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f276409 dda583f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | # Hyper Flux Projection (HFP) — O(1)-memory causal language model
# Copyright (C) 2026 Kayrahan Yılmaz
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import dataclasses
@dataclasses.dataclass
class HFPConfig:
"""Feature flags and hyper-parameters for optional physics-inspired analogues.
All flags are *disabled* by default to keep the baseline model clean, fast
and honest: these physics-inspired aux terms are experimental hooks, NOT
load-bearing parts of the trained model. Enable one only to *test* whether
it adds value; when off, no wasted compute and no false "physics" claim.
(Onceki surumde hepsi True idi ama modeling bunlari loss'a hic baglamiyordu
-> olu hesap. Durust baseline icin kapatildi; ilham olarak deneye acik kalir.)
"""
# Feature toggles - deneysel, default kapali (opt-in)
ENABLE_CURVATURE: bool = False
ENABLE_ENTROPY_MAP: bool = False
ENABLE_DEFECT_FLAG: bool = False
ENABLE_COHERENCE: bool = False
ENABLE_CONSERVATION: bool = False
ENABLE_RYU_TAKAYANAGI: bool = False
ENABLE_5D_CURVATURE: bool = False
# Hyper-parameters (used when the feature is enabled)
REG_WEIGHT: float = 0.01 # gate-entropy regularisation weight
LANDMARK_MAX: int = 49 # max entries in landmark buffer
ENTROPY_THRESH: float = 0.25 # threshold for dynamic short-memory expansion
MAX_SHORT_LEN: int = 32 # maximum short-memory length (tokens)
GRAD_CLIP_VAL: float = 0.5 # gradient-clipping value per memory block
MIXED_PRECISION: bool = True # use torch.float16 for gate logits only
WARP_K: float = 0.5 # Witten propagator warp factor
# Global singleton configuration used throughout the package
config = HFPConfig()
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