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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

40 lines
1.3 KiB
Python

# SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models.dits.base import DiTArchConfig, DiTConfig
from sglang.multimodal_gen.configs.models.fsdp import is_layer
from sglang.multimodal_gen.runtime.platforms import AttentionBackendEnum
@dataclass
class Ideogram4DiTArchConfig(DiTArchConfig):
adaln_dim: int = 512
attention_head_dim: int = 256
in_channels: int = 128
intermediate_size: int = 12288
llm_features_dim: int = 53248
mrope_section: tuple[int, int, int] | list[int] = (24, 20, 20)
norm_eps: float = 1e-5
num_attention_heads: int = 18
num_layers: int = 34
rope_theta: int = 5_000_000
_fsdp_shard_conditions: list = field(default_factory=lambda: [is_layer])
_supported_attention_backends: set[AttentionBackendEnum] = field(
default_factory=lambda: {
AttentionBackendEnum.FA,
AttentionBackendEnum.TORCH_SDPA,
}
)
def __post_init__(self) -> None:
super().__post_init__()
self.hidden_size = self.num_attention_heads * self.attention_head_dim
self.num_channels_latents = self.in_channels
@dataclass
class Ideogram4DiTConfig(DiTConfig):
arch_config: DiTArchConfig = field(default_factory=Ideogram4DiTArchConfig)
prefix: str = "ideogram4"