loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
[oneflow] [vae] diffusers.OneFlowAutoencoderKL
[diffusers] [tokenizer] transformers.CLIPTokenizer
[oneflow] [unet] diffusers.OneFlowUNet2DConditionModel
[oneflow] [safety_checker] stable_diffusion.OneFlowStableDiffusionSafetyChecker
[oneflow] [scheduler] diffusers.OneFlowPNDMScheduler
[diffusers] [feature_extractor] transformers.CLIPFeatureExtractor
[oneflow] [text_encoder] transformers.OneFlowCLIPTextModel
[oneflow] compiling unet beforehand to make sure the progress bar is more accurate
[oneflow] [elapsed(s)] [unet compilation] 25.13586367602693
 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋  | 50/51 [00:02<00:00, 22.99it/s]
Traceback (most recent call last):
  File "demo.py", line 17, in <module>
    images = pipe(prompt).images
  File "/opt/conda/lib/python3.8/site-packages/oneflow/autograd/autograd_mode.py", line 154, in wrapper
    return func(*args, **kwargs)
  File "/code/diffusion/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_oneflow.py", line 321, in __call__
    latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample
  File "/code/diffusion/diffusers/src/diffusers/schedulers/scheduling_pndm_oneflow.py", line 223, in step
    return self.step_plms(model_output=model_output, timestep=timestep, sample=sample, return_dict=return_dict)
  File "/code/diffusion/diffusers/src/diffusers/schedulers/scheduling_pndm_oneflow.py", line 338, in step_plms
    prev_sample = self._get_prev_sample(sample, timestep, prev_timestep, model_output)
  File "/code/diffusion/diffusers/src/diffusers/schedulers/scheduling_pndm_oneflow.py", line 362, in _get_prev_sample
    if (alpha_prod_t_prev.dtype == torch.float64):
TypeError: Cannot interpret 'oneflow.float64' as a data type

Fetching 16 files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 16/16 [00:00<00:00, 25940.81it/s]
The config attributes {'upcast_attention': True} were passed to OneFlowUNet2DConditionModel, but are not expected and will be ignored. Please verify your config.json configuration file.
Traceback (most recent call last):
  File "sd-i.py", line 13, in <module>
    pipe = StableDiffusionImg2ImgPipeline.from_pretrained(model_id_or_path, torch_dtype=torch.float16)
  File "/root/zsf/oneflow/diffusers/src/diffusers/pipeline_oneflow_utils.py", line 706, in from_pretrained
    loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
  File "/root/zsf/oneflow/diffusers/src/diffusers/modeling_oneflow_utils.py", line 518, in from_pretrained
    raise ValueError(
ValueError: torch.float16 needs to be of type `torch.dtype`, e.g. `torch.float16`, but is <class 'torch.dtype'>.

[ERROR](GRAPH:UNetGraph_0:UNetGraph) building graph got error.
ERROR:root:Internal Error: Exception msg InferDataType Failed. Expected kFloat, but got kFloat16

python -m oneflow --doctor
loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
path: ['/usr/local/miniconda3/envs/py3.10.8/lib/python3.10/site-packages/oneflow']
version: 0.8.1+cu112.git.2a86da23
git_commit: 2a86da23
cmake_build_type: Release
rdma: True
mlir: True

WARNING: CUDA Minor Version Compatibility mode ENABLED.
  Using driver version 470.42.01 which has support for CUDA 11.4.  This container
  was built with CUDA 11.8 and will be run in Minor Version Compatibility mode.
  CUDA Forward Compatibility is preferred over Minor Version Compatibility for use
  with this container but was unavailable:
  [[System has unsupported display driver / cuda driver combination (CUDA_ERROR_SYSTEM_DRIVER_MISMATCH) cuInit()=803]]
  See https://docs.nvidia.com/deploy/cuda-compatibility/ for details.

loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
Fetching 16 files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 16/16 [00:00<00:00, 2110.81it/s]
[oneflow] [text_encoder] transformers.OneFlowCLIPTextModel
[oneflow] [unet] diffusers.OneFlowUNet2DConditionModel
[oneflow] [safety_checker] stable_diffusion.OneFlowStableDiffusionSafetyChecker
[diffusers] [feature_extractor] transformers.CLIPFeatureExtractor
[oneflow] [scheduler] diffusers.OneFlowPNDMScheduler
[diffusers] [tokenizer] transformers.CLIPTokenizer
ftfy or spacy is not installed using BERT BasicTokenizer instead of ftfy.
[oneflow] [vae] diffusers.OneFlowAutoencoderKL
[oneflow] compiling unet beforehand to make sure the progress bar is more accurate
[oneflow] [elapsed(s)] [unet compilation] 23.832770048989914
  0%|                                                                                                                                                                                       | 0/51 [00:00<?, ?it/s]F20221108 02:54:25.671985   157 fused_multi_head_attention_inference_kernel.cu:150] UNIMPLEMENTED
*** Check failure stack trace: ***
    @     0x7f35f204bf6a  google::LogMessage::Fail()
    @     0x7f35f204c252  google::LogMessage::SendToLog()
    @     0x7f35f204bad7  google::LogMessage::Flush()
    @     0x7f35f204e649  google::LogMessageFatal::~LogMessageFatal()
    @     0x7f35e6042d62  oneflow::user_op::(anonymous namespace)::DispatchArchTag<>()
    @     0x7f35eba61e2a  oneflow::user_op::(anonymous namespace)::DispatchArchTag<>()
    @     0x7f35eba584c5  oneflow::user_op::(anonymous namespace)::DispatchCutlassFmha()
    @     0x7f35eba65c4a  oneflow::user_op::(anonymous namespace)::FusedMultiHeadAttentionInferenceKernel::Compute()
    @     0x7f35eac67523  oneflow::UserKernel::ForwardUserKernel()
    @     0x7f35eac676a4  oneflow::UserKernel::ForwardDataContent()
    @     0x7f35eac35747  oneflow::Kernel::Forward()
    @     0x7f35eac360c0  oneflow::Kernel::Launch()
    @     0x7f35eacda00d  oneflow::(anonymous namespace)::LightActor<>::ProcessMsg()
    @     0x7f35eb23dfd0  oneflow::Thread::PollMsgChannel()
    @     0x7f35eb23e348  _ZNSt6thread11_State_implINS_8_InvokerISt5tupleIJZN7oneflow6ThreadC4ERKNS3_8StreamIdEEUlvE_EEEEE6_M_runEv
    @     0x7f35f20609af  execute_native_thread_routine
    @     0x7f36c8db1609  start_thread
    @     0x7f36c8b70133  clone

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
[<ipython-input-32-9857761ca7ed>](https://localhost:8080/#) in <module>
      2 from diffusers import OneFlowStableDiffusionPipeline
      3 
----> 4 pipe = OneFlowStableDiffusionPipeline.from_pretrained(
      5     "CompVis/stable-diffusion-v1-4",
      6     use_auth_token=True,

[/usr/local/lib/python3.8/dist-packages/diffusers/pipeline_oneflow_utils.py](https://localhost:8080/#) in from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
    714                 class_candidates = {c: class_obj for c in importable_classes.keys()}
    715             else:
--> 716                 with torch.mock_torch.enable():
    717                     # else we just import it from the library.
    718                     library = importlib.import_module(library_name)

AttributeError: module 'torch' has no attribute 'mock_torch'

loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
W20221108 11:30:13.097517 41659 cuda_device_descriptor_class.cpp:48] initialization error

