Source code for tket.passes

from __future__ import annotations

import json
from dataclasses import dataclass
from enum import Enum
from functools import cache
from pathlib import Path
from typing import TYPE_CHECKING

from hugr import Hugr
from hugr.passes.composable import (
    ComposablePass,
    ComposedPass,
    PassResult,
    implement_pass_run,
)
from hugr.passes.scope import GlobalScope, PassScope
from typing_extensions import deprecated

from tket import _state

from .._pattern import Rule, RuleMatcher
from .._state.build import OneQbGate, from_coms
from .._tket import optimiser as _optimiser
from .._tket import passes as _passes
from . import inline_funcs

if TYPE_CHECKING:
    from tket.util import PytketPassProto as PytketPass

__all__ = [
    "Cliffordize",
    "InlineFuncsHeuristic",
    "InlineFunctions",
    "ModifierResolverPass",
    "Normalize",
    "NormalizeGuppy",
    "PassResult",
    "PlatformTarget",
    "PytketHugrPass",
    "QSystemRebasePass",
    "_QSystemLLVMPass",
]


[docs] class PlatformTarget(Enum): """A hardware platform that passes can target. Passes use this to decide which platform-specific gate sets and extensions to produce or accept. See the individual passes (e.g. :py:class:`PytketHugrPass`) for the behaviour associated with each target. """ Tket = "tket" # Platform-agnostic target using only the base `tket` extensions. Sol = "sol" # Quantinuum Sol platform (base tket + Sol operations). Helios = "helios" # Quantinuum Helios platform (base tket + Helios operations).
[docs] @dataclass class PytketHugrPass(ComposablePass): pytket_passes: list[PytketPass] target: PlatformTarget = PlatformTarget.Tket _scope: PassScope = GlobalScope.PRESERVE_PUBLIC """ A class which provides an interface to apply pytket passes to Hugr programs. The user can create a :py:class:`PytketHugrPass` object from any serializable member of `pytket.passes`. The ``target`` selects which set of encoder/decoder extensions is used when translating between HUGRs and pytket circuits, controlling which operations get encoded as pytket commands and which pytket commands get decoded back into HUGR operations: - :py:attr:`PlatformTarget.Tket` (default): Only base ``tket`` operations are encoded. When decoding, pytket commands are translated into base ``tket.quantum`` operations, falling back to Helios qsystem operations for commands without a base counterpart (e.g. ``ZZPhase``). - :py:attr:`PlatformTarget.Sol`: Base ``tket`` and native Sol operations are encoded. When decoding, commands are translated into native Sol qsystem operations where possible, falling back to base ``tket.quantum`` operations. - :py:attr:`PlatformTarget.Helios`: Base ``tket`` and native Helios operations are encoded. When decoding, commands are translated into native Helios qsystem operations where possible, falling back to base ``tket.quantum`` operations. Operations without a valid encoder are kept as-is on a pytket roundtrip. Pytket commands without a valid decoder produce an unsupported ``TKET1.tk1op`` operation in the decoded HUGR. Parameters: - pytket_passes: The pytket passes to run. - target: The platform target selecting which encoder/decoder extension set to use when translating between HUGRs and pytket circuits. Defaults to the platform-agnostic :py:attr:`PlatformTarget.Tket`. """
[docs] def __init__( self, *pytket_passes: PytketPass, target: PlatformTarget = PlatformTarget.Tket, ) -> None: """Initialize a PytketHugrPass from a :py:class:`~pytket.passes.BasePass` instance.""" self.pytket_passes = list(pytket_passes) self.target = target
[docs] def with_scope(self, scope: PassScope) -> PytketHugrPass: """Set the scope configuration for the composed pass.""" self._scope = scope return self
[docs] def run(self, hugr: Hugr, *, inplace: bool = True) -> PassResult: """Run the pytket pass as a HUGR transform returning a PassResult.""" return implement_pass_run( self, hugr=hugr, inplace=inplace, copy_call=lambda h: self._run_pytket_pass_on_hugr(h, inplace), )
