# ruff: noqa: E501
from collections.abc import Generator

import pytest
import torch
import torch.nn.functional as F
from PIL import Image
from transformers import CLIPModel, CLIPProcessor

from tests.helpers.runtime import OmniRunner
from tests.helpers.stage_config import get_deploy_config_path
from vllm_omni import Omni
from vllm_omni.inputs.data import OmniDiffusionSamplingParams
from vllm_omni.platforms import current_omni_platform

PROMPT = "A brown and white dog is running on the grass"
MODEL_NAME = "tencent/HunyuanImage-3.0"
LOCAL_CLIP_PATH = "openai/clip-vit-base-patch32"
DEPLOY_CONFIG_PATH = get_deploy_config_path("hunyuan_image3.yaml")

pytestmark = [pytest.mark.advanced_model, pytest.mark.diffusion]

# System prompt type. Options: None, dynamic, en_vanilla, en_recaption, en_think_recaption, en_unified
# Below are the CLIP embedding tensors from the official HunyuanImage model (seed=1234, prompt: "A brown and white dog is running on the grass").
# SEED_1234 denotes the output without system prompt, while the remaining entries correspond to outputs generated with different system prompts.
# fmt: off
SEED_1234 = torch.tensor(
    [
        0.027797, 0.028964, -0.005051, 0.001059, 0.017021, -0.034029, 0.021989, 0.033318, -0.000308, 0.016179, 0.010504, -0.034201, 0.050230, -0.021170, 0.083530, -0.003621,
        0.040758, 0.039913, 0.044305, -0.019285, -0.058387, -0.001099, 0.042782, -0.036136, -0.014955, 0.002147, 0.009439, 0.012943, -0.028732, -0.018349, 0.002861, 0.013019,
        0.014362, -0.038833, 0.029413, 0.020724, 0.002714, 0.010416, -0.020527, 0.050266, -0.081026, -0.006814, -0.007457, -0.032333, 0.008417, -0.122455, -0.006085, -0.025610,
        0.012614, 0.025817, -0.005419, 0.038657, 0.000789, 0.067111, 0.002818, 0.028696, 0.047305, -0.009993, -0.019508, 0.038604, 0.099657, 0.026728, 0.012361, 0.013626,
        0.023164, -0.037186, 0.007535, 0.054645, -0.009012, -0.019383, -0.005234, -0.018715, -0.000346, 0.051317, -0.028744, 0.029933, -0.006382, -0.018414, -0.033906, -0.028892,
        -0.015301, -0.004276, 0.014626, -0.008505, 0.013717, -0.027323, -0.001332, -0.040227, 0.047021, -0.019082, -0.037260, -0.029780, -0.594026, 0.016573, -0.010523, 0.042616,
        -0.013136, 0.030540, -0.151685, -0.005367, 0.016209, -0.034183, 0.009852, 0.038452, 0.005494, -0.017887, -0.007167, 0.017262, -0.038980, 0.011995, 0.021952, -0.031660,
        0.020507, -0.035880, 0.035183, -0.026975, -0.050788, -0.002553, 0.037774, -0.020082, -0.015403, 0.045022, 0.072167, -0.029237, 0.003895, -0.051250, 0.008581, 0.023545,
        -0.026827, 0.020895, 0.041780, -0.040766, -0.008146, 0.080630, 0.000404, 0.032003, -0.005279, -0.090707, -0.013813, 0.010204, -0.001513, 0.016394, -0.001321, 0.020535,
        -0.038645, 0.024858, 0.024378, 0.018717, -0.056314, 0.024402, 0.018694, 0.029009, -0.008502, -0.014694, -0.028345, 0.005202, 0.046116, -0.032166, -0.030706, -0.038738,
        -0.031356, -0.009683, 0.040069, 0.001596, -0.012621, 0.018590, -0.024138, 0.035330, 0.011546, 0.015791, -0.026932, 0.004531, 0.022455, -0.012871, 0.013915, -0.009567,
        -0.010976, 0.013497, 0.042590, 0.002072, -0.052718, -0.045494, 0.013036, -0.005403, -0.005947, -0.003437, 0.016653, -0.016805, -0.040291, 0.007927, 0.001296, -0.008319,
        0.021514, -0.001452, -0.121998, 0.015396, -0.022594, -0.006977, -0.040108, -0.035550, -0.021872, -0.014721, 0.019799, 0.036556, 0.015072, -0.057988, -0.011684, -0.045220,
        -0.026295, 0.052647, 0.013741, -0.013428, 0.061794, 0.021431, -0.011316, -0.009963, 0.008198, 0.027746, 0.074219, -0.019499, 0.042673, 0.016028, 0.007214, -0.010650,
        -0.019682, 0.001902, 0.038867, -0.007333, 0.031749, 0.004391, 0.018688, 0.044654, 0.030615, -0.027816, 0.031711, -0.056952, -0.033499, -0.039368, 0.025801, -0.027610,
        -0.009329, -0.001799, 0.024061, -0.012593, -0.050266, -0.012512, 0.019528, -0.083434, 0.018238, 0.034138, -0.020120, -0.009910, -0.002280, 0.035325, 0.034440, -0.055205,
        -0.017698, -0.000439, -0.034703, 0.013356, -0.037287, 0.048494, -0.018570, 0.028069, 0.019269, -0.007263, -0.008521, 0.000426, -0.016677, 0.056162, -0.011944, 0.017322,
        0.022219, -0.014266, -0.009292, -0.009979, 0.014973, 0.011623, -0.017799, 0.032925, -0.024668, 0.007312, -0.025035, -0.008967, -0.026827, 0.011889, -0.138517, -0.009608,
        -0.020592, -0.001272, 0.015676, -0.025706, 0.031775, -0.004195, 0.026876, -0.014748, -0.025966, -0.008741, 0.035437, 0.017139, -0.005140, -0.007101, -0.012510, -0.023600,
        0.032969, -0.005510, 0.020010, 0.032567, 0.015558, 0.004265, -0.036300, 0.048210, 0.080424, -0.052820, -0.002063, -0.020875, 0.052530, -0.001638, -0.020299, -0.035202,
        0.087818, 0.034614, -0.032735, 0.033201, -0.001751, 0.029574, 0.009926, 0.011619, -0.001267, -0.020149, -0.003826, -0.029860, 0.011437, -0.051276, 0.024344, 0.003096,
        -0.011573, 0.038228, -0.005730, -0.052328, 0.001909, -0.025877, 0.019976, -0.010160, 0.023892, 0.049161, -0.028978, 0.018700, -0.026460, 0.001090, -0.072128, -0.008406,