loaded library: /usr/lib/x86_64-linux-gnu/libibverbs.so.1
W20221108 11:30:13.097517 41659 cuda_device_descriptor_class.cpp:48] initialization error
Fetching 16 files: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████| 16/16 [00:00<00:00, 17067.36it/s]
[oneflow] [unet] diffusers.OneFlowUNet2DConditionModel
[oneflow] [text_encoder] transformers.OneFlowCLIPTextModel
[oneflow] [safety_checker] stable_diffusion.OneFlowStableDiffusionSafetyChecker
[oneflow] [vae] diffusers.OneFlowAutoencoderKL
[diffusers] [feature_extractor] transformers.CLIPFeatureExtractor
[diffusers] [tokenizer] transformers.CLIPTokenizer
ftfy or spacy is not installed using BERT BasicTokenizer instead of ftfy.
[oneflow] [scheduler] diffusers.OneFlowPNDMScheduler
E20221108 11:30:41.811245 41659 cuda_device_manager_factory.cpp:65] Failed to get cuda runtime version: initialization error
F20221108 11:30:41.811539 41659 scheduler.cpp:125] Check failed: err : initialization error (3) 
*** Check failure stack trace: ***
    @     0x7f29565f0f6a  google::LogMessage::Fail()
    @     0x7f29565f1252  google::LogMessage::SendToLog()
    @     0x7f29565f0ad7  google::LogMessage::Flush()
    @     0x7f29565f3649  google::LogMessageFatal::~LogMessageFatal()
    @     0x7f294ef4e2f0  oneflow::boxing::collective::ExecutorImpl::Init()
    @     0x7f294ef4f6b5  oneflow::boxing::collective::Scheduler::Impl::Impl()
    @     0x7f294ef4fc93  oneflow::boxing::collective::Scheduler::Scheduler()
    @     0x7f294e6fa0b2  oneflow::MultiClientSessionContext::TryInit()
    @     0x7f294e6fab5e  oneflow::MultiClientSessionContext::TryInit()
    @     0x7f2a1e564dcf  (unknown)
    @     0x7f2a1e3f8f79  (unknown)
    @           0x4ffdb7  cfunction_call
    @           0x4f95eb  _PyObject_MakeTpCall.localalias
    @           0x50c73f  method_vectorcall
    @           0x4f4d0c  _PyEval_EvalFrameDefault
    @           0x5001ff  _PyFunction_Vectorcall
    @           0x4f0913  _PyEval_EvalFrameDefault
    @           0x50c44e  method_vectorcall
    @           0x4f4d0c  _PyEval_EvalFrameDefault
    @           0x4f893d  _PyObject_FastCallDictTstate.localalias
    @           0x509bc8  slot_tp_init
    @           0x4f963b  _PyObject_MakeTpCall.localalias
    @           0x4f4fcb  _PyEval_EvalFrameDefault
    @           0x5001ff  _PyFunction_Vectorcall
    @           0x4f89ed  _PyObject_FastCallDictTstate.localalias
    @           0x509bc8  slot_tp_init
    @           0x4f9956  type_call
    @           0x50d0d9  PyObject_Call
    @           0x4f2c32  _PyEval_EvalFrameDefault
    @           0x50c44e  method_vectorcall
    @           0x4f1592  _PyEval_EvalFrameDefault
    @           0x599fe2  _PyEval_Vector
Aborted (core dumped)

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/zhaodi/diffusers/src/diffusers/__init__.py", line 22, in <module>
    from transformers import CLIPTextModel, CLIPFeatureExtractor
  File "<frozen importlib._bootstrap>", line 1075, in _handle_fromlist
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1101, in __getattr__
    value = getattr(module, name)
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1100, in __getattr__
    module = self._get_module(self._class_to_module[name])
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1112, in _get_module
    raise RuntimeError(
RuntimeError: Failed to import transformers.models.clip.modeling_clip because of the following error (look up to see its traceback):
oneflow.cuda.amp.GradScaler is not implemented, please submit an issue at  
'https://github.com/Oneflow-Inc/oneflow/issues' including the log information of the error, the 
minimum reproduction code, and the system information.

sd init time  373.8917450904846 s.
==> function  text_to_image  try to run...
text_to_image  cuda mem before  4336.75  MB
text_to_image  host mem before  9173.0  MB
E
======================================================================
ERROR: test_sd_graph_save_and_load (__main__.OneFlowPipeLineGraphSaveLoadTests)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/zhaodi/work/test.py", line 175, in test_sd_graph_save_and_load
    _test_sd_graph_save_and_load(True, f0 ,f1, f2)
  File "/home/zhaodi/work/test.py", line 141, in _test_sd_graph_save_and_load
    no_g_images = text_to_image(prompt, (i, j), prefix=f"is_save_{str(is_save)}-", with_graph=False)
  File "/home/zhaodi/work/test.py", line 32, in new_fn
    out = fn(*args, **kwargs)
  File "/home/zhaodi/work/test.py", line 117, in text_to_image
    images = pipe(
  File "/home/zhaodi/oneflow/python/oneflow/autograd/autograd_mode.py", line 154, in wrapper
    return func(*args, **kwargs)
  File "/home/zhaodi/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_oneflow.py", line 620, in __call__
    text_embeddings = self._encode_prompt(
  File "/home/zhaodi/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_oneflow.py", line 393, in _encode_prompt
    text_embeddings = self.text_encoder(text_input_ids.to(device), attention_mask=attention_mask)
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/transformers/models/clip/modeling_clip.py", line 816, in forward
    return self.text_model(
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/transformers/models/clip/modeling_clip.py", line 712, in forward
    hidden_states = self.embeddings(input_ids=input_ids, position_ids=position_ids)
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/transformers/models/clip/modeling_clip.py", line 227, in forward
    inputs_embeds = self.token_embedding(input_ids)
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/torch/nn/modules/sparse.py", line 160, in forward
    return F.embedding(
  File "/home/zhaodi/miniconda3/lib/python3.10/site-packages/torch/nn/functional.py", line 2210, in embedding
    return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
TypeError: embedding(): argument 'indices' (position 2) must be Tensor, not Tensor