[docs] def then(self, other: ComposablePass) -> ComposablePass: """Perform another composable pass after this pass.""" if isinstance(other, PytketHugrPass) and self.target == other.target: combined = PytketHugrPass( *self.pytket_passes, *other.pytket_passes, target=self.target ) return combined.with_scope(self._scope) else: return ComposedPass(self, other)
def _run_pytket_pass_on_hugr(self, hugr: Hugr, inplace: bool) -> PassResult: tk_program = _state.CompilationState.from_python(hugr) for py_pass in self.pytket_passes: pass_json = json.dumps(py_pass.to_dict()) _passes.tket1_pass( tk_program._inner, pass_json, scope=self._scope, target=self.target.value, ) package = tk_program.to_python() new_hugr = package.modules[0] return PassResult.for_pass(self, hugr=new_hugr, inplace=inplace, result=None)
[docs] @dataclass class Normalize(ComposablePass): resolve_modifiers: bool = True simplify_cfgs: bool = True remove_tuple_untuple: bool = True constant_folding: bool = True remove_dead_funcs: bool = True inline_funcs: inline_funcs.InlineFuncsHeuristic | bool = True inline_dfgs: bool = True remove_redundant_order_edges: bool = True squash_borrows: bool = True _scope: PassScope = GlobalScope.PRESERVE_PUBLIC """Flatten the structure of a program to enable additional optimisations. This should normally be called first before other optimisations. Parameters: - resolve_modifiers: Whether to resolve modifier operations. - simplify_cfgs: Whether to simplify CFG control flow. - remove_tuple_untuple: Whether to remove tuple/untuple operations. - constant_folding: Whether to constant fold the program. - remove_dead_funcs: Whether to remove dead functions. - inline_dfgs: Whether to inline DFG operations. - inline_funcs: Heuristic for inlining function calls, or True for default heuristic, or False to disable inlining. - remove_redundant_order_edges: Whether to remove redundant order edges. - squash_borrows: Whether to squash return-borrow pairs on BorrowArrays. """
[docs] def run(self, hugr: Hugr, *, inplace: bool = True) -> PassResult: return implement_pass_run( self, hugr=hugr, inplace=inplace, copy_call=lambda h: self._normalize(h, inplace), )
[docs] def with_scope(self, _scope: PassScope) -> Normalize: """Set the scope of this pass and return self.""" self._scope = _scope return self
def _normalize(self, hugr: Hugr, inplace: bool) -> PassResult: tk_program = _state.CompilationState.from_python(hugr) self._run_tk(tk_program) package = tk_program.to_python() return PassResult.for_pass( self, hugr=package.modules[0], inplace=inplace, result=None ) def _run_tk(self, program: _state.CompilationState) -> _state.CompilationState: """Run the pass in the CompilationState TODO: This should be part of a protocol.""" inline_funcs_heuristic: inline_funcs.InlineFuncsHeuristic | None match self.inline_funcs: case True: inline_funcs_heuristic = inline_funcs.MaxSize(128) case False: inline_funcs_heuristic = None case _: inline_funcs_heuristic = self.inline_funcs _passes.normalize_guppy( program._inner, resolve_modifiers=self.resolve_modifiers, simplify_cfgs=self.simplify_cfgs, remove_tuple_untuple=self.remove_tuple_untuple, constant_folding=self.constant_folding, remove_dead_funcs=self.remove_dead_funcs, inline_dfgs=self.inline_dfgs, inline_funcs=inline_funcs_heuristic, remove_redundant_order_edges=self.remove_redundant_order_edges, squash_borrows=self.squash_borrows, scope=self._scope, ) return program
[docs] @deprecated("Use `Normalize` instead.") class NormalizeGuppy(Normalize): """Deprecated alias for :py:class:`Normalize`."""
@cache def _cliffordize_matcher() -> RuleMatcher: """Build the matcher containing the supported Cliffordize rules.""" replacements = [ ("T", "S"), ("Tdg", "Sdg"), ] rules = [ Rule( from_coms(OneQbGate(source)(0))._inner, from_coms(OneQbGate(replacement)(0))._inner, ) for source, replacement in replacements ] return RuleMatcher(rules)
[docs] @dataclass class Cliffordize(ComposablePass): """Replace supported non-Clifford operations with Clifford operations. This pass is intended for debugging and workflows that require Clifford-only circuits. It is not semantics-preserving. The currently supported replacements are: - `T` with `S` - `Tdg` with `Sdg` Other non-Clifford operations, including arbitrary rotations, symbolic rotations, `PhasedX`, and `ZZPhase`, are left unchanged. """ _scope: PassScope = GlobalScope.PRESERVE_PUBLIC
