import pytest from .test_flux_dev import run_test_flux_dev @pytest.mark.parametrize( "height,width,num_inference_steps,cache_threshold,lora_name,use_qencoder,cpu_offload,expected_lpips", [ # (1024, 1024, 50, 0, None, False, False, 0.5), # 13min20s 5min55s 0.19539418816566467 # (1024, 1024, 50, 0.05, None, False, True, 0.5), # 7min11s 0.21917256712913513 # (1024, 1024, 50, 0.12, None, False, True, 0.5), # 2min58s, 0.24101486802101135 # (1024, 1024, 50, 0.2, None, False, True, 0.5), # 2min23s, 0.3101634383201599 # (1024, 1024, 50, 0.5, None, False, True, 0.5), # 1min44s 0.6543852090835571 # (1024, 1024, 30, 0, None, False, False, 0.5), # 8min2s 3min40s 0.2141970843076706 # (1024, 1024, 30, 0.05, None, False, True, 0.5), # 4min57 0.21297718584537506 # (1024, 1024, 30, 0.12, None, False, True, 0.5), # 2min34 0.25963714718818665 # (1024, 1024, 30, 0.2, None, False, True, 0.5), # 1min51 0.31409069895744324 # (1024, 1024, 20, 0, None, False, False, 0.5), # 5min25 2min29 0.18987375497817993 # (1024, 1024, 20, 0.05, None, False, True, 0.5), # 3min3 0.17194810509681702 # (1024, 1024, 20, 0.12, None, False, True, 0.5), # 2min15 0.19407868385314941 # (1024, 1024, 20, 0.2, None, False, True, 0.5), # 1min48 0.2832985818386078 (1024, 1024, 30, 0.12, None, False, False, 0.26), (512, 2048, 30, 0.12, "anime", True, False, 0.4), ], ) def test_flux_dev_base( height: int, width: int, num_inference_steps: int, cache_threshold: float, lora_name: str | None, use_qencoder: bool, cpu_offload: bool, expected_lpips: float, ): run_test_flux_dev( precision="int4", height=height, width=width, num_inference_steps=num_inference_steps, guidance_scale=3.5, use_qencoder=use_qencoder, cpu_offload=cpu_offload, lora_name=lora_name, lora_scale=1, cache_threshold=cache_threshold, max_dataset_size=16, expected_lpips=expected_lpips, )