| """Frozen source-specific reference-storage contract; no native FP4 runtime.""" |
| import math |
| from pathlib import PurePosixPath |
| from typing import Literal |
| from pydantic import BaseModel,ConfigDict,Field,model_validator |
|
|
| class Strict(BaseModel): |
| model_config=ConfigDict(extra='forbid',frozen=True) |
|
|
| class FileDigest(Strict): |
| sha256:str=Field(pattern=r'^[0-9a-f]{64}$') |
| size_bytes:int=Field(ge=0) |
|
|
| class Tensor(Strict): |
| shape:tuple[int,...] |
| dtype:Literal['bfloat16','float32','float16','int64','int32','bool'] |
| file:str |
| method:Literal['preserve','nvfp4'] |
| global_scale:float|None=Field(default=None,gt=0,allow_inf_nan=False) |
| group_size:int|None=None |
|
|
| @model_validator(mode='after') |
| def layout(self): |
| if any(x<0 for x in self.shape):raise ValueError('Negative shape') |
| if self.method=='preserve': |
| if self.global_scale is not None or self.group_size is not None:raise ValueError('Protected tensor has quantization fields') |
| elif len(self.shape)!=2 or min(self.shape)<1 or self.shape[1]%16 or self.group_size!=16 or self.global_scale is None or self.dtype!='bfloat16': |
| raise ValueError('Invalid NVFP4 BF16-source matrix') |
| relative=PurePosixPath(self.file) |
| if relative.is_absolute() or '..' in relative.parts or '\\' in self.file:raise ValueError('Unsafe tensor file') |
| return self |
|
|
| class Component(Strict): |
| class_name:Literal['QwenImage21Transformer2DModel','MiniMaxH3Transformer3DModel'] |
| tensors:dict[str,Tensor] |
| quantized_matrices:int=Field(gt=0) |
| preserved_tensors:int=Field(ge=0) |
|
|
| @model_validator(mode='after') |
| def inventory(self): |
| selected=sum(x.method=='nvfp4' for x in self.tensors.values()) |
| if selected!=self.quantized_matrices or len(self.tensors)-selected!=self.preserved_tensors:raise ValueError('Inventory counts mismatch') |
| return self |
|
|
| class DiffusionManifest(Strict): |
| schema_version:Literal['axq-diffusion.reference/1']='axq-diffusion.reference/1' |
| format:Literal['nvfp4']='nvfp4' |
| status:Literal['development']='development' |
| source_model:Literal['Qwen/Qwen-Image-2.1-Turbo','MiniMaxAI/MiniMax-H3'] |
| source_revision:str=Field(pattern=r'^[0-9a-f]{40}$') |
| backend:Literal['numpy-reference']='numpy-reference' |
| execution:Literal['reconstruct-bfloat16-diffusers']='reconstruct-bfloat16-diffusers' |
| native_low_precision_verified:Literal[False]=False |
| quality_certified:Literal[False]=False |
| source_files:dict[str,FileDigest] |
| components:dict[str,Component] |
| files:dict[str,FileDigest] |
|
|
| @model_validator(mode='after') |
| def binding(self): |
| source={ |
| 'Qwen/Qwen-Image-2.1-Turbo':('fc13ba1986fcb905854dc8de2f52eee395f49b5b',{'transformer'},'QwenImage21Transformer2DModel'), |
| 'MiniMaxAI/MiniMax-H3':('42ed227ee7df40d41602854ae760620d6eb651fe',{'transformer','transformer_ref'},'MiniMaxH3Transformer3DModel'), |
| } |
| revision,components,class_name=source[self.source_model] |
| if self.source_revision!=revision or set(self.components)!=components:raise ValueError('Source pin/component identity mismatch') |
| if not self.files or not self.source_files:raise ValueError('Missing bound files') |
| for name in [*self.files,*self.source_files]: |
| relative=PurePosixPath(name) |
| if relative.is_absolute() or '..' in relative.parts or '\\' in name:raise ValueError('Unsafe manifest member') |
| for name,spec in self.components.items(): |
| if spec.class_name!=class_name:raise ValueError('Wrong component class') |
| for tensor in spec.tensors.values(): |
| if tensor.file not in self.files or not tensor.file.startswith(name+'/'):raise ValueError('Unbound tensor member') |
| return self |
|
|