[docs] def run(self, hugr: Hugr, *, inplace: bool = True) -> PassResult: """Run the pass and return the transformed HUGR and rewrite count.""" return implement_pass_run( self, hugr=hugr, inplace=inplace, copy_call=lambda h: self._cliffordize(h, inplace), )
[docs] def with_scope(self, scope: PassScope) -> Cliffordize: """Set the scope of this pass and return self.""" self._scope = scope return self
def _cliffordize(self, hugr: Hugr, inplace: bool) -> PassResult: tk_program = _state.CompilationState.from_python(hugr) rewrite_count = self._run_tk(tk_program) package = tk_program.to_python() return PassResult.for_pass( self, hugr=package.modules[0], inplace=inplace, result=rewrite_count, ) def _run_tk(self, program: _state.CompilationState) -> int: """Run the pass on a CompilationState and return the rewrite count.""" return _cliffordize_matcher().apply_all_matches_once( program._inner, scope=self._scope, )
[docs] @dataclass class InlineFunctions(ComposablePass): """Inline acyclic function calls below the selected scope. Parameters: - heuristic: Heuristic used to choose which non-recursive functions to inline. Defaults to `MaxSize(128)`. """ heuristic: inline_funcs.InlineFuncsHeuristic = inline_funcs.MaxSize(128) # noqa: RUF009 _scope: PassScope = GlobalScope.PRESERVE_PUBLIC
[docs] def run(self, hugr: Hugr, *, inplace: bool = True) -> PassResult: return implement_pass_run( self, hugr=hugr, inplace=inplace, copy_call=lambda h: self._inline_functions(h, inplace), )
[docs] def with_scope(self, _scope: PassScope) -> InlineFunctions: """Set the scope of this pass and return self.""" self._scope = _scope return self
def _inline_functions(self, hugr: Hugr, inplace: bool) -> PassResult: tk_program = _state.CompilationState.from_python(hugr) _passes.inline_functions( tk_program._inner, heuristic=self.heuristic, scope=self._scope, ) package = tk_program.to_python() return PassResult.for_pass( self, hugr=package.modules[0], inplace=inplace, result=None )
def _greedy_depth_reduce(program: _state.CompilationState) -> int: return _passes.greedy_depth_reduce(program._inner) def _badger_optimise( program: _state.CompilationState, optimiser: _optimiser.BadgerOptimiser | Path | None = None, *, max_threads: int | None = None, timeout: int | None = None, progress_timeout: int | None = None, max_circuit_count: int | None = None, log_dir: Path | None = None, ) -> None: """Optimise a circuit using the Badger optimiser. HyperTKET's best attempt at optimising a circuit using circuit rewriting. If `optimiser` is a path, it should point to a file containing a Badger ECC set. If `optimiser` is None, the default ECC set will be used. Otherwise, the provided BadgerOptimiser instance will be used. The input circuit is expected to be in the Nam gate set, i.e. CX + Rz + H. Mutates the circuit in place. Will use at most `max_threads` threads (plus a constant). Defaults to the number of CPUs available. The optimisation will terminate at the first of the following timeout criteria, if set: - `timeout` seconds (default: 15min) have elapsed since the start of the optimisation - `progress_timeout` (default: None) seconds have elapsed since progress in the cost function was last made - `max_circuit_count` (default: None) circuits have been explored. Log files will be written to the directory `log_dir` if specified. """ badger_optimiser: _optimiser.BadgerOptimiser if optimiser is None: try: import tket_eccs except ImportError: raise ValueError( "The default rewriter is not available. Please specify a path to a rewriter or install tket-eccs." ) ecc = tket_eccs.nam_6_3() badger_optimiser = _optimiser.BadgerOptimiser.load_precompiled(ecc) elif isinstance(optimiser, Path): badger_optimiser = _optimiser.BadgerOptimiser.load_precompiled(optimiser) else: badger_optimiser = optimiser _passes.badger_optimise( program._inner, optimiser=badger_optimiser, max_threads=max_threads, timeout=timeout, progress_timeout=progress_timeout, max_circuit_count=max_circuit_count, log_dir=log_dir, )