        0.010828, 0.020621, -0.005706, 0.023797, 0.036231, -0.112069, 0.017601, 0.007496, 0.045999, 0.016771, 0.021977, 0.022305, 0.018377, 0.002036, -0.029815, -0.082922,
        -0.012710, -0.026355, 0.003790, 0.017472, -0.023148, -0.002901, -0.057854, 0.028393, 0.230866, -0.023486, 0.051094, 0.047508, 0.018957, -0.037130, 0.001054, -0.026126,
        0.021970, -0.046915, -0.019419, -0.014077, 0.002502, -0.079454, -0.057149, -0.081701, 0.041979, -0.043074, -0.009425, -0.035776, -0.021794, -0.004826, -0.057263, -0.072940,
        0.037651, -0.013991, -0.043863, -0.020581, 0.034319, -0.052566, -0.010355, -0.022963, 0.027144, -0.017339, 0.088930, -0.000670, -0.026547, -0.026586, -0.032531, 0.040314,
        0.010148, 0.021104, 0.009228, -0.073227, 0.036650, -0.019337, 0.010211, -0.089620, -0.024676, -0.020729, -0.004070, 0.000784, -0.110561, 0.015390, 0.027151, -0.003228,
        -0.066704, -0.004797, -0.026117, -0.018131, -0.090114, 0.020659, -0.007157, 0.013608, -0.022324, 0.027487, 0.018873, 0.027854, 0.045085, -0.039992, -0.017829, 0.011071,
        -0.011393, -0.004454, -0.037189, -0.030299, 0.059668, 0.005064, 0.024655, -0.037239, 0.046882, -0.010356, -0.009690, 0.061909, -0.024736, 0.016849, 0.000784, 0.000201,
        0.066165, 0.010234, -0.012134, -0.002823, -0.060847, 0.008953, 0.010348, 0.022292, -0.044602, -0.020981, 0.038839, 0.006616, -0.016836, -0.043995, -0.005463, -0.036413,
        0.034895, -0.018008, -0.009543, -0.025080, -0.035243, 0.042696, -0.028911, -0.030676, -0.038542, -0.027798, -0.026607, 0.019467, 0.070629, -0.037356, -0.042648, -0.000284,
        0.033095, 0.077781, -0.052930, 0.022515, -0.029926, -0.033821, -0.003277, -0.000038, -0.026871, 0.018223, -0.004221, 0.023454, -0.030611, -0.006396, -0.009873, -0.008402,
    ],
    dtype=torch.float32,
)
SYSTEM_PROMPT_DYNAMIC = torch.tensor(
    [
        0.010809, 0.021177, -0.017600, -0.016814, 0.012351, -0.024554, 0.018299, 0.039305, 0.003331, 0.030473, 0.005557, -0.040898, 0.047294, -0.016136, 0.076989, -0.002723,
        0.017622, 0.042330, 0.058266, -0.016232, -0.029502, 0.004529, 0.033543, -0.041481, -0.017631, 0.002727, 0.018874, 0.019932, -0.030052, -0.009997, 0.004582, 0.002135,
        -0.003720, -0.030923, 0.021174, 0.034033, -0.007096, 0.011522, -0.009518, 0.055688, -0.092351, -0.003914, 0.004589, -0.032635, 0.012479, -0.140607, -0.014141, -0.031821,
        0.001396, 0.026780, -0.007623, 0.039957, 0.006434, 0.047516, 0.014377, 0.015237, 0.034212, 0.003576, -0.027357, 0.038888, 0.087272, 0.020248, 0.015165, 0.016002,
        0.020781, -0.040509, -0.008929, 0.080857, -0.002642, -0.009738, -0.005683, -0.000615, -0.012801, 0.046457, -0.045004, 0.024689, 0.002498, -0.017333, -0.027366, -0.023231,
        -0.006064, -0.021505, 0.007405, -0.021249, 0.026252, -0.018690, 0.020093, -0.036954, 0.037510, -0.032027, -0.030871, -0.011173, -0.618627, 0.021213, -0.004366, 0.029555,
        -0.004324, 0.020221, -0.143832, -0.021386, 0.010482, -0.042113, 0.016164, 0.040350, 0.014627, -0.011778, -0.018102, 0.035380, -0.020305, 0.010590, 0.009227, -0.011415,
        0.018623, -0.036384, 0.031003, -0.017073, -0.056456, -0.010423, 0.033029, -0.023511, -0.008717, 0.045716, 0.068273, -0.027886, 0.009665, -0.039801, 0.001465, 0.024361,
        -0.015039, 0.022903, 0.033362, -0.022804, 0.008631, 0.076518, 0.000619, 0.022786, -0.015435, -0.095242, -0.006092, 0.015496, -0.009081, 0.015740, 0.004280, 0.013103,
        -0.031836, 0.034241, 0.031836, 0.032636, -0.053721, 0.034370, 0.019172, 0.018383, 0.006907, -0.036039, -0.027927, 0.008646, 0.040496, -0.060314, -0.039116, -0.021488,
        -0.031682, -0.005077, 0.034920, 0.002148, -0.008087, 0.002024, -0.008480, 0.041096, 0.011401, 0.020380, -0.025078, 0.005002, 0.022252, -0.014577, 0.008051, -0.014476,
        -0.007078, 0.021075, 0.036965, 0.005343, -0.038671, -0.037222, 0.014052, -0.009952, -0.003958, -0.001878, 0.017848, -0.016608, -0.030813, 0.010921, 0.001068, 0.003095,
        0.007076, -0.001936, -0.102996, 0.006838, -0.005243, -0.009140, -0.043796, -0.027227, -0.008426, -0.013177, 0.015602, 0.021036, 0.025484, -0.064836, -0.003593, -0.038036,
        -0.023102, 0.064053, 0.007850, 0.000771, 0.039297, 0.011903, -0.015866, -0.017612, 0.006308, 0.024342, 0.086761, -0.016705, 0.039239, 0.025079, -0.006452, 0.003174,
        -0.010146, 0.010787, 0.035932, -0.015346, 0.037191, 0.010990, 0.011573, 0.044958, 0.035560, -0.017339, 0.018878, -0.025394, -0.044339, -0.029852, 0.015951, -0.032248,
        -0.012019, 0.013497, 0.012224, -0.001284, -0.034041, -0.015768, 0.000230, -0.086076, 0.024878, 0.031929, -0.016668, -0.019815, -0.001325, 0.007944, 0.017674, -0.036097,
        -0.019651, -0.001272, -0.032842, 0.002056, -0.037140, 0.043191, -0.003710, 0.011767, 0.020313, -0.018396, -0.015935, 0.010228, -0.017349, 0.049363, -0.010007, 0.019533,
        0.018076, 0.016608, -0.005523, -0.007793, 0.016868, 0.019341, -0.008236, 0.026765, -0.025324, -0.007849, -0.023648, -0.007791, -0.018508, 0.015357, -0.166499, -0.003718,
        -0.035447, -0.005229, 0.019327, -0.014207, 0.028433, -0.002619, 0.013888, -0.033146, -0.017015, 0.004677, 0.039554, 0.003803, -0.014592, -0.018886, -0.023868, -0.022708,
