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Q-TensorFormer v4: Quantum-Enhanced Tensor Network LLM Compression.
Now with:
- QKAN integration (DARUAN activations)
- Energy-aware training (hardware-specific cost models)
- Pareto frontier tracking
- Budget-constrained optimization
"""
from .config import (
ModelConfig, TrainingConfig, BudgetConfig, ExperimentConfig,
PRESETS, tiny_config, small_config, medium_config, production_config,
)
from .tensor_layers import TTLinear, TTFeedForward, factorize_dim
from .quantum_layers import (
QuantumFeatureEncoder, QuantumKernelAttention, EntanglementMonitor,
)
from .router import QuantumRouter
from .scheduler import RankScheduler, EntropyDrivenScheduler
from .blocks import HybridBlock, TensorOnlyBlock
from .models import QTensorFormer, DenseBaseline, create_model
from .budget import BudgetTracker, EnergyEstimator
from .training import Trainer, DistillationTrainer, create_optimizer, create_scheduler
# V4 additions
from .qkan import DARUAN, QKANLayer, HQKANFFN, QKANEmbedding, create_qkan_ffn
from .energy_v4 import (
EnergyEstimatorV4, ParetoTracker, HARDWARE_PROFILES,
estimate_model_energy, HardwareProfile,
)
__version__ = "4.0.0"
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