[docs] @dataclass class ModifierResolverPass(ComposablePass): """A pass to resolve Guppy modifiers (control, dagger, power). Original function nodes replaced by solved modified versions may be removed when no longer needed and allowed by the pass scope. Nodes whose interface is preserved by the scope are kept. """ _scope: PassScope = GlobalScope.PRESERVE_PUBLIC
[docs] def run(self, hugr: Hugr, *, inplace: bool = True) -> PassResult: return implement_pass_run( self, hugr=hugr, inplace=inplace, copy_call=lambda h: self._resolve(h, inplace), )
[docs] def with_scope(self, scope: PassScope) -> ModifierResolverPass: """Set the scope of this pass and return self.""" self._scope = scope return self
def _resolve(self, hugr: Hugr, inplace: bool) -> PassResult: tk_program = _state.CompilationState.from_python(hugr) self._run_tk(tk_program) package = tk_program.to_python() return PassResult.for_pass( self, hugr=package.modules[0], inplace=inplace, result=None ) def _run_tk(self, program: _state.CompilationState) -> _state.CompilationState: """Run the pass in the CompilationState""" _passes.resolve_modifiers( program._inner, scope=self._scope, ) return program
[docs] @dataclass(kw_only=True) class QSystemRebasePass(ComposablePass): """Convert quantum operations to QSystem operations. Parameters: - resolve_modifiers: Whether to resolve Guppy modifiers. - lower_drops: Whether to lower qubit drops to QSystem operations. - hide_funcs: Whether to mark generated helper functions as private. """ resolve_modifiers: bool = True lower_drops: bool = True hide_funcs: bool = True _scope: PassScope = GlobalScope.PRESERVE_PUBLIC
[docs] def run(self, hugr: Hugr, *, inplace: bool = True) -> PassResult: return implement_pass_run( self, hugr=hugr, inplace=inplace, copy_call=lambda h: self._qsystem_rebase(h, inplace), )
[docs] def with_scope(self, scope: PassScope) -> QSystemRebasePass: """Set the scope of this pass and return self.""" self._scope = scope return self
def _qsystem_rebase(self, hugr: Hugr, inplace: bool) -> PassResult: tk_program = _state.CompilationState.from_python(hugr) self._run_tk(tk_program) package = tk_program.to_python() return PassResult.for_pass( self, hugr=package.modules[0], inplace=inplace, result=None ) def _run_tk(self, program: _state.CompilationState) -> _state.CompilationState: """Run the pass in the CompilationState""" _passes.qsystem_rebase_pass( program._inner, resolve_modifiers=self.resolve_modifiers, lower_drops=self.lower_drops, hide_funcs=self.hide_funcs, scope=self._scope, ) return program
@dataclass(kw_only=True) class _QSystemLLVMPass(ComposablePass): """Prepare a QSystem program for LLVM lowering. This is normally called automatically by the tools before LLVM lowering. Parameters: - constant_fold: Whether to perform constant folding. - monomorphize: Whether to monomorphize generic functions. - force_order: Whether to enforce total ordering of all HUGR operations. """ constant_fold: bool = True monomorphize: bool = True force_order: bool = True _scope: PassScope = GlobalScope.PRESERVE_PUBLIC def run(self, hugr: Hugr, *, inplace: bool = True) -> PassResult: return implement_pass_run( self, hugr=hugr, inplace=inplace, copy_call=lambda h: self._qsystem_llvm(h, inplace), ) def with_scope(self, scope: PassScope) -> _QSystemLLVMPass: """Set the scope of this pass and return self.""" self._scope = scope return self def _qsystem_llvm(self, hugr: Hugr, inplace: bool) -> PassResult: tk_program = _state.CompilationState.from_python(hugr) self._run_tk(tk_program) package = tk_program.to_python() return PassResult.for_pass( self, hugr=package.modules[0], inplace=inplace, result=None ) def _run_tk(self, program: _state.CompilationState) -> _state.CompilationState: """Run the pass in the CompilationState""" _passes.qsystem_llvm_pass( program._inner, constant_fold=self.constant_fold, monomorphize=self.monomorphize, force_order=self.force_order, scope=self._scope, ) return program