        0.033661, 0.008626, 0.015687, 0.046395, 0.014173, 0.015083, -0.025994, 0.039120, 0.076334, -0.061165, 0.001791, -0.017579, 0.067567, -0.002415, -0.032495, -0.025576,
        0.079027, 0.036370, -0.013303, 0.030510, -0.009061, 0.019135, 0.015627, 0.024864, 0.015093, -0.017066, -0.014075, -0.021907, 0.017388, -0.033492, 0.013317, -0.000040,
        0.003396, 0.044030, -0.009194, -0.049524, -0.005015, -0.040007, 0.009104, 0.000580, 0.005603, 0.035891, -0.038913, 0.023239, -0.017022, -0.002695, -0.095759, 0.018503,
        0.017365, 0.011104, -0.003433, 0.024113, 0.052609, -0.085274, 0.027565, -0.005833, 0.020700, 0.015842, 0.019148, 0.020203, -0.000698, -0.005337, -0.037400, -0.060144,
        -0.031893, -0.038396, -0.001949, 0.018901, -0.014268, -0.004721, -0.055913, 0.013814, 0.215024, -0.011357, 0.057530, 0.050092, 0.016513, -0.059254, 0.001494, -0.031472,
        0.032190, -0.047512, -0.020501, -0.002571, 0.007844, -0.063630, -0.043938, -0.079595, 0.032820, -0.021659, -0.003738, -0.035267, -0.013794, -0.021172, -0.046356, -0.077079,
        0.021526, -0.007447, -0.050276, -0.029743, 0.022208, -0.039137, -0.021426, -0.029825, 0.029390, -0.002943, 0.073158, -0.000435, -0.032029, -0.038524, -0.029886, 0.017473,
        0.013513, 0.022738, 0.000632, -0.073718, 0.029219, -0.018896, 0.007302, -0.116122, -0.013324, -0.012214, -0.005960, -0.003720, -0.155869, 0.019896, 0.016919, -0.021133,
        -0.066911, -0.000926, -0.020871, -0.015295, -0.086108, 0.014918, -0.009284, 0.001689, -0.038155, 0.039163, 0.015988, 0.014413, 0.034205, -0.053273, 0.001687, 0.012227,
        -0.007341, -0.006123, -0.005731, -0.026863, 0.060196, 0.028929, 0.019328, -0.033709, 0.038789, -0.015624, 0.013323, 0.053821, -0.015538, -0.001610, 0.012959, -0.013897,
        0.082010, 0.012866, -0.017269, 0.000017, -0.059458, 0.015870, 0.028455, 0.025234, -0.051163, -0.022976, 0.011866, -0.005613, -0.008738, -0.047658, -0.002155, -0.029432,
        0.039242, -0.013491, -0.001641, -0.024210, -0.019187, 0.026716, -0.025698, -0.027591, -0.034678, -0.002473, -0.019391, 0.017597, 0.064385, -0.029104, -0.034501, -0.004955,
        0.015008, 0.060749, -0.051693, 0.020279, -0.027170, -0.027003, 0.000254, 0.011352, -0.028116, 0.028938, -0.007224, 0.019978, -0.025379, -0.004874, -0.019361, -0.020278,
    ],
    dtype=torch.float32,
)
SYSTEM_EN_RECAPTION = torch.tensor(
    [
        0.007721, 0.015421, -0.019305, -0.000920, 0.016031, -0.019730, 0.029683, 0.026810, -0.010510, 0.021463, 0.008833, -0.040851, 0.043260, -0.007042, 0.057224, 0.011995,
        0.007818, 0.046369, 0.059838, -0.028548, -0.047399, -0.000983, 0.024343, -0.052259, -0.013638, 0.006856, 0.009186, 0.014235, -0.031497, -0.008644, -0.009349, 0.018900,
        0.002913, -0.022475, 0.039518, 0.019052, -0.007600, 0.010634, -0.011830, 0.075675, -0.071738, -0.014947, 0.004995, -0.025804, -0.002553, -0.093262, 0.002881, -0.033744,
        -0.007234, 0.013659, 0.009897, 0.039185, -0.005366, 0.041534, -0.005924, 0.019786, 0.048566, -0.009356, -0.027360, 0.042557, 0.091286, 0.009286, 0.015410, 0.028166,
        0.022476, -0.025162, 0.012144, 0.084603, -0.003150, -0.008549, -0.002099, -0.014987, -0.019480, 0.046843, -0.030613, 0.015557, -0.008965, -0.008798, -0.027032, -0.014112,
        0.018703, -0.014749, -0.000928, -0.024660, 0.024004, 0.004560, 0.028156, -0.028467, 0.025444, -0.038699, -0.014927, -0.031593, -0.648498, 0.018529, 0.003378, 0.030188,
        -0.002314, 0.014950, -0.146615, -0.009005, 0.016579, -0.037867, 0.020907, 0.033160, 0.007877, -0.026345, -0.056428, 0.031255, -0.018404, 0.013334, 0.009988, -0.022790,
        0.020803, -0.036862, 0.036222, -0.006646, -0.058084, -0.012036, 0.044199, -0.027665, -0.015779, 0.051554, 0.059970, -0.025977, 0.003967, -0.035247, -0.000488, 0.023182,
        0.000468, 0.019190, 0.047268, -0.032279, -0.005302, 0.078669, -0.001915, 0.024918, -0.014952, -0.078905, -0.018333, 0.001362, -0.015115, 0.005435, 0.002313, 0.018766,
        -0.032773, 0.037344, 0.024061, 0.012143, -0.057106, 0.029490, 0.019537, 0.009099, 0.026064, -0.015927, -0.037047, 0.006002, 0.025191, -0.035318, -0.032245, -0.047822,
        -0.023568, -0.004533, 0.025100, 0.002758, -0.002649, -0.012287, -0.012139, 0.043080, 0.003295, 0.024667, -0.021050, 0.006752, 0.025315, -0.011127, 0.009800, -0.021343,
        -0.024866, 0.010098, 0.026954, 0.012467, -0.035866, -0.031780, 0.007479, -0.003388, -0.012619, -0.012099, 0.014974, -0.001908, -0.032700, 0.004703, 0.003238, -0.007498,
        0.023241, 0.002715, -0.111739, 0.003317, 0.006475, -0.019792, -0.046558, -0.032593, -0.020762, -0.005059, 0.016934, 0.029195, 0.028744, -0.050633, 0.001907, -0.028791,
        -0.016695, 0.052143, 0.010439, 0.007204, 0.028502, 0.012607, -0.012414, -0.031238, 0.007305, 0.032309, 0.087924, -0.010530, 0.029925, 0.032666, -0.002202, 0.017539,
        -0.009091, -0.001631, 0.024906, -0.013102, 0.031772, 0.018465, 0.012035, 0.031460, 0.030193, 0.005289, 0.025859, -0.038971, -0.046577, -0.025852, 0.035235, -0.038514,