----------------------------------------------------------------------
Ran 1 test in 374.084s

FAILED (errors=1)

Traceback (most recent call last):
  File "demo_inference.py", line 8, in <module>
    from diffusers import StableDiffusionPipeline
  File "/root/diffusers/src/diffusers/__init__.py", line 21, in <module>
    from .models import AutoencoderKL, UNet2DConditionModel, UNet2DModel, VQModel
  File "/root/diffusers/src/diffusers/models/__init__.py", line 28, in <module>
    from .unet_2d_condition_oneflow import OneFlowUNet2DConditionModel
  File "/root/diffusers/src/diffusers/models/unet_2d_condition_oneflow.py", line 6, in <module>
    import oneflow.utils.checkpoint
ModuleNotFoundError: No module named 'oneflow.utils.checkpoint'

Traceback (most recent call last):
  File "oneflow-test.py", line 17, in <module>
    pipe = StableDiffusionPipeline.from_pretrained(
  File "/src/diffusers/src/diffusers/pipeline_oneflow_utils.py", line 657, in from_pretrained
    class_obj = getattr(library, class_name)
  File "/src/transformers/src/transformers/utils/import_utils.py", line 1043, in __getattr__
    raise AttributeError(f"module {self.__name__} has no attribute {name}")
AttributeError: module transformers has no attribute CLIPImageProcessor
Segmentation fault

(ldm) [root@VM-0-3-centos models]# python test.py
libibverbs not available, ibv_fork_init skipped
[oneflow] [vae] diffusers.OneFlowAutoencoderKL
[diffusers] [tokenizer] transformers.CLIPTokenizer
[oneflow] [unet] diffusers.OneFlowUNet2DConditionModel
[oneflow] [safety_checker] stable_diffusion.OneFlowStableDiffusionSafetyChecker
[diffusers] [feature_extractor] transformers.CLIPFeatureExtractor
[oneflow] [text_encoder] transformers.OneFlowCLIPTextModel
[oneflow] [scheduler] diffusers.OneFlowDDIMScheduler
[oneflow] compiling unet beforehand to make sure the progress bar is more accurate
[oneflow] [elapsed(s)] [unet compilation] 32.545996212400496
  0%|                                                                                                                             | 0/30 [00:00<?, ?it/s]
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /www/models/test.py:23 in <module>                                                               │
│                                                                                                  │
│   20 │   return images, False                                                                    │
│   21 pipe.safety_checker = dummy                                                                 │
│   22 pipe = pipe.to("cuda")                                                                      │
│ ❱ 23 image = pipe(prompt, num_inference_steps=30).images[0]                                      │
│   24 image.save(f"output.png")                                                                   │
│                                                                                                  │
│ /root/.conda/envs/ldm/lib/python3.8/site-packages/oneflow/autograd/autograd_mode.py:154 in       │
│ wrapper                                                                                          │
│                                                                                                  │
│   151 │   def __call__(self, func):                                                              │
│   152 │   │   def wrapper(*args, **kwargs):                                                      │
│   153 │   │   │   with AutoGradMode(False):                                                      │
│ ❱ 154 │   │   │   │   return func(*args, **kwargs)                                               │
│   155 │   │                                                                                      │
│   156 │   │   return wrapper                                                                     │
│   157                                                                                            │
│                                                                                                  │
│ /www/models/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_oneflow │
│ .py:345 in __call__                                                                              │
│                                                                                                  │
│   342 │   │   │   if isinstance(self.scheduler, LMSDiscreteScheduler):                           │
│   343 │   │   │   │   latents = self.scheduler.step(noise_pred, i, latents, **extra_step_kwarg   │
│   344 │   │   │   else:                                                                          │
│ ❱ 345 │   │   │   │   latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwarg   │
│   346 │   │   │   torch._oneflow_internal.profiler.RangePop()                                    │
│   347 │   │                                                                                      │
│   348 │   │   # scale and decode the image latents with vae                                      │
│                                                                                                  │
│ /www/models/diffusers/src/diffusers/schedulers/scheduling_ddim_oneflow.py:259 in step            │
│                                                                                                  │
│   256 │   │                                                                                      │
│   257 │   │   # 3. compute predicted original sample from predicted noise also called            │
│   258 │   │   # "predicted x_0" of formula (12) from https://arxiv.org/pdf/2010.02502.pdf        │
│ ❱ 259 │   │   pred_original_sample = (sample - beta_prod_t ** (0.5) * model_output) / alpha_pr   │
│   260 │   │                                                                                      │
│   261 │   │   # 4. Clip "predicted x_0"                                                          │
│   262 │   │   if self.config.clip_sample:                                                        │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 (positional 0) and cpu:0 (positional 1)!

