[new-model] Add native Helios transformer

Author: sy3535

fastvideo/configs/models/dits/__init__.py

@@ -4,6 +4,7 @@
 from fastvideo.configs.models.dits.flux import FluxDiTConfig
 from fastvideo.configs.models.dits.flux_2 import Flux2Config
 from fastvideo.configs.models.dits.glm_image import GlmImageDiTConfig
+from fastvideo.configs.models.dits.helios import HeliosConfig
 from fastvideo.configs.models.dits.hunyuangamecraft import HunyuanGameCraftConfig
 from fastvideo.configs.models.dits.hunyuanvideo import HunyuanVideoConfig
 from fastvideo.configs.models.dits.hunyuanvideo15 import HunyuanVideo15Config
@@ -22,6 +23,6 @@
     "HunyuanVideoConfig", "HunyuanVideo15Config", "HunyuanGameCraftConfig", "WanVideoConfig", "DreamXWorldConfig",
     "DreamXWorldARConfig", "CosmosVideoConfig", "Cosmos25VideoConfig", "FluxDiTConfig", "Flux2Config",
     "LongCatVideoConfig", "LTX2VideoConfig", "HYWorldConfig", "Kandinsky5VideoConfig", "MagiHumanVideoConfig",
-    "StableAudioConfig", "GlmImageDiTConfig", "LingBotWorld2CausalFastVideoConfig", "LingBotVideoConfig",
-    "ZImageDiTConfig"
+    "StableAudioConfig", "GlmImageDiTConfig", "HeliosConfig", "LingBotWorld2CausalFastVideoConfig",
+    "LingBotVideoConfig", "ZImageDiTConfig"
 ]

fastvideo/configs/models/dits/helios.py

@@ -0,0 +1,78 @@
+# SPDX-License-Identifier: Apache-2.0
+from dataclasses import dataclass, field
+
+from fastvideo.configs.models.dits.base import DiTArchConfig, DiTConfig
+from fastvideo.platforms import AttentionBackendEnum
+
+
+def _is_transformer_block(name: str, module) -> bool:
+    del module
+    return name.startswith("blocks.") and name.split(".")[-1].isdigit()
+
+
+@dataclass
+class HeliosArchConfig(DiTArchConfig):
+    """Architecture fields for Helios-Distilled's history-aware DiT."""
+
+    _fsdp_shard_conditions: list = field(default_factory=lambda: [_is_transformer_block])
+    _supported_attention_backends: tuple[AttentionBackendEnum, ...] = (
+        AttentionBackendEnum.FLASH_ATTN,
+        AttentionBackendEnum.TORCH_SDPA,
+    )
+    param_names_mapping: dict = field(default_factory=dict)
+    reverse_param_names_mapping: dict = field(default_factory=dict)
+    lora_param_names_mapping: dict = field(default_factory=dict)
+
+    patch_size: tuple[int, int, int] = (1, 2, 2)
+    num_attention_heads: int = 40
+    attention_head_dim: int = 128
+    in_channels: int = 16
+    out_channels: int = 16
+    text_dim: int = 4096
+    freq_dim: int = 256
+    ffn_dim: int = 13824
+    num_layers: int = 40
+    cross_attn_norm: bool = True
+    qk_norm: str = "rms_norm_across_heads"
+    eps: float = 1e-6
+    added_kv_proj_dim: int | None = None
+    rope_dim: tuple[int, int, int] = (44, 42, 42)
+    rope_theta: float = 10000.0
+    guidance_cross_attn: bool = True
+    zero_history_timestep: bool = True
+    has_multi_term_memory_patch: bool = True
+    is_amplify_history: bool = False
+    history_scale_mode: str = "per_head"
+
+    def __post_init__(self) -> None:
+        super().__post_init__()
+        self.out_channels = self.out_channels or self.in_channels
+        self.hidden_size = self.num_attention_heads * self.attention_head_dim
+        self.num_channels_latents = self.out_channels
+        if not self.cross_attn_norm:
+            raise ValueError("Helios currently requires cross_attn_norm=True")
+        if self.qk_norm != "rms_norm_across_heads":
+            raise ValueError("Helios currently requires qk_norm='rms_norm_across_heads'")
+        if self.added_kv_proj_dim is not None:
+            raise ValueError("Helios added_kv_proj_dim variants are not supported")
+        if not self.guidance_cross_attn:
+            raise ValueError("Helios currently requires guidance_cross_attn=True")
+        if not self.zero_history_timestep:
+            raise ValueError("Helios currently requires zero_history_timestep=True")
+        if not self.has_multi_term_memory_patch:
+            raise ValueError("Helios currently requires has_multi_term_memory_patch=True")
+        if self.is_amplify_history:
+            raise ValueError("Helios is_amplify_history variants are not supported")
+        if self.history_scale_mode != "per_head":
+            raise ValueError("Helios currently requires history_scale_mode='per_head'")
+        if sum(self.rope_dim) != self.attention_head_dim:
+            raise ValueError(
+                f"Helios rope_dim must sum to attention_head_dim, got {self.rope_dim} and {self.attention_head_dim}")
+        if any(dim % 2 for dim in self.rope_dim):
+            raise ValueError(f"Helios rope dimensions must be even: {self.rope_dim}")
+
+
+@dataclass
+class HeliosConfig(DiTConfig):
+    arch_config: DiTArchConfig = field(default_factory=HeliosArchConfig)
+    prefix: str = "Helios"