nemo_automodel.components.models.glm4_moe.model

Module Contents

Classes

Name	Description
`Block`	-
`Glm4MoeForCausalLM`	-
`Glm4MoeModel`	-

Data

ModelClass

API

class nemo_automodel.components.models.glm4_moe.model.Block(
    layer_idx: int,
    config: transformers.models.glm4_moe.configuration_glm4_moe.Glm4MoeConfig,
    moe_config: nemo_automodel.components.moe.config.MoEConfig,
    backend: nemo_automodel.components.models.common.BackendConfig
)

Bases: Module

input_layernorm

mlp

= MoE(moe_config, backend)

post_attention_layernorm

self_attn

= Glm4MoeAttention(config, backend)

nemo_automodel.components.models.glm4_moe.model.Block._mlp(
    x: torch.Tensor,
    padding_mask: torch.Tensor | None
) -> torch.Tensor

nemo_automodel.components.models.glm4_moe.model.Block.forward(
    x: torch.Tensor,
    freqs_cis: torch.Tensor,
    attention_mask: torch.Tensor | None = None,
    padding_mask: torch.Tensor | None = None,
    attn_kwargs: typing.Any = {}
) -> torch.Tensor

nemo_automodel.components.models.glm4_moe.model.Block.init_weights(
    buffer_device: torch.device
)

class nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM(
    config: transformers.models.glm4_moe.configuration_glm4_moe.Glm4MoeConfig,
    moe_config: nemo_automodel.components.moe.config.MoEConfig | None = None,
    backend: nemo_automodel.components.models.common.BackendConfig | None = None,
    kwargs = {}
)

Bases: HFCheckpointingMixin, Module, MoEFSDPSyncMixin

_keep_in_fp32_modules_strict

= ['e_score_correction_bias']

lm_head

model

state_dict_adapter

tie_word_embeddings_support

TieSupport = TieSupport.UNTIED_ONLY

nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM.forward(
    input_ids: torch.Tensor,
    position_ids: torch.Tensor | None = None,
    attention_mask: torch.Tensor | None = None,
    padding_mask: torch.Tensor | None = None,
    logits_to_keep: typing.Union[int, torch.Tensor] = 0,
    output_hidden_states: bool | None = None,
    attn_kwargs: typing.Any = {}
) -> transformers.modeling_outputs.CausalLMOutputWithPast

nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM.from_config(
    config: transformers.models.glm4_moe.configuration_glm4_moe.Glm4MoeConfig,
    moe_config: nemo_automodel.components.moe.config.MoEConfig | None = None,
    backend: nemo_automodel.components.models.common.BackendConfig | None = None,
    kwargs = {}
)

classmethod

nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM.from_pretrained(
    pretrained_model_name_or_path: str,
    model_args = (),
    kwargs = {}
)

classmethod

nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM.get_input_embeddings()

nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM.get_output_embeddings()

nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM.initialize_weights(
    buffer_device: torch.device | None = None,
    dtype: torch.dtype = torch.bfloat16
) -> None

nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM.set_input_embeddings(
    value
)

nemo_automodel.components.models.glm4_moe.model.Glm4MoeForCausalLM.set_output_embeddings(
    new_embeddings
)

class nemo_automodel.components.models.glm4_moe.model.Glm4MoeModel(
    config: transformers.models.glm4_moe.configuration_glm4_moe.Glm4MoeConfig,
    backend: nemo_automodel.components.models.common.BackendConfig,
    moe_config: nemo_automodel.components.moe.config.MoEConfig | None = None,
    moe_overrides: dict | None = None
)

Bases: Module

embed_tokens

head_dim

layers

= torch.nn.ModuleDict()

max_seq_len

= config.max_position_embeddings

moe_config

= moe_config or MoEConfig(**moe_defaults)

norm

rotary_emb

nemo_automodel.components.models.glm4_moe.model.Glm4MoeModel.forward(
    input_ids: torch.Tensor,
    position_ids: torch.Tensor | None = None,
    attention_mask: torch.Tensor | None = None,
    padding_mask: torch.Tensor | None = None,
    attn_kwargs: typing.Any = {}
) -> torch.Tensor

nemo_automodel.components.models.glm4_moe.model.Glm4MoeModel.init_weights(
    buffer_device: torch.device | None = None
) -> None

nemo_automodel.components.models.glm4_moe.model.ModelClass = Glm4MoeForCausalLM