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python
nano-gemini / src /config.py
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from __future__ import annotations
from dataclasses import dataclass, field
from typing import List
QUANTILES = [0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9]
MEDIAN_INDEX = 4
SIGMA_EPS = 1e-6
@dataclass
class GemmaConfig:
model_dims: int
n_heads: int
n_kv_heads: int
head_dim: int
intermediate_size: int
qk_norm: bool = True
sliding_window: int = 0
global_every: int = 6
@dataclass
class ResidualConfig:
hidden_dims: int = 128
output_dims: int = 64
@dataclass
class MeridianConfig:
name: str
size: str
gemma: GemmaConfig
n_layers: int
input_feature_dim: int = 192
input_patch_len: int = 32
output_patch_len: int = 64
quantiles: List[float] = field(default_factory=lambda: QUANTILES.copy())
max_variates: int = 128
max_context: int = 15360
max_horizon: int = 512
use_variate_attention: bool = True
residual: ResidualConfig = field(default_factory=ResidualConfig)
NanoConfig = MeridianConfig("Meridian-Nano","nano",
GemmaConfig(64,4,4,16,128), n_layers=4,
residual=ResidualConfig(128,64))
G6Config = MeridianConfig("Meridian-G6","g6",
GemmaConfig(4096,32,8,128,11008,sliding_window=64,global_every=6),
n_layers=28, residual=ResidualConfig(512,4096))