mirror of
https://github.com/blackboxprogramming/BlackRoad-Operating-System.git
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0108860bff
Create comprehensive research-lab pack structure with mathematical and quantum computing modules from blackroad-prism-console: Math Modules: - hilbert_core.py: Hilbert space symbolic reasoning - collatz/: Distributed Collatz conjecture verification - linmath/: Linear mathematics C library - lucidia_math_forge/: Symbolic proof engine - lucidia_math_lab/: Experimental mathematics Quantum Modules: - lucidia_quantum/: Quantum core - quantum_engine/: Circuit simulation Experiments: - br_math/: Gödel gap, quantum experiments Includes pack.yaml manifest and comprehensive README. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
38 lines
1.3 KiB
Python
38 lines
1.3 KiB
Python
"""PyTorch bridge for Quantum Neural Networks."""
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from __future__ import annotations
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import os
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import random
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from typing import Any
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import numpy as np
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import torch
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from qiskit_machine_learning.connectors import TorchConnector
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from qiskit_machine_learning.neural_networks import NeuralNetwork
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class QModule(torch.nn.Module):
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"""Wrap a Qiskit ``NeuralNetwork`` as a ``torch.nn.Module``."""
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def __init__(self, qnn: NeuralNetwork, seed: int | None = 42) -> None:
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super().__init__()
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if seed is not None:
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random.seed(seed)
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np.random.seed(seed)
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torch.manual_seed(seed)
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self.qnn = qnn
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self.connector = TorchConnector(neural_network=self.qnn)
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def forward(self, x: torch.Tensor) -> torch.Tensor:
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if not isinstance(x, torch.Tensor): # pragma: no cover - defensive
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raise TypeError("expected torch.Tensor")
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return self.connector(x)
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def to(self, device: Any) -> "QModule": # type: ignore[override]
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if device not in {"cpu", torch.device("cpu")}: # pragma: no cover - gpu path
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if os.getenv("LUCIDIA_QML_GPU", "off").lower() not in {"1", "true", "on"}:
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raise RuntimeError("GPU disabled")
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self.connector.to(device)
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return super().to(device)
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