forked from M-Labs/artiq
transforms.devirtualizer.FunctionResolver: implement.
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@ -57,6 +57,7 @@ class Module:
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ref_period=ref_period)
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dead_code_eliminator = transforms.DeadCodeEliminator(engine=self.engine)
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local_access_validator = validators.LocalAccessValidator(engine=self.engine)
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devirtualizer = transforms.Devirtualizer()
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self.name = src.name
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self.globals = src.globals
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@ -65,9 +66,12 @@ class Module:
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monomorphism_validator.visit(src.typedtree)
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escape_validator.visit(src.typedtree)
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iodelay_estimator.visit_fixpoint(src.typedtree)
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devirtualizer.visit(src.typedtree)
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self.artiq_ir = artiq_ir_generator.visit(src.typedtree)
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dead_code_eliminator.process(self.artiq_ir)
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local_access_validator.process(self.artiq_ir)
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# for f in self.artiq_ir:
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# print(f)
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def build_llvm_ir(self, target):
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"""Compile the module to LLVM IR for the specified target."""
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@ -3,5 +3,6 @@ from .inferencer import Inferencer
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from .int_monomorphizer import IntMonomorphizer
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from .iodelay_estimator import IODelayEstimator
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from .artiq_ir_generator import ARTIQIRGenerator
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from .devirtualizer import Devirtualizer
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from .dead_code_eliminator import DeadCodeEliminator
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from .llvm_ir_generator import LLVMIRGenerator
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92
artiq/compiler/transforms/devirtualizer.py
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92
artiq/compiler/transforms/devirtualizer.py
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@ -0,0 +1,92 @@
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"""
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:class:`Devirtualizer` performs method resolution at
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compile time.
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Devirtualization is implemented using a lattice
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with three states: unknown → assigned once → diverges.
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The lattice is computed individually for every
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variable in scope as well as every
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(constructor type, field name) pair.
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"""
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from pythonparser import algorithm
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from .. import ir, types
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def _advance(target_map, key, value):
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if key not in target_map:
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target_map[key] = value # unknown → assigned once
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else:
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target_map[key] = None # assigned once → diverges
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class FunctionResolver(algorithm.Visitor):
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def __init__(self, variable_map):
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self.variable_map = variable_map
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self.in_assign = False
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self.scope_map = dict()
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self.scope = None
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self.queue = []
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def finalize(self):
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for thunk in self.queue:
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thunk()
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def visit_scope(self, node):
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old_scope, self.scope = self.scope, node
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self.generic_visit(node)
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self.scope = old_scope
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def visit_in_assign(self, node):
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self.in_assign = True
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self.visit(node)
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self.in_assign = False
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def visit_Assign(self, node):
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self.visit(node.value)
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self.visit_in_assign(node.targets)
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def visit_For(self, node):
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self.visit(node.iter)
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self.visit_in_assign(node.target)
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self.visit(node.body)
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self.visit(node.orelse)
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def visit_withitem(self, node):
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self.visit(node.context_expr)
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self.visit_in_assign(node.optional_vars)
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def visit_comprehension(self, node):
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self.visit(node.iter)
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self.visit_in_assign(node.target)
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self.visit(node.ifs)
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def visit_ModuleT(self, node):
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self.visit_scope(node)
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def visit_FunctionDefT(self, node):
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_advance(self.scope_map, (self.scope, node.name), node)
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self.visit_scope(node)
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def visit_NameT(self, node):
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if self.in_assign:
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# Just give up if we assign anything at all to a variable, and
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# assume it diverges.
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_advance(self.scope_map, (self.scope, node.id), None)
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else:
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# Copy the final value in scope_map into variable_map.
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key = (self.scope, node.id)
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def thunk():
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if key in self.scope_map:
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self.variable_map[node] = self.scope_map[key]
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self.queue.append(thunk)
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class Devirtualizer:
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def __init__(self):
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self.variable_map = dict()
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self.method_map = dict()
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def visit(self, node):
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resolver = FunctionResolver(self.variable_map)
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resolver.visit(node)
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resolver.finalize()
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# print(self.variable_map)
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