        0.001042, 0.013012, 0.023701, -0.014630, -0.029269, -0.011981, 0.008219, -0.067347, -0.003456, 0.028198, -0.008657, -0.017773, 0.010540, 0.023964, 0.021012, -0.034465,
        -0.023748, 0.004065, -0.021598, 0.008440, -0.031533, 0.038390, -0.007680, -0.003852, 0.016136, -0.017906, -0.008927, 0.006300, -0.001251, 0.029337, -0.008632, 0.020568,
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        -0.035588, 0.003756, 0.015383, -0.013358, 0.009385, -0.001359, 0.012623, -0.028724, 0.001607, 0.012809, 0.032668, 0.011834, -0.015587, -0.007170, -0.021344, -0.019664,
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        0.095075, 0.019901, -0.019114, 0.022832, 0.003741, 0.027148, 0.018231, 0.027741, 0.020328, 0.001700, -0.006939, -0.024154, 0.018523, -0.029819, 0.008050, -0.004477,
        0.006087, 0.056878, -0.009083, -0.061537, -0.011531, -0.037551, 0.000434, -0.005843, 0.024739, 0.032020, -0.053119, 0.020704, -0.012385, -0.002726, -0.082489, 0.009072,
        0.013341, 0.000316, 0.001899, 0.022868, 0.034407, -0.066857, 0.020589, 0.012195, 0.023211, -0.001520, 0.000897, 0.029670, -0.015930, 0.006509, -0.035172, -0.061215,
        -0.014099, -0.038584, -0.012213, 0.018613, -0.012365, -0.002777, -0.055184, 0.017146, 0.214358, -0.015750, 0.052488, 0.045205, 0.025334, -0.054615, 0.002117, -0.038122,
        0.012402, -0.053418, -0.025405, 0.007235, 0.013208, -0.092481, -0.048700, -0.085186, 0.029039, -0.036767, -0.000777, -0.017625, -0.012556, -0.004887, -0.033660, -0.082310,
        0.013387, -0.003256, -0.062981, -0.019886, 0.017624, -0.037421, -0.020743, -0.020894, 0.041974, -0.008502, 0.088413, -0.018697, -0.029398, -0.029389, -0.043721, 0.013872,
        0.003944, 0.030361, 0.005355, -0.081355, 0.041843, -0.016395, 0.011954, -0.060440, -0.000966, -0.019101, 0.006803, -0.011310, -0.148581, 0.020342, 0.012795, -0.016473,
        -0.053300, -0.012340, -0.016640, -0.029834, -0.082405, 0.011859, -0.004255, -0.004396, -0.012515, 0.031962, 0.030438, 0.013792, 0.031557, -0.047200, 0.006485, 0.024815,
        -0.019376, -0.011454, -0.034184, -0.021329, 0.050115, 0.021720, 0.002874, -0.047163, 0.044031, -0.014663, 0.020534, 0.056017, 0.007017, 0.003323, 0.005734, -0.002777,
        0.082836, 0.012048, -0.023236, -0.007401, -0.071598, 0.016760, 0.017282, 0.028306, -0.026220, -0.008016, -0.000202, -0.020271, -0.019828, -0.046986, -0.005805, -0.039647,
        0.042879, -0.004463, 0.007753, -0.028916, -0.020612, 0.028833, -0.039839, -0.052447, -0.013275, -0.002407, -0.018937, 0.033216, 0.075535, -0.045026, -0.009901, 0.016637,
        -0.000322, 0.073925, -0.055701, 0.014912, -0.045671, -0.021189, 0.006761, -0.002015, -0.027410, 0.018250, -0.015916, 0.016254, -0.044964, 0.029261, -0.029319, -0.005222,
    ],
    dtype=torch.float32,
)
SYSTEM_EN_THINK_RECAPTION = torch.tensor(
    [
        0.011004, 0.017341, -0.019959, -0.018314, 0.016520, -0.027395, 0.017946, 0.039665, 0.000645, 0.035903, 0.002499, -0.045664, 0.039472, -0.013479, 0.081302, 0.000182,
        0.006947, 0.042845, 0.059741, -0.010796, -0.035240, 0.004176, 0.029557, -0.043467, -0.017271, 0.006896, 0.010997, 0.022498, -0.023308, -0.013046, -0.000742, 0.016209,
        -0.007152, -0.029868, 0.028747, 0.033743, -0.000227, 0.018419, -0.015023, 0.050376, -0.098475, -0.002375, 0.007897, -0.023936, 0.007843, -0.122463, -0.011680, -0.027267,
        -0.007270, 0.021869, -0.011415, 0.043770, 0.000551, 0.048573, 0.003132, 0.014233, 0.037080, -0.004818, -0.028738, 0.044468, 0.073843, 0.016947, 0.014484, 0.021931,
        0.020110, -0.032309, -0.003811, 0.095704, -0.006950, -0.007237, -0.005529, -0.020573, -0.016259, 0.041909, -0.038748, 0.018029, 0.005066, -0.021186, -0.020102, -0.019719,
        0.006239, -0.021284, 0.004213, -0.024963, 0.032345, -0.012557, 0.037268, -0.038075, 0.040998, -0.032766, -0.023509, -0.016426, -0.627412, 0.022675, 0.000101, 0.023162,
        -0.002081, 0.015922, -0.138671, -0.027995, 0.011579, -0.042859, 0.019935, 0.038077, 0.012640, -0.017377, -0.027456, 0.035151, -0.015756, 0.018530, 0.004646, -0.002589,
        0.019645, -0.043736, 0.034947, -0.010166, -0.061165, -0.019195, 0.028909, -0.019415, -0.009485, 0.049566, 0.068621, -0.038644, 0.011278, -0.036133, 0.000564, 0.022611,
        -0.013612, 0.020854, 0.030614, -0.025578, 0.005673, 0.076526, -0.004887, 0.027769, -0.022605, -0.092657, -0.013218, 0.008081, -0.015227, 0.018031, -0.005145, 0.015028,
        -0.027193, 0.034767, 0.028710, 0.032007, -0.053175, 0.033528, 0.019437, 0.011517, 0.012107, -0.027679, -0.026937, 0.008612, 0.036909, -0.051484, -0.039971, -0.034372,
        -0.023825, -0.003025, 0.033648, -0.001852, 0.007309, 0.000714, -0.001075, 0.038534, 0.007586, 0.016213, -0.025223, -0.001099, 0.015852, -0.011477, 0.020635, -0.010696,
        -0.019634, 0.025613, 0.034374, 0.007169, -0.035000, -0.032268, 0.015114, -0.014217, -0.005229, -0.005495, 0.018189, -0.011360, -0.026755, 0.007036, -0.002333, -0.001174,
        0.014729, 0.001739, -0.108591, 0.004699, 0.002048, -0.014801, -0.042855, -0.028846, -0.009609, -0.004500, 0.019466, 0.021848, 0.022140, -0.063035, -0.004272, -0.030798,
