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

303 行
5.7 KiB
Python

# SPDX-License-Identifier: Apache-2.0
from dataclasses import dataclass, field
from sglang.multimodal_gen.configs.models import DiTConfig, EncoderConfig, VAEConfig
from sglang.multimodal_gen.configs.models.dits.ideogram import Ideogram4DiTConfig
from sglang.multimodal_gen.configs.models.encoders.ideogram import (
Ideogram4TextEncoderConfig,
)
from sglang.multimodal_gen.configs.models.vaes.flux import Flux2VAEConfig
from sglang.multimodal_gen.configs.pipeline_configs.base import (
ImagePipelineConfig,
ModelTaskType,
)
LATENT_SHIFT = (
0.01984364,
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0.31356594,
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0.12446,
0.07062869,
0.30880162,
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0.02578168,
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0.309178,
-0.18065738,
-0.19401479,
-0.34495114,
-0.01760592,
)
LATENT_SCALE = (
1.63933691,
1.70204478,
1.73642566,
1.90004803,
1.6675316,
1.69059584,
1.56853198,
1.62314944,
1.89106626,
1.58086668,
1.60822129,
1.60962993,
1.63322129,
1.56074359,
1.73419528,
1.7919265,
1.64040632,
1.66802808,
1.60390303,
1.75480492,
1.63187587,
1.64334594,
1.61722884,
1.60146046,
1.63459219,
1.55291476,
1.68771497,
1.68415657,
1.78966054,
1.66631641,
1.65626686,
1.65976433,
1.63487607,
1.69513249,
1.72933756,
1.91310663,
1.67035057,
1.72286863,
1.56719251,
1.61934825,
1.88628859,
1.56911539,
1.59455129,
1.60829869,
1.62470611,
1.56052853,
1.73677003,
1.77563606,
1.63732541,
1.66370527,
1.59508952,
1.75153949,
1.63029275,
1.64517667,
1.61659342,
1.59722044,
1.64103121,
1.5408531,
1.68610394,
1.67772755,
1.78998563,
1.66621713,
1.65458955,
1.66041308,
1.64710857,
1.68163503,
1.74000294,
1.92784786,
1.67411194,
1.67395548,
1.57406532,
1.62199356,
1.87618195,
1.5584375,
1.57438785,
1.61711053,
1.63094305,
1.55644029,
1.73124302,
1.80666627,
1.6463621,
1.65932006,
1.60816188,
1.75682671,
1.64695873,
1.63121722,
1.61380832,
1.60478651,
1.63396035,
1.53505068,
1.65534289,
1.67132281,
1.80317197,
1.6767314,
1.65700938,
1.68426259,
1.65339716,
1.67540638,
1.73298504,
1.94067348,
1.67893609,
1.70635117,
1.5730906,
1.61928553,
1.87148809,
1.56244866,
1.56697152,
1.61584394,
1.62759496,
1.55480378,
1.73484107,
1.79055143,
1.64688773,
1.66121492,
1.60135887,
1.75254572,
1.64798332,
1.62989921,
1.61381592,
1.60792883,
1.63939668,
1.53075757,
1.65371318,
1.66801185,
1.80029087,
1.67591476,
1.65655173,
1.68533454,
)
@dataclass
class Ideogram4PipelineConfig(ImagePipelineConfig):
task_type: ModelTaskType = ModelTaskType.T2I
should_use_guidance: bool = False
vae_precision: str = "bf16"
dit_precision: str = "bf16"
text_encoder_precisions: tuple[str, ...] = field(default_factory=lambda: ("bf16",))
dit_config: DiTConfig = field(default_factory=Ideogram4DiTConfig)
vae_config: VAEConfig = field(default_factory=Flux2VAEConfig)
text_encoder_configs: tuple[EncoderConfig, ...] = field(
default_factory=lambda: (Ideogram4TextEncoderConfig(),)
)
text_encoder_extra_args: list[dict] = field(default_factory=lambda: [{}])
preprocess_text_funcs: tuple = field(default_factory=lambda: (None,))
postprocess_text_funcs: tuple = field(default_factory=lambda: (None,))
patch_size: int = 2
ae_scale_factor: int = 8
max_text_tokens: int = 2048
def prepare_latent_shape(self, batch, batch_size, num_frames):
patch = self.patch_size * self.ae_scale_factor
grid_h = batch.height // patch
grid_w = batch.width // patch
return (batch_size, grid_h * grid_w, self.dit_config.arch_config.in_channels)