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919fd68 | 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 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 | """Resynthesis configuration β all fields are INITIAL VALUES, NOT CAPS.
``num_layers``, ``num_experts``, ``recursive_steps``, and domains are SEEDS
that grow on observed demand. Termination is confidence-based (NeuralStopGate
+ utility/contradiction gates), never host-imposed caps.
The ONE allowed backstop is the malfunction-guardrail (anti-infinite-loop),
commented as guardrail-not-cap. Picking a bigger number is still a cap.
"""
from __future__ import annotations
from dataclasses import dataclass
# Resynthesis-owned vocabulary/feature parent (frozen, additive-only).
# Its immutable inherited tensor geometry is hidden_size=4096, 32 layers,
# linear_attention + full_attention hybrid, vocab=248320, native >4M context.
#
# AUTHORITY CONTRACT: these tensors are a small immutable lego in the larger
# NoNE/RBO/Fabric graph. They may tokenize, project additive hidden state into
# the inherited vocabulary, and seed feature/context tensors. Parent logits,
# confidence, answer selection, and parent-relative retention are diagnostics
# only and must never select, score, stop, retain, or veto an additive result.
RESYNTHESIS_HIDDEN_SIZE = 4096
RESYNTHESIS_NUM_HIDDEN_LAYERS = 32
RESYNTHESIS_PROJECTION_VOCAB_SIZE = 248_320
# Long-context STACK+COMPOSE (compose, do not replace):
# absolute KV order + Dual Chunk β parent RoPE indices + trained parent
# YaRN live + exact online-softmax long pool over every hidden position.
# Context-intent C, action A, and relational connectivity R:
# Science attention composes C_i K_j, Q_i C_j, and R_i^Q R_j^K over the
# preserved Q_i K_j path. C is model-owned hidden-plus-intent-plus-action
# state: ``C = c_proj(hidden) + intent_c_proj(intent) + gate_a * action_c_proj(action)``.
# R is conditioned by the NoNE router's selected expert-intent tensor. Exact
# online-softmax tiling preserves every causal edge without a resident N x N
# score table. Long pools compose intent and action as separate additive
# ``QΒ·C`` and ``QΒ·A`` channels over the baseline ``QΒ·K`` path. These are
# trained graph tensors, never host routing flags.
# Long-pool C may be [batch, sequence] or [batch, sequence, hidden]; there is
# no host cap on C/R width or sequence length (uncapped-policy: intentional).
# Dual-Chunk keeps RoPE inside the pretrained band; do not YaRN-stretch.
RESYNTHESIS_MAX_POSITION_EMBEDDINGS = 4_194_304
# Native attention must exceed the trained 4M floor. This is a proof/geometry
# extent, not a floor+tile host cap: runtime admission observes absolute KV
# extent while Dual Chunk preserves the parent's folded RoPE band and exact
# KV-addressed history.
RESYNTHESIS_NATIVE_CONTEXT_FLOOR = 4_194_304
NATIVE_ATTENTION_POSITION_APERTURE = 100_000_001
DUAL_CHUNK_PRETRAIN_LENGTH = 262_144
DUAL_CHUNK_LOCAL_SIZE = 8_192
# Dual Chunk keeps parent RoPE inside the pretrained band; do not YaRN-stretch.
PRETRAINED_ROPE_BAND_TOKENS = DUAL_CHUNK_PRETRAIN_LENGTH
# Execution tile width for parent/additive online-softmax pools. One tile equals
# one Dual-Chunk successive window so prefill schedule and RoPE localization
# stay coherent at 4M+ tokens. ``validate_native_context_admission`` validates
# tensor shape/sign and observes full absolute KV extent; it must not silently
# truncate or reject merely because the prompt passed the old floor+tile value.
RESYNTHESIS_ONLINE_SOFTMAX_TILE_TOKENS = 8_192
# Native tiled prefill for the frozen parent backbone: long prompts are fed to
# the complete parent graph in cache-preserving tiles so activations stay
# bounded. Every token updates all 24 trained globally recurrent linear-
# attention layers. Beyond the pretrained band, the eight full-attention
# layers retain a bounded hot K/V window; no input token is dropped, rejected,
# or truncated. One prefill tile equals one Dual-Chunk successive window and
# one online-softmax pool window, keeping parent RoPE localization, recurrent
# state, prefill scheduling, and the additive long pool coherent.
RESYNTHESIS_NATIVE_PREFILL_TILE_TOKENS = 8_192