        -0.018452, 0.055169, 0.012240, -0.003555, 0.038293, 0.008503, -0.016608, -0.021309, 0.000690, 0.027093, 0.088054, -0.008881, 0.034087, 0.030647, 0.003284, 0.005038,
        -0.008359, 0.006311, 0.032462, -0.009699, 0.035283, 0.015261, 0.012827, 0.038169, 0.033959, -0.018048, 0.018122, -0.025259, -0.040084, -0.030879, 0.019853, -0.042558,
        -0.011938, 0.019602, 0.016537, -0.003378, -0.027890, -0.014909, -0.005464, -0.071862, 0.012335, 0.021899, -0.017008, -0.023228, 0.003263, 0.004571, 0.016447, -0.029446,
        -0.022645, -0.001261, -0.018573, 0.007431, -0.027587, 0.035362, -0.006785, -0.000614, 0.026044, -0.009056, -0.009843, 0.010467, -0.011929, 0.042025, -0.014068, 0.023113,
        0.023880, 0.014948, 0.004370, -0.005262, 0.012587, 0.021608, -0.001783, 0.023697, -0.024945, -0.011533, -0.020953, -0.007205, -0.024693, 0.012961, -0.168760, 0.001767,
        -0.041265, -0.007044, 0.015021, -0.008407, 0.029642, -0.000956, 0.008607, -0.035365, -0.012187, 0.011744, 0.032612, 0.006226, -0.015891, -0.017747, -0.022565, -0.024505,
        0.031279, 0.004188, 0.011939, 0.038032, 0.008798, 0.012314, -0.024830, 0.034484, 0.076395, -0.060108, 0.001019, -0.016138, 0.067729, 0.003899, -0.029845, -0.019960,
        0.086663, 0.040965, -0.010458, 0.027808, -0.006394, 0.017343, 0.014788, 0.024756, 0.016446, -0.012537, -0.008406, -0.028109, 0.013369, -0.033571, 0.012170, -0.002199,
        0.005263, 0.052280, -0.018171, -0.047898, -0.010087, -0.038632, 0.006773, -0.000838, 0.011197, 0.038187, -0.049525, 0.021689, -0.007385, -0.005987, -0.094551, 0.019019,
        0.012760, 0.009617, -0.002262, 0.030228, 0.047823, -0.079764, 0.023391, -0.005561, 0.018866, 0.012817, 0.020878, 0.027037, -0.013905, -0.002874, -0.035522, -0.046266,
        -0.032448, -0.036010, -0.007776, 0.016512, -0.012279, -0.005665, -0.057974, 0.016967, 0.202836, -0.009066, 0.066093, 0.045689, 0.018319, -0.048465, 0.000242, -0.040874,
        0.027824, -0.049045, -0.015616, -0.000307, 0.009163, -0.072975, -0.042979, -0.082254, 0.040549, -0.027049, 0.000725, -0.034118, -0.019604, -0.019097, -0.042483, -0.075446,
        0.019387, -0.005218, -0.053573, -0.029975, 0.008195, -0.036608, -0.018920, -0.025610, 0.028426, -0.002688, 0.074996, -0.003423, -0.032505, -0.030565, -0.028142, 0.014437,
        0.013359, 0.019376, 0.008356, -0.069731, 0.031824, -0.011103, 0.019327, -0.117090, -0.009352, -0.010290, -0.002129, -0.009198, -0.172915, 0.021232, 0.017274, -0.030060,
        -0.061449, -0.006598, -0.013069, -0.012857, -0.081220, 0.019058, -0.004841, 0.003066, -0.037741, 0.041806, 0.018281, 0.009458, 0.036761, -0.044987, 0.003557, 0.008890,
        -0.008011, -0.004063, -0.013474, -0.022090, 0.055398, 0.037475, 0.006991, -0.035962, 0.045503, -0.017162, 0.022391, 0.052754, -0.005924, -0.005936, 0.012673, -0.017922,
        0.084548, 0.014695, -0.013817, 0.000421, -0.065167, 0.018269, 0.023317, 0.023523, -0.034229, -0.019588, 0.007911, -0.002426, -0.017109, -0.050870, 0.002848, -0.033077,
        0.043451, -0.010609, -0.000375, -0.023206, -0.018155, 0.027102, -0.036006, -0.035115, -0.023922, 0.005989, -0.015372, 0.027123, 0.075210, -0.035302, -0.029799, 0.003642,
        0.007714, 0.063498, -0.053234, 0.015699, -0.040459, -0.027354, -0.002433, 0.010923, -0.020134, 0.029292, -0.010176, 0.013508, -0.032403, 0.004323, -0.017504, -0.015237,
    ],
    dtype=torch.float32,
)
SYSTEM_EN_VANILLA = torch.tensor(
    [
        0.010809, 0.021177, -0.017600, -0.016814, 0.012351, -0.024554, 0.018299, 0.039305, 0.003331, 0.030473, 0.005557, -0.040898, 0.047294, -0.016136, 0.076989, -0.002723,
        0.017622, 0.042330, 0.058266, -0.016232, -0.029502, 0.004529, 0.033543, -0.041481, -0.017631, 0.002727, 0.018874, 0.019932, -0.030052, -0.009997, 0.004582, 0.002135,
        -0.003720, -0.030923, 0.021174, 0.034033, -0.007096, 0.011522, -0.009518, 0.055688, -0.092351, -0.003914, 0.004589, -0.032635, 0.012479, -0.140607, -0.014141, -0.031821,
        0.001396, 0.026780, -0.007623, 0.039957, 0.006434, 0.047516, 0.014377, 0.015237, 0.034212, 0.003576, -0.027357, 0.038888, 0.087272, 0.020248, 0.015165, 0.016002,
        0.020781, -0.040509, -0.008929, 0.080857, -0.002642, -0.009738, -0.005683, -0.000615, -0.012801, 0.046457, -0.045004, 0.024689, 0.002498, -0.017333, -0.027366, -0.023231,
        -0.006064, -0.021505, 0.007405, -0.021249, 0.026252, -0.018690, 0.020093, -0.036954, 0.037510, -0.032027, -0.030871, -0.011173, -0.618627, 0.021213, -0.004366, 0.029555,
        -0.004324, 0.020221, -0.143832, -0.021386, 0.010482, -0.042113, 0.016164, 0.040350, 0.014627, -0.011778, -0.018102, 0.035380, -0.020305, 0.010590, 0.009227, -0.011415,
        0.018623, -0.036384, 0.031003, -0.017073, -0.056456, -0.010423, 0.033029, -0.023511, -0.008717, 0.045716, 0.068273, -0.027886, 0.009665, -0.039801, 0.001465, 0.024361,
        -0.015039, 0.022903, 0.033362, -0.022804, 0.008631, 0.076518, 0.000619, 0.022786, -0.015435, -0.095242, -0.006092, 0.015496, -0.009081, 0.015740, 0.004280, 0.013103,
        -0.031836, 0.034241, 0.031836, 0.032636, -0.053721, 0.034370, 0.019172, 0.018383, 0.006907, -0.036039, -0.027927, 0.008646, 0.040496, -0.060314, -0.039116, -0.021488,
