.value_map = value_map
self.quote = quote
self.attr_type_cache = {}
def _compute_value_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):
# 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 = 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:
# 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)
def proxy_diagnostic(diag):
note = diagnostic.Diagnostic("note",
"while inferring a type for an attribute '{attr}' of a host object",
{"attr": attr_name},
loc)
diag.notes.append(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)
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,
@ -304,108 +400,15 @@ class StitchingInferencer(Inferencer):
# 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.
#
# FIXME: We perform exhaustive checks of every known host object every
# time an attribute access is visited, which is potentially quadratic.
# This is done because it is simpler than performing the checks only when:
# * a previously unknown attribute is encountered,
# * a previously unknown host object is encountered;
# which would be the optimal solution.
object_type = value_node.type.find()
for object_value, object_loc in self.value_map[object_type]:
attr_value_type = None
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):
# 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 = attr_value.__func__
is_method = True
else:
attributes = object_type.attributes
is_method = False
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:
# 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)
def proxy_diagnostic(diag):
note = diagnostic.Diagnostic("note",
"while inferring a type for an attribute '{attr}' of a host object",
{"attr": attr_name},
loc)
diag.notes.append(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)
attr_value_type = ast.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_value_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.