# Bounded activation geometry, not a context cap: every source token first
# executes the complete parent and participates in an attended segment summary
# before the additive Fabric/NoNE prefill traversal.
RESYNTHESIS_NATIVE_PREFILL_SUMMARIES_PER_TILE = 4
RESYNTHESIS_NUM_ATTENTION_HEADS = 16
RESYNTHESIS_NUM_KEY_VALUE_HEADS = 4
RESYNTHESIS_INTERMEDIATE_SIZE = 12_288
RESYNTHESIS_HEAD_DIM = 256
RESYNTHESIS_FULL_ATTENTION_INTERVAL = 4
RESYNTHESIS_FULL_ATTENTION_LAYERS = (
RESYNTHESIS_NUM_HIDDEN_LAYERS // RESYNTHESIS_FULL_ATTENTION_INTERVAL
)
RESYNTHESIS_LINEAR_ATTENTION_LAYERS = (
RESYNTHESIS_NUM_HIDDEN_LAYERS - RESYNTHESIS_FULL_ATTENTION_LAYERS
)
# Long prompts retain the parent's globally recurrent linear-attention state at
# every layer while bounding the resident full-attention K/V to one trained
# Dual-Chunk local window. The pretrained-band boundary selects the storage
# backend; it does not reject, truncate, route, or stop a prompt.
RESYNTHESIS_NATIVE_HYBRID_ACTIVATION_TOKENS = DUAL_CHUNK_PRETRAIN_LENGTH
RESYNTHESIS_NATIVE_HOT_KV_TOKENS = DUAL_CHUNK_LOCAL_SIZE
# Resynthesis glyph-plane dimension.
GLYPH_DIM = 168
# Public Release 188 resolves its immutable lexical parent and tokenizer
# directly from repository-relative files. Historical lab manifests, receipts,
# worktree paths, and source fingerprints are deliberately absent here.
RESYNTHESIS_NATIVE_PARENT_GENERATION = "release_188"
RESYNTHESIS_NATIVE_PARENT_ROOT = "weights/safetensors"
RESYNTHESIS_NATIVE_PARENT_RUNTIME_ROOT = ""
RESYNTHESIS_NATIVE_PARENT_MANIFEST_PATH = ""
RESYNTHESIS_NATIVE_PARENT_MANIFEST_SHA256 = ""
RESYNTHESIS_NATIVE_PARENT_MODEL_SHA256 = ""
RESYNTHESIS_PARENT_CHECKPOINT_MANIFEST_PATH = ""
RESYNTHESIS_PARENT_CHECKPOINT_MANIFEST_SHA256 = ""
_RESYNTHESIS_PARENT_ARTIFACT_PACKAGE = ""
# The public runtime uses the Transformers tokenizer files under ``tokenizer/``.
# Fastokens remains an optional acceleration implementation rather than a
# release-owned artifact or admission requirement.
RESYNTHESIS_FASTOKENS_VERSION = "0.2.1"
RESYNTHESIS_FASTOKENS_COMMIT = ""
RESYNTHESIS_FASTOKENS_ROOT = ""
RESYNTHESIS_FASTOKENS_SITE = ""
RESYNTHESIS_FASTOKENS_RECEIPT_PATH = ""
RESYNTHESIS_FASTOKENS_RECEIPT_SHA256 = ""
RESYNTHESIS_FASTOKENS_SOURCE_ARCHIVE_SHA256 = ""
RESYNTHESIS_FASTOKENS_WHEEL_PATH = ""
RESYNTHESIS_FASTOKENS_WHEEL_SHA256 = ""
RESYNTHESIS_PARENT_TOKENIZER_SHA256 = ""
RESYNTHESIS_PARENT_TOKENIZER_VOCAB_SIZE = 248_077
@dataclass(frozen=True)
class ResynthesisConfig:
"""Top-level config for the Resynthesis reasoning-science model.
``hidden_size`` names the frozen Resynthesis vocabulary/feature projection
seam (4096), not the capacity of the complete additive model. Successor
generations may add wider learned transfer, page, expert, and reasoning
structure around that seam through explicit prefix-preserving migrations.
Everything outside the immutable projection interface is an initial seed.
"""
# ββ Frozen vocabulary/feature lego (never answer or learning authority) ββ
hidden_size: int = RESYNTHESIS_HIDDEN_SIZE
# ``None`` starts the accepted additive generation at the complete current
# feature seam. An explicit positive value is its initial materialized
# knowledge-transfer rank, never a maximum. A retained successor may widen
# this rank while keeping every accepted row/column byte-exact.
knowledge_transfer_dim: int | None = None
# Rank of the additive hidden-to-vocabulary residual pathway. ``None``
# derives the initial accepted rank from the model-owned knowledge-transfer
# geometry, never from a fixed host constant. An explicit positive value is
# likewise only an initial materialized rank: retained successors may widen
# it through prefix-exact checkpoint migration, and no production path may
# treat it as a maximum.
logit_residual_rank: int | None = None
base_model_dir: str = RESYNTHESIS_NATIVE_PARENT_ROOT
native_parent_manifest_path: str = ""
native_parent_manifest_sha256: str = ""