        -0.031682, -0.005077, 0.034920, 0.002148, -0.008087, 0.002024, -0.008480, 0.041096, 0.011401, 0.020380, -0.025078, 0.005002, 0.022252, -0.014577, 0.008051, -0.014476,
        -0.007078, 0.021075, 0.036965, 0.005343, -0.038671, -0.037222, 0.014052, -0.009952, -0.003958, -0.001878, 0.017848, -0.016608, -0.030813, 0.010921, 0.001068, 0.003095,
        0.007076, -0.001936, -0.102996, 0.006838, -0.005243, -0.009140, -0.043796, -0.027227, -0.008426, -0.013177, 0.015602, 0.021036, 0.025484, -0.064836, -0.003593, -0.038036,
        -0.023102, 0.064053, 0.007850, 0.000771, 0.039297, 0.011903, -0.015866, -0.017612, 0.006308, 0.024342, 0.086761, -0.016705, 0.039239, 0.025079, -0.006452, 0.003174,
        -0.010146, 0.010787, 0.035932, -0.015346, 0.037191, 0.010990, 0.011573, 0.044958, 0.035560, -0.017339, 0.018878, -0.025394, -0.044339, -0.029852, 0.015951, -0.032248,
        -0.012019, 0.013497, 0.012224, -0.001284, -0.034041, -0.015768, 0.000230, -0.086076, 0.024878, 0.031929, -0.016668, -0.019815, -0.001325, 0.007944, 0.017674, -0.036097,
        -0.019651, -0.001272, -0.032842, 0.002056, -0.037140, 0.043191, -0.003710, 0.011767, 0.020313, -0.018396, -0.015935, 0.010228, -0.017349, 0.049363, -0.010007, 0.019533,
        0.018076, 0.016608, -0.005523, -0.007793, 0.016868, 0.019341, -0.008236, 0.026765, -0.025324, -0.007849, -0.023648, -0.007791, -0.018508, 0.015357, -0.166499, -0.003718,
        -0.035447, -0.005229, 0.019327, -0.014207, 0.028433, -0.002619, 0.013888, -0.033146, -0.017015, 0.004677, 0.039554, 0.003803, -0.014592, -0.018886, -0.023868, -0.022708,
        0.033661, 0.008626, 0.015687, 0.046395, 0.014173, 0.015083, -0.025994, 0.039120, 0.076334, -0.061165, 0.001791, -0.017579, 0.067567, -0.002415, -0.032495, -0.025576,
        0.079027, 0.036370, -0.013303, 0.030510, -0.009061, 0.019135, 0.015627, 0.024864, 0.015093, -0.017066, -0.014075, -0.021907, 0.017388, -0.033492, 0.013317, -0.000040,
        0.003396, 0.044030, -0.009194, -0.049524, -0.005015, -0.040007, 0.009104, 0.000580, 0.005603, 0.035891, -0.038913, 0.023239, -0.017022, -0.002695, -0.095759, 0.018503,
        0.017365, 0.011104, -0.003433, 0.024113, 0.052609, -0.085274, 0.027565, -0.005833, 0.020700, 0.015842, 0.019148, 0.020203, -0.000698, -0.005337, -0.037400, -0.060144,
        -0.031893, -0.038396, -0.001949, 0.018901, -0.014268, -0.004721, -0.055913, 0.013814, 0.215024, -0.011357, 0.057530, 0.050092, 0.016513, -0.059254, 0.001494, -0.031472,
        0.032190, -0.047512, -0.020501, -0.002571, 0.007844, -0.063630, -0.043938, -0.079595, 0.032820, -0.021659, -0.003738, -0.035267, -0.013794, -0.021172, -0.046356, -0.077079,
        0.021526, -0.007447, -0.050276, -0.029743, 0.022208, -0.039137, -0.021426, -0.029825, 0.029390, -0.002943, 0.073158, -0.000435, -0.032029, -0.038524, -0.029886, 0.017473,
        0.013513, 0.022738, 0.000632, -0.073718, 0.029219, -0.018896, 0.007302, -0.116122, -0.013324, -0.012214, -0.005960, -0.003720, -0.155869, 0.019896, 0.016919, -0.021133,
        -0.066911, -0.000926, -0.020871, -0.015295, -0.086108, 0.014918, -0.009284, 0.001689, -0.038155, 0.039163, 0.015988, 0.014413, 0.034205, -0.053273, 0.001687, 0.012227,
        -0.007341, -0.006123, -0.005731, -0.026863, 0.060196, 0.028929, 0.019328, -0.033709, 0.038789, -0.015624, 0.013323, 0.053821, -0.015538, -0.001610, 0.012959, -0.013897,
        0.082010, 0.012866, -0.017269, 0.000017, -0.059458, 0.015870, 0.028455, 0.025234, -0.051163, -0.022976, 0.011866, -0.005613, -0.008738, -0.047658, -0.002155, -0.029432,
        0.039242, -0.013491, -0.001641, -0.024210, -0.019187, 0.026716, -0.025698, -0.027591, -0.034678, -0.002473, -0.019391, 0.017597, 0.064385, -0.029104, -0.034501, -0.004955,
        0.015008, 0.060749, -0.051693, 0.020279, -0.027170, -0.027003, 0.000254, 0.011352, -0.028116, 0.028938, -0.007224, 0.019978, -0.025379, -0.004874, -0.019361, -0.020278,
    ],
    dtype=torch.float32,
)
SYSTEM_EN_UNIFIED = torch.tensor(
    [
        0.011409, 0.014191, -0.023163, -0.020119, 0.019190, -0.029559, 0.019616, 0.035872, 0.010434, 0.028709, 0.011616, -0.039422, 0.038369, -0.004631, 0.081177, 0.007400,
        0.008903, 0.040408, 0.055323, -0.011950, -0.026940, 0.004916, 0.028101, -0.046200, -0.016732, 0.005115, 0.012100, 0.016136, -0.026057, -0.013827, -0.004914, 0.015261,
        -0.010824, -0.028188, 0.022934, 0.026204, -0.003855, 0.013797, -0.014518, 0.050289, -0.100077, -0.002962, 0.009050, -0.028205, 0.016294, -0.128956, -0.012730, -0.023647,
        -0.009306, 0.020066, 0.000033, 0.043619, 0.003250, 0.053425, 0.005889, 0.021529, 0.036032, -0.003254, -0.029715, 0.048345, 0.077978, 0.010674, 0.019296, 0.018721,
        0.019244, -0.040115, -0.004245, 0.085214, -0.005280, -0.010746, -0.000164, -0.023405, -0.015641, 0.040193, -0.038735, 0.018966, -0.004031, -0.017879, -0.023017, -0.030379,
        0.006468, -0.015959, 0.000532, -0.026530, 0.042640, -0.006095, 0.037899, -0.043658, 0.040965, -0.034682, -0.023729, -0.019291, -0.630840, 0.029658, 0.005462, 0.026650,
