forked from M-Labs/artiq
compiler.embedding: cache attribute types (fixes #276).
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@ -295,26 +295,9 @@ class StitchingInferencer(Inferencer):
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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 _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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#
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# FIXME: We perform exhaustive checks of every known host object every
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# time an attribute access is visited, which is potentially quadratic.
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# This is done because it is simpler than performing the checks only when:
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# * a previously unknown attribute is encountered,
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# * a previously unknown host object is encountered;
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# which would be the optimal solution.
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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_value_type = None
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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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@ -354,10 +337,10 @@ class StitchingInferencer(Inferencer):
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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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is_method = True
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else:
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attributes = object_type.attributes
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is_method = False
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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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@ -407,6 +390,26 @@ class StitchingInferencer(Inferencer):
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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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