# The graph parent predates the current rolling Resynthesis schema. These source
# fields describe the historical reconstruction lineage for diagnostics;
# they may change as the runtime improves and never veto load, resume, or
# promotion. Exact model/checkpoint tensor identities remain authoritative.
parent_runtime_source_dir: str = ""
parent_source_fingerprint_path: str = ""
parent_source_fingerprint_sha256: str = ""
parent_source_id: str = ""
parent_source_bundle_sha256: str = ""
parent_source_recovery_manifest_path: str = ""
parent_source_recovery_manifest_sha256: str = ""
parent_rbo_outcome_source_path: str = ""
parent_rbo_outcome_source_sha256: str = ""
parent_integrated_source_sha256: str = ""
parent_rbo_source_sha256: str = ""
parent_none_fabric_source_sha256: str = ""
parent_loader_source_sha256: str = ""
# The 553-tensor capability payload is isolated from the authoritative
# 1,043-tensor parent and fused by a separately trained Resynthesis surface.
# The directory is audit provenance only: the executable compatibility
# graph is pinned inside Resynthesis and never imports this mutable worktree.
legacy_capability_source_dir: str = ""
legacy_capability_source_sha256: str = ""
base_weights: str = "model.safetensors"
tokenizer_path: str = "tokenizer.json"
config_path: str = "config.json"
vocab_size: int = RESYNTHESIS_PROJECTION_VOCAB_SIZE
# Exact lexical rows currently owned by the verified Fastokens BPE. The
# frozen projection is padded to ``vocab_size`` for tensor geometry, so
# these values are deliberately distinct. This is not a generation cap:
# successor tokenizers may append rows while preserving every inherited
# token ID, and the additive vocabulary bridge maps any remaining physical
# projection rows through model-owned tensors before native selection.
tokenizer_vocab_size: int = RESYNTHESIS_PARENT_TOKENIZER_VOCAB_SIZE
# Immutable inherited token-ID prefix. Successor tokenizer artifacts may
# append rows beyond both this prefix and the physical projection width,
# but they may never renumber or replace these IDs. Keeping the prefix
# separate from the active lexical size makes vocabulary growth explicit
# without turning inherited projection geometry into a cap.
tokenizer_prefix_vocab_size: int = (
RESYNTHESIS_PARENT_TOKENIZER_VOCAB_SIZE
)
# Initial materialized rank of the learned projection-row-to-lexical-row
# bridge. This is a growth seed, not a ceiling: successor generations may
# widen it with prefix-exact checkpoint migration. The bridge prevents
# projection-only coordinates from becoming undecodable token IDs while
# retaining their trainable signal inside the Resynthesis graph.
vocabulary_transfer_rank: int = 16
# ββ Additive science MoE stack (SEEDS β grow on demand, no ceiling) ββ
num_layers: int = 4 # INITIAL count β grows via growth tool
num_experts: int = 8 # INITIAL count β grows via growth tool
expert_hidden_size: int = 1024
memory_slots: int = 1 # minimal seed row; grows on demand
attention_heads: int = 16
mhc_heads: int = 8
# Boundary provenance only. This does not route or stop the model; it binds
# a cold-reloaded graph to a checkpointed geometry migration.
geometry_migrated: bool = False
recursive_steps: int = 0 # 0 = RBO confidence controls traversal (no cap)
residual_init: float = 0.02
# This scale gates an additional *additive-hidden* low-rank update. It no
# longer blends parent logits into the answer surface; the frozen lm_head is
# used only as the shared vocabulary projection over trained additive state.
logit_residual_init: float = -4.0
# Parent-relative KL/identity retention is forbidden. Retention compares
# against the prior accepted additive generation at the explicit learning
# boundary, never against the hollow frozen vocabulary parent.
kl_anchor_weight: float = 0.0
kl_anchor_warmup_steps: int = 100
glyph_input_dim: int = GLYPH_DIM
# ββ Identity ββ
identity_name: str = "Resynthesis"
identity_creator: str = "Namenotfound.ai by Wendell Adams"
# ββ Execution grounding (default ON) ββ
execution_grounding: bool = True
# ββ Uncapped policy marker ββ
uncapped_policy: str = "intentional"
# ββ Model artifacts root ββ
artifacts_dir: str = ".nnf-resynthesis/models"
# ββ Exact public-release relocation coordinates ββ
# These paths may move in an exported repository. Their corresponding
# identities remain the immutable native-parent/Fastokens authority.
native_parent_model_sha256: str = ""
parent_checkpoint_manifest_path: str = ""
parent_checkpoint_manifest_sha256: str = ""
fastokens_receipt_path: str = ""
fastokens_receipt_sha256: str = ""
fastokens_site_path: str = ""
fastokens_wheel_path: str = ""
fastokens_wheel_sha256: str = ""
fastokens_source_archive_sha256: str = ""
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