        -0.000292, 0.013954, -0.149594, -0.019405, 0.015321, -0.045104, 0.030332, 0.031727, 0.012349, -0.009553, -0.022371, 0.034043, -0.014838, 0.015398, -0.003657, 0.000477,
        0.021084, -0.041406, 0.029946, -0.013832, -0.057358, -0.018086, 0.031598, -0.031835, -0.006697, 0.040866, 0.068602, -0.042203, 0.007362, -0.036959, 0.003794, 0.026533,
        -0.011873, 0.017343, 0.028333, -0.021804, 0.004007, 0.075133, 0.003340, 0.025326, -0.015068, -0.092280, -0.011514, 0.006827, -0.008254, 0.021181, -0.005035, 0.022263,
        -0.022443, 0.043919, 0.026637, 0.028568, -0.056881, 0.036740, 0.024430, 0.015891, 0.012257, -0.031126, -0.030108, 0.007229, 0.026998, -0.051685, -0.033003, -0.031170,
        -0.024021, 0.004235, 0.030164, 0.002674, 0.008018, 0.005532, 0.001621, 0.044790, 0.006413, 0.027160, -0.015022, 0.000911, 0.019723, -0.016244, 0.020077, -0.006847,
        -0.014110, 0.022461, 0.031656, 0.002760, -0.039078, -0.026893, 0.006628, -0.011775, -0.000240, -0.005908, 0.014943, -0.012131, -0.021755, 0.004732, -0.005297, -0.002922,
        0.014631, -0.002010, -0.112400, 0.000842, -0.002732, -0.014861, -0.052099, -0.034167, -0.011613, -0.006101, 0.013278, 0.018867, 0.026530, -0.068150, -0.003306, -0.032801,
        -0.018523, 0.050875, 0.005488, -0.007241, 0.045707, 0.023119, -0.021519, -0.022683, 0.004806, 0.024827, 0.091371, -0.014424, 0.043836, 0.033094, 0.002390, 0.005450,
        -0.004893, 0.013608, 0.031272, -0.002449, 0.031607, 0.014646, 0.014146, 0.043995, 0.028826, -0.012219, 0.021008, -0.020911, -0.036967, -0.036256, 0.013328, -0.038382,
        -0.012084, 0.018183, 0.018782, -0.004697, -0.024284, -0.015474, -0.001463, -0.076015, 0.013923, 0.022125, -0.018765, -0.010793, 0.008409, 0.002067, 0.017961, -0.029716,
        -0.020915, -0.001779, -0.009217, -0.001933, -0.036081, 0.042577, 0.000118, -0.013920, 0.014901, -0.016486, -0.010278, -0.000449, -0.017234, 0.042453, -0.009893, 0.021087,
        0.017671, 0.009861, -0.004210, 0.004944, 0.015627, 0.014370, -0.001128, 0.030247, -0.019552, -0.014017, -0.020859, -0.002614, -0.024405, 0.016532, -0.173204, -0.001196,
        -0.037415, -0.010990, 0.010449, -0.006124, 0.019211, 0.003695, 0.011679, -0.031852, -0.009764, 0.005773, 0.035793, 0.003455, -0.011772, -0.020532, -0.027434, -0.024761,
        0.027483, -0.001554, 0.010411, 0.037888, 0.015619, 0.019186, -0.021204, 0.038158, 0.074991, -0.064521, -0.002503, -0.014499, 0.068165, 0.006145, -0.032891, -0.021540,
        0.091385, 0.047584, -0.009590, 0.028004, -0.002962, 0.021061, 0.014854, 0.025840, 0.016068, -0.014364, -0.016418, -0.033454, 0.011734, -0.036518, 0.013015, -0.003966,
        0.000855, 0.051373, -0.010960, -0.047078, -0.011048, -0.042015, 0.006818, 0.005483, 0.010251, 0.034951, -0.046162, 0.021258, -0.013397, -0.005259, -0.093775, 0.019974,
        0.014992, 0.004043, -0.005931, 0.035662, 0.050723, -0.083293, 0.028047, -0.008042, 0.020763, 0.016763, 0.022913, 0.027129, -0.014314, -0.009854, -0.039019, -0.044870,
        -0.028101, -0.038026, -0.006294, 0.018265, -0.015425, -0.007866, -0.052784, 0.010470, 0.200260, -0.007798, 0.064482, 0.046612, 0.025353, -0.059695, -0.001831, -0.039643,
        0.025148, -0.042752, -0.014928, -0.010216, 0.014195, -0.069149, -0.041424, -0.078360, 0.036999, -0.021357, 0.011032, -0.026564, -0.016214, -0.023440, -0.044723, -0.064498,
        0.018283, -0.007165, -0.051802, -0.026299, 0.005867, -0.034691, -0.020621, -0.030512, 0.024458, -0.011330, 0.066558, -0.004069, -0.031624, -0.030639, -0.037451, 0.013079,
        0.015152, 0.008058, 0.009223, -0.069514, 0.030702, -0.009681, 0.014826, -0.115441, -0.005514, -0.011925, 0.001046, -0.007148, -0.164128, 0.018043, 0.017001, -0.026352,
        -0.049691, -0.011637, -0.013045, -0.014851, -0.079469, 0.017692, -0.006575, 0.001063, -0.028299, 0.038777, 0.019930, 0.010641, 0.036955, -0.039004, -0.006477, 0.004278,
        -0.001006, -0.002514, -0.017242, -0.023927, 0.049113, 0.038393, 0.011633, -0.031537, 0.041725, -0.012146, 0.023445, 0.049999, -0.008538, 0.001319, 0.012732, -0.021170,
        0.082096, 0.009610, -0.025717, 0.002566, -0.060849, 0.017403, 0.032650, 0.018658, -0.030629, -0.025032, 0.005555, 0.000522, -0.009667, -0.043099, 0.005939, -0.027156,
        0.045634, -0.011986, 0.002713, -0.032225, -0.015494, 0.028734, -0.036528, -0.033101, -0.027174, 0.009490, -0.016537, 0.029435, 0.065709, -0.037711, -0.020497, -0.005578,
        0.011768, 0.061035, -0.044676, 0.016113, -0.042945, -0.022579, 0.002430, 0.012474, -0.018198, 0.030468, -0.016646, 0.019020, -0.035804, 0.001175, -0.018312, -0.010760,
    ],
    dtype=torch.float32,
)
# fmt: on
SYSTEM_PROMPT_CASES = [
    pytest.param("none", None, SEED_1234, id="none"),
    pytest.param("dynamic", "dynamic", SYSTEM_PROMPT_DYNAMIC, id="dynamic"),
    pytest.param("en_vanilla", "en_vanilla", SYSTEM_EN_VANILLA, id="en_vanilla"),
    pytest.param("en_recaption", "en_recaption", SYSTEM_EN_RECAPTION, id="en_recaption"),
    pytest.param("en_think_recaption", "en_think_recaption", SYSTEM_EN_THINK_RECAPTION, id="en_think_recaption"),
    pytest.param("en_unified", "en_unified", SYSTEM_EN_UNIFIED, id="en_unified"),
]


