"""
Layer Specification for hunyuan-large.
"""
from megatron.core.fusions.fused_bias_dropout import get_bias_dropout_add
from megatron.training import get_args
from megatron.core.transformer.enums import AttnMaskType
from megatron.core.tensor_parallel import ColumnParallelLinear, RowParallelLinear
from megatron.core.transformer import ModuleSpec, TransformerLayerSubmodules
from megatron.core.transformer.identity_op import IdentityOp
from megatron.core.transformer.dot_product_attention import DotProductAttention
from megatron.core.models.gpt.gpt_layer_specs import _get_mlp_module_spec
from mindspeed_llm.core import PTNorm
from mindspeed_llm.tasks.models.transformer.transformer_layer_hunyuan import HunyuanLargeTransformerLayer
from mindspeed_llm.tasks.models.transformer.hunyuan_large_attention import HunyuanLargeAttention, HunyuanLargeAttentionSubmodules
args = get_args()
num_experts, moe_grouped_gemm, qk_layernorm = args.num_experts, args.moe_grouped_gemm, args.qk_layernorm
layer_spec = ModuleSpec(
module=HunyuanLargeTransformerLayer,
submodules=TransformerLayerSubmodules(
input_layernorm=PTNorm,
self_attention=ModuleSpec(
module=HunyuanLargeAttention,
params={"attn_mask_type": AttnMaskType.causal},
submodules=HunyuanLargeAttentionSubmodules(
linear_qkv=ColumnParallelLinear,
core_attention=DotProductAttention,
linear_proj=RowParallelLinear,
q_layernorm=PTNorm if qk_layernorm else IdentityOp,
k_layernorm=PTNorm if qk_layernorm else IdentityOp,
),
),
self_attn_bda=get_bias_dropout_add,
pre_mlp_layernorm=PTNorm,
mlp=_get_mlp_module_spec(use_te=False, num_experts=num_experts, moe_grouped_gemm=moe_grouped_gemm),
mlp_bda=get_bias_dropout_add,
sharded_state_dict_keys_map={
'input_layernorm.': 'self_attention.linear_qkv.layer_norm_',
'pre_mlp_layernorm.': 'mlp.linear_fc1.layer_norm_',
},
),
)