default.tensor can preprocess with graph based decomposition system
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This commit refactors the preprocess.decompose function to improve its integration with the new graph-based decomposition system and adds support for device-specific parameters. Key Changes: - Enhanced decompose() function to accept device_wires and target_gates parameters - Improved work wire calculation using set operations: len(set(device_wires) - set(tape.wires)) - Removed redundant num_available_work_wires and graph_solution parameters (computed internally) - Added preprocess_decompose_plxpr_to_plxpr function for PLXPR integration - Updated function signature and internal logic for better parameter handling Testing: - Added comprehensive test coverage for new device_wires and target_gates functionality - Added parametrized tests for work wire calculation with various edge cases - Added fixtures for graph decomposition backward compatibility testing - Used spy-based testing for safe parameter verification without mocking core functionality Code Quality: - Added __all__ export list for proper module interface definition - Fixed pylint warnings and ensured CI/CD compatibility - Improved exception handling with explicit re-raising patterns - Enhanced imports and dependencies for graph-based decomposition Backward Compatibility: - Maintained full backward compatibility for existing decompose() calls - Legacy behavior preserved when device_wires/target_gates not provided - Comprehensive fixture-based testing ensures both old and new modes work correctly
Co-authored-by: Christina Lee <[email protected]>
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JerryChen97
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Sep 12, 2025
albi3ro
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albi3ro
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albi3ro
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NQ part has been spawn at #8260 |
JerryChen97
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default.tensor can preprocess with graph based decomposition system
JerryChen97
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Sep 17, 2025
PietropaoloFrisoni
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Sep 17, 2025
JerryChen97
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astralcai
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Context:
Previously, the
default.tensordevice did not integrate with the new graph-based decomposition system introduced in PennyLane. This system allows for more intelligent circuit compilation by selecting the best decomposition strategy based on available hardware resources (e.g., choosing a gate implementation that doesn't require extra "work" wires if the device has none to spare). This PR updates the device's preprocessing pipeline to leverage this new, more efficient decomposition logic.Description of the Change:
default_tensor.pyto correctly configure and include the graph decomposition transform in its preprocessing pipeline. This involves passing necessary device information, likedevice_wiresandtarget_gates, to thedecomposefunction.TestPreprocessingTransforms, to validate the structure and behavior of the updated preprocessing pipeline. These tests ensure that:decomposetransform is correctly included in the pipeline.device_wiresandtarget_gates.@pytest.mark.usefixtures("enable_and_disable_graph_decomp")fixture, ensuring they run with both the old and new decomposition methods for backward compatibility and robustness.Benefits:
Possible Drawbacks:
Related GitHub Issues:
[sc-97955] [sc-97952]