@pytest.fixture(scope="session")
def clip_bundle() -> tuple[CLIPModel, CLIPProcessor]:
    try:
        model = CLIPModel.from_pretrained(LOCAL_CLIP_PATH, local_files_only=True)
        processor = CLIPProcessor.from_pretrained(LOCAL_CLIP_PATH, local_files_only=True)
    except OSError as exc:
        pytest.skip(f"Could not load CLIP model from local cache ({LOCAL_CLIP_PATH}): {exc}")

    model.eval()
    return model, processor


@pytest.fixture(scope="module")
def omni() -> Generator[Omni, None, None]:
    with OmniRunner(
        MODEL_NAME,
        deploy_config=str(DEPLOY_CONFIG_PATH),
        mode="text-to-image",
    ) as runner:
        yield runner.omni


def _extract_generated_image(outputs: list[object]) -> Image.Image:
    if not outputs:
        raise AssertionError("No outputs were returned from Omni.generate()")

    first_output = outputs[0]
    if images := getattr(first_output, "images", None):
        return images[0]

    request_output = getattr(first_output, "request_output", None)
    if request_output is not None and (images := getattr(request_output, "images", None)):
        return images[0]

    raise AssertionError("No generated image found in Omni output")


def extract_embedding(image: Image.Image, clip_model: CLIPModel, clip_processor: CLIPProcessor) -> torch.Tensor:
    inputs = clip_processor(images=image.convert("RGB"), return_tensors="pt")
    with torch.inference_mode():
        features = clip_model.get_image_features(**inputs)
        features = F.normalize(features, p=2, dim=-1)
    return features.squeeze(0)


def compare_semantic(
    expected_embedding: torch.Tensor,
    image: Image.Image,
    clip_model: CLIPModel,
    clip_processor: CLIPProcessor,
) -> float:
    features = extract_embedding(image, clip_model, clip_processor)
    expected = F.normalize(expected_embedding, p=2, dim=-1)
    return torch.dot(expected, features).item()


def _generate_image(omni: Omni, use_system_prompt: str | None) -> Image.Image:
    generator_device = current_omni_platform.device_type or "cuda"
    sampling_params = OmniDiffusionSamplingParams(
        seed=1234,
        generator=torch.Generator(device=generator_device).manual_seed(1234),
        num_outputs_per_prompt=1,
    )
    if use_system_prompt is not None:
        sampling_params.extra_args = {"use_system_prompt": use_system_prompt}

    outputs = omni.generate({"prompt": PROMPT}, sampling_params)
    return _extract_generated_image(outputs)


@pytest.mark.skipif(torch.accelerator.device_count() < 8, reason="Need at least 8 CUDA GPUs for this test.")
@pytest.mark.parametrize("system_prompt_name,use_system_prompt,expected_embedding", SYSTEM_PROMPT_CASES)
def test_system_prompt_scores(
    omni: Omni,
    clip_bundle: tuple[CLIPModel, CLIPProcessor],
    system_prompt_name: str,
    use_system_prompt: str | None,
    expected_embedding: torch.Tensor,
) -> None:
    clip_model, clip_processor = clip_bundle
    generated_image = _generate_image(omni, use_system_prompt)
    score = compare_semantic(expected_embedding, generated_image, clip_model, clip_processor)

    print(f"{system_prompt_name}: CLIP cosine similarity = {score:.6f}")