fal/AuraFlow · Warnings and slow generation

Hi, I'm getting the same warnings and would be interested too what the expected duration of the generation time is (it's actually 45s on a 4090 with the code below).

Code is the example from model card:

from diffusers import AuraFlowPipeline
import torch

pipeline = AuraFlowPipeline.from_pretrained(
    "fal/AuraFlow",
    torch_dtype=torch.float16
).to("cuda")

image = pipeline(
    prompt="close-up portrait of a majestic iguana with vibrant blue-green scales, piercing amber eyes, and orange spiky crest. Intricate textures and details visible on scaly skin. Wrapped in dark hood, giving regal appearance. Dramatic lighting against black background. Hyper-realistic, high-resolution image showcasing the reptile's expressive features and coloration.",
    height=1024,
    width=1024,
    num_inference_steps=50, 
    generator=torch.Generator().manual_seed(666),
    guidance_scale=3.5,
).images[0]

Installed dependencies are (created with pip freeze):

accelerate==0.33.0
anyio==4.4.0
argon2-cffi==23.1.0
argon2-cffi-bindings==21.2.0
arrow==1.3.0
asttokens==2.4.1
async-lru==2.0.4
attrs==23.2.0
Babel==2.15.0
beautifulsoup4==4.12.3
bleach==6.1.0
certifi==2024.7.4
cffi==1.16.0
charset-normalizer==3.3.2
comm==0.2.2
debugpy==1.8.2
decorator==5.1.1
defusedxml==0.7.1
diffusers @ git+https://github.com/huggingface/diffusers.git@2c25b98c8ea74cfb5ec56ba49cc6edafef0b26af
executing==2.0.1
fastjsonschema==2.20.0
filelock==3.15.4
fqdn==1.5.1
fsspec==2024.6.1
gitdb==4.0.11
GitPython==3.1.41
h11==0.14.0
httpcore==1.0.5
httpx==0.27.0
huggingface-hub==0.24.2
idna==3.7
importlib_metadata==8.2.0
ipykernel==6.29.5
ipython==8.26.0
ipywidgets==8.1.3
isoduration==20.11.0
jedi==0.19.1
Jinja2==3.1.4
json5==0.9.25
jsonpointer==3.0.0
jsonschema==4.23.0
jsonschema-specifications==2023.12.1
jupyter-events==0.10.0
jupyter-lsp==2.2.5
jupyter_client==8.6.2
jupyter_core==5.7.2
jupyter_server==2.14.2
jupyter_server_terminals==0.5.3
jupyterlab==4.2.3
jupyterlab_pygments==0.3.0
jupyterlab_server==2.27.3
jupyterlab_widgets==3.0.11
MarkupSafe==2.1.5
matplotlib-inline==0.1.7
mistune==3.0.2
mpmath==1.3.0
nbclient==0.10.0
nbconvert==7.16.4
nbformat==5.10.4
nest-asyncio==1.6.0
networkx==3.3
notebook_shim==0.2.4
numpy==1.26.4
nvidia-cublas-cu12==12.1.3.1
nvidia-cuda-cupti-cu12==12.1.105
nvidia-cuda-nvrtc-cu12==12.1.105
nvidia-cuda-runtime-cu12==12.1.105
nvidia-cudnn-cu12==9.1.0.70
nvidia-cufft-cu12==11.0.2.54
nvidia-curand-cu12==10.3.2.106
nvidia-cusolver-cu12==11.4.5.107
nvidia-cusparse-cu12==12.1.0.106
nvidia-nccl-cu12==2.20.5
nvidia-nvjitlink-cu12==12.5.82
nvidia-nvtx-cu12==12.1.105
overrides==7.7.0
packaging==24.1
pandocfilters==1.5.1
parso==0.8.4
pexpect==4.9.0
pillow==10.4.0
platformdirs==4.2.2
prometheus_client==0.20.0
prompt_toolkit==3.0.47
protobuf==5.27.2
psutil==6.0.0
ptyprocess==0.7.0
pure_eval==0.2.3
pycparser==2.22
Pygments==2.18.0
python-dateutil==2.9.0.post0
python-json-logger==2.0.7
PyYAML==6.0.1
pyzmq==26.0.3
referencing==0.35.1
regex==2024.5.15
requests==2.32.3
rfc3339-validator==0.1.4
rfc3986-validator==0.1.1
rpds-py==0.19.1
safetensors==0.4.3
Send2Trash==1.8.3
sentencepiece==0.2.0
setuptools==69.0.3
six==1.16.0
smmap==5.0.1
sniffio==1.3.1
soupsieve==2.5
stack-data==0.6.3
sympy==1.13.1
terminado==0.18.1
tinycss2==1.3.0
tokenizers==0.19.1
torch==2.4.0
tornado==6.4.1
tqdm==4.66.4
traitlets==5.14.3
transformers==4.43.2
triton==3.0.0
types-python-dateutil==2.9.0.20240316
typing_extensions==4.12.2
uri-template==1.3.0
urllib3==2.2.2
wcwidth==0.2.13
webcolors==24.6.0
webencodings==0.5.1
websocket-client==1.8.0
wheel==0.43.0
widgetsnbextension==4.0.11
zipp==3.19.2

Thanks