config#

Saved execution policy for GDN training-time numerical emulation.

Classes

`LinearAttentionConfig`	GDN chunk-64 policy; unsupported numerical modes fail config validation.
`LinearAttentionPolicyEntry`	Assign a complete policy to supported modules matching `module_name`.

class LinearAttentionConfig#

Bases: ModeloptBaseConfig

GDN chunk-64 policy; unsupported numerical modes fail config validation.

state.block_v defines one dynamic scale per [Dk, block_v] tile of each sequence/head. The initial state and every chunk’s final state are rounded when gdn_state_quantizer is enabled. Outputs use the incoming rounded state.

backend: Literal['fla']#

chunk_size: Literal[64]#

model_config = {'extra': 'forbid', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

schema_version: Literal[1]#

solve: _SolveConfig#

state: _StateConfig#

class LinearAttentionPolicyEntry#

Bases: ModeloptBaseConfig

Assign a complete policy to supported modules matching module_name.

Rules apply in order: the last match wins, without merging nested fields. A rule must match at least one supported linear-attention module.

cfg: LinearAttentionConfig#

model_config = {'extra': 'forbid', 'validate_assignment': True}#: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

module_name: str#