File size: 6,394 Bytes
a066584 | 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 | # Copyright 2026 Modilify
# SPDX-License-Identifier: LicenseRef-Modilify-Open-Model-1.0
"""Serializable configuration for the native Modilify Mk1 MLX runtime."""
from __future__ import annotations
from dataclasses import dataclass, field
import json
from pathlib import Path
from typing import Any
from mlx_vlm.models.diffusion_gemma.config import ModelConfig, TextConfig
from mlx_vlm.models.gemma4.config import VisionConfig
from mlx_vlm.models.qwen3_vl.config import _config_kwargs, _maybe_deserialize_config
MODEL_TYPE = "modilify_mk1"
TEXT_MODEL_TYPE = "modilify_mk1_text"
def _require_model_type(payload: dict[str, Any], expected: str) -> None:
actual = payload.get("model_type")
if actual != expected:
raise ValueError(
f"Expected model_type {expected!r}, got {actual!r}. "
"This runtime only loads native Modilify Mk1 checkpoints."
)
@dataclass
class ModilifyMk1Config:
"""Mk1 inference configuration. ``model_type`` is always ``modilify_mk1``."""
text_config: TextConfig
vision_config: VisionConfig | None = None
model_type: str = MODEL_TYPE
boi_token_id: int = 255999
eoi_token_id: int = 258882
image_token_id: int = 258880
video_token_id: int | None = None
pad_token_id: int = 0
bos_token_id: int = 2
eos_token_id: list[int] | int = field(default_factory=lambda: [1, 106])
initializer_range: float = 0.02
canvas_length: int = 256
denoise_temperature: float = 0.8
commit_failure_budget: float = 0.2
jump_failure_budget: float = 2.0
jump_on_no_progress_after: int = 12
max_ponder_steps: int = 64
min_trajectory_progress: float = 0.005
latent_dim: int = 1536
latent_dropout: float = 0.0
latent_local_attention_window: int = 128
latent_memory_slots: int = 64
latent_num_heads: int = 16
latent_num_layers: int = 4
turn_end_token_id: int = 106
repetition_penalty: float = 1.0
dtype: str | None = "bfloat16"
generation_config: dict[str, Any] | None = None
def __post_init__(self) -> None:
if self.model_type != MODEL_TYPE:
raise ValueError(
f"ModilifyMk1Config.model_type must be {MODEL_TYPE!r}, "
f"got {self.model_type!r}."
)
if isinstance(self.text_config, dict):
text_payload = dict(self.text_config)
text_payload.setdefault("model_type", TEXT_MODEL_TYPE)
self.text_config = TextConfig(
**_config_kwargs(TextConfig, text_payload)
)
@classmethod
def from_dict(cls, payload: dict[str, Any]) -> "ModilifyMk1Config":
payload = dict(payload)
_require_model_type(payload, MODEL_TYPE)
text_payload = dict(payload.get("text_config") or {})
text_payload.setdefault("model_type", TEXT_MODEL_TYPE)
payload["text_config"] = TextConfig(
**_config_kwargs(TextConfig, text_payload)
)
if payload.get("vision_config") is not None:
payload["vision_config"] = _maybe_deserialize_config(
VisionConfig, payload.get("vision_config")
)
return cls(**_config_kwargs(cls, payload))
@classmethod
def from_json(cls, path: str | Path) -> "ModilifyMk1Config":
with Path(path).open(encoding="utf-8") as handle:
return cls.from_dict(json.load(handle))
def to_dict(self) -> dict[str, Any]:
def _as_dict(value: Any) -> Any:
if hasattr(value, "to_dict"):
return value.to_dict()
if hasattr(value, "__dict__") and not isinstance(
value, (str, int, float, bool, list, dict, type(None))
):
return {
key: _as_dict(item)
for key, item in vars(value).items()
if not key.startswith("_")
}
return value
return {
"model_type": MODEL_TYPE,
"text_config": _as_dict(self.text_config),
"vision_config": None
if self.vision_config is None
else _as_dict(self.vision_config),
"boi_token_id": self.boi_token_id,
"eoi_token_id": self.eoi_token_id,
"image_token_id": self.image_token_id,
"video_token_id": self.video_token_id,
"pad_token_id": self.pad_token_id,
"bos_token_id": self.bos_token_id,
"eos_token_id": self.eos_token_id,
"initializer_range": self.initializer_range,
"canvas_length": self.canvas_length,
"denoise_temperature": self.denoise_temperature,
"commit_failure_budget": self.commit_failure_budget,
"jump_failure_budget": self.jump_failure_budget,
"jump_on_no_progress_after": self.jump_on_no_progress_after,
"max_ponder_steps": self.max_ponder_steps,
"min_trajectory_progress": self.min_trajectory_progress,
"latent_dim": self.latent_dim,
"latent_dropout": self.latent_dropout,
"latent_local_attention_window": self.latent_local_attention_window,
"latent_memory_slots": self.latent_memory_slots,
"latent_num_heads": self.latent_num_heads,
"latent_num_layers": self.latent_num_layers,
"turn_end_token_id": self.turn_end_token_id,
"repetition_penalty": self.repetition_penalty,
"dtype": self.dtype,
}
def trunk_model_config(self) -> ModelConfig:
"""Build the borrowed trunk config object used only inside this package."""
return ModelConfig(
text_config=self.text_config,
vision_config=self.vision_config,
model_type=self.model_type,
boi_token_id=self.boi_token_id,
eoi_token_id=self.eoi_token_id,
image_token_id=self.image_token_id,
video_token_id=self.video_token_id,
initializer_range=self.initializer_range,
canvas_length=self.canvas_length,
eos_token_id=self.eos_token_id,
generation_config=self.generation_config,
dtype=self.dtype,
)
@property
def vocab_size(self) -> int:
return int(self.text_config.vocab_size)
@property
def hidden_size(self) -> int:
return int(self.text_config.hidden_size)
|