qwen3_5_model_descriptor

Classes

`Qwen3P5TextModelDescriptor`
`Qwen3P5VLModelDescriptor`
`Qwen3P5TextFFNIntermediateLayerDescriptor`
`Qwen3P5VLFFNIntermediateLayerDescriptor`
`Qwen3P5TextKVHeadsLayerDescriptor`
`Qwen3P5VLKVHeadsLayerDescriptor`
`Qwen3P5KVHeadsPruningMixIn`	KV-head pruning for Qwen3.5 gated full-attention layers.
`Qwen3P5TextGatedDeltaNetLayerDescriptor`
`Qwen3P5VLGatedDeltaNetLayerDescriptor`
`Qwen3P5MoeTextModelDescriptor`
`Qwen3P5MoeVLModelDescriptor`

class Qwen3P5KVHeadsPruningMixIn

Bases: KVHeadsPruningMixIn

KV-head pruning for Qwen3.5 gated full-attention layers.

__init__(layer_descriptor)

Parameters:: layer_descriptor (KVHeadsLayerDescriptor)

prune_single_layer(layer_idx, parent_state_dict, new_state_dict, original_config, new_config, descriptor, gqa_init_mode, mlp_init_config, is_original_mha, keys, keys_to_remove, **kwargs)

Parameters:

layer_idx (int)
parent_state_dict (dict)
new_state_dict (dict)
original_config (PreTrainedConfig)
new_config (PreTrainedConfig)
gqa_init_mode (GQAInitMode)
mlp_init_config (dict[str, Any] | None)
is_original_mha (bool)
keys (dict)
keys_to_remove (dict)

class Qwen3P5MoeTextModelDescriptor

Bases: _Qwen3P5MoeModelDescriptor

classmethod anymodel_arch_info()

Return type:: dict[str, Any]

static init_rotary_embedding(model, runtime)

class Qwen3P5MoeVLModelDescriptor

Bases: _Qwen3P5MoeModelDescriptor

static init_rotary_embedding(model, runtime)

classmethod runtime_benchmark_export_descriptor()

Return type:: Type[ModelDescriptor]

class Qwen3P5TextFFNIntermediateLayerDescriptor

Bases: FFNIntermediateLayerDescriptor

__init__(down_proj_name='mlp.down_proj', ffn_prefix_name='model.layers.{layer_idx}.mlp', linear_weight_names=<factory>)

Parameters:

down_proj_name (str)
ffn_prefix_name (str)
linear_weight_names (List[str])

Return type:

None

down_proj_name: str = 'mlp.down_proj'

ffn_prefix_name: str = 'model.layers.{layer_idx}.mlp'

linear_weight_names: List[str]

class Qwen3P5TextGatedDeltaNetLayerDescriptor

Bases: GatedDeltaNetLayerDescriptor

__init__(target_name='linear_attn', gdn_prefix_name='model.layers.{layer_idx}.linear_attn')

Parameters:

target_name (str)
gdn_prefix_name (str)

Return type:

None

gdn_prefix_name: str = 'model.layers.{layer_idx}.linear_attn'

target_name: str = 'linear_attn'

class Qwen3P5TextKVHeadsLayerDescriptor

Bases: KVHeadsLayerDescriptor

__init__(o_proj_name='self_attn.o_proj', attn_prefix_name='model.layers.{layer_idx}.self_attn', qkvo_weight_names=<factory>)

Parameters:

o_proj_name (str)
attn_prefix_name (str)
qkvo_weight_names (List[str])

Return type:

None

attn_prefix_name: str = 'model.layers.{layer_idx}.self_attn'

o_proj_name: str = 'self_attn.o_proj'

qkvo_weight_names: List[str]

class Qwen3P5TextModelDescriptor

Bases: _Qwen3P5BaseModelDescriptor

classmethod create_runtime_benchmark_model(runtime_config, block_configs)

Parameters:: block_configs (list[BlockConfig])

classmethod embedding_pruning_spec(config, *, widths, alignment)

Parameters:: alignment (int)

static final_norm_name()

static init_rotary_embedding(model, runtime)

static input_embedding_name()

static layer_block_name(index)

Parameters:: index (int)

static layer_name_predicates(num_layers)

Parameters:: num_layers (int)
Return type:: Dict[str, Pattern]

static output_embedding_name()

static pruning_mixins()

Return type:: Dict[str, PruningMixIn]

classmethod runtime_benchmark_config_fields(lm_config)

Return type:: dict[str, Any]

classmethod runtime_vllm_benchmark_args(config)

Parameters:: config (Any)
Return type:: list[str]

class Qwen3P5VLFFNIntermediateLayerDescriptor

Bases: FFNIntermediateLayerDescriptor

__init__(down_proj_name='mlp.down_proj', ffn_prefix_name='model.language_model.layers.{layer_idx}.mlp', linear_weight_names=<factory>)

Parameters:

down_proj_name (str)
ffn_prefix_name (str)
linear_weight_names (List[str])

Return type:

None

down_proj_name: str = 'mlp.down_proj'

ffn_prefix_name: str = 'model.language_model.layers.{layer_idx}.mlp'

linear_weight_names: List[str]

class Qwen3P5VLGatedDeltaNetLayerDescriptor

Bases: GatedDeltaNetLayerDescriptor

__init__(target_name='linear_attn', gdn_prefix_name='model.language_model.layers.{layer_idx}.linear_attn')

Parameters:

target_name (str)
gdn_prefix_name (str)

Return type:

None

gdn_prefix_name: str = 'model.language_model.layers.{layer_idx}.linear_attn'

target_name: str = 'linear_attn'

class Qwen3P5VLKVHeadsLayerDescriptor

Bases: KVHeadsLayerDescriptor

__init__(o_proj_name='self_attn.o_proj', attn_prefix_name='model.language_model.layers.{layer_idx}.self_attn', qkvo_weight_names=<factory>)

Parameters:

o_proj_name (str)
attn_prefix_name (str)
qkvo_weight_names (List[str])

Return type:

None

attn_prefix_name: str = 'model.language_model.layers.{layer_idx}.self_attn'

o_proj_name: str = 'self_attn.o_proj'

qkvo_weight_names: List[str]

class Qwen3P5VLModelDescriptor

Bases: _Qwen3P5BaseModelDescriptor

classmethod anymodel_arch_info()

Return type:: dict[str, Any]

classmethod embedding_pruning_spec(config, *, widths, alignment)

Parameters:: alignment (int)

static final_norm_name()

static get_language_model_config(config)

static init_rotary_embedding(model, runtime)

static input_embedding_name()

static layer_block_name(index)

Parameters:: index (int)

static layer_name_predicates(num_layers)

Parameters:: num_layers (int)
Return type:: Dict[str, Pattern]

static output_embedding_name()

static pruning_mixins()

Return type:: Dict[str, PruningMixIn]

classmethod runtime_benchmark_export_descriptor()

Return type:: Type[ModelDescriptor]

classmethod vision_module_names()

Return type:: tuple[str, …]