Traceback (most recent call last):
  File "/root/tasker-anime_txt2img/run.py", line 102, in execute_task
    result = inpaint(model, prompt, negative_prompt, img_url, mask_url, seed, strength, scale, steps)
  File "/root/tasker-anime_txt2img/api.py", line 251, in inpaint
    drawer.draw(
  File "/root/tasker-anime_txt2img/drawer_oneflow.py", line 191, in draw
    result = pipe(**params)
  File "/root/.conda/envs/ai/lib/python3.10/site-packages/oneflow/autograd/autograd_mode.py", line 154, in wrapper
    return func(*args, **kwargs)
  File "/root/diffusers-oneflow-fork/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy_oneflow.py", line 565, in __call__
    device = self._execution_device
  File "/root/diffusers-oneflow-fork/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy_oneflow.py", line 279, in _execution_device
    if self.device != torch.device("meta") or not hasattr(self.unet, "_hf_hook"):
RuntimeError: Expected one of cpu, cuda device type at start of device string: meta

Traceback (most recent call last):
  File "/home/terrance/.local/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1110, in _get_module
    return importlib.import_module("." + module_name, self.__name__)
  File "/usr/lib/python3.10/importlib/__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
  File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 883, in exec_module
  File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
  File "/home/terrance/.local/lib/python3.10/site-packages/transformers/models/clip/modeling_clip.py", line 27, in <module>
    from ...modeling_utils import PreTrainedModel
  File "/home/terrance/.local/lib/python3.10/site-packages/transformers/modeling_utils.py", line 83, in <module>
    from accelerate import __version__ as accelerate_version
  File "/home/terrance/.local/lib/python3.10/site-packages/accelerate/__init__.py", line 7, in <module>
    from .accelerator import Accelerator
  File "/home/terrance/.local/lib/python3.10/site-packages/accelerate/accelerator.py", line 27, in <module>
    import torch.utils.hooks as hooks
  File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
  File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 674, in _load_unlocked
  File "<frozen importlib._bootstrap>", line 571, in module_from_spec
  File "/home/terrance/.local/lib/python3.10/site-packages/oneflow/mock_torch/__init__.py", line 88, in create_module
    raise NotImplementedError(oneflow_mod_fullname + error_msg)
NotImplementedError: oneflow.utils.hooks is not implemented, please submit an issue at  
'https://github.com/Oneflow-Inc/oneflow/issues' including the log information of the error, the 
minimum reproduction code, and the system information.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/terrance/oneflow/test_diffusion.py", line 2, in <module>
    from diffusers import OneFlowStableDiffusionPipeline
  File "/home/terrance/oneflow/diffusers/src/diffusers/__init__.py", line 22, in <module>
    from transformers import CLIPTextModel, CLIPFeatureExtractor
  File "<frozen importlib._bootstrap>", line 1075, in _handle_fromlist
  File "/home/terrance/.local/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1101, in __getattr__
    value = getattr(module, name)
  File "/home/terrance/.local/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1100, in __getattr__
    module = self._get_module(self._class_to_module[name])
  File "/home/terrance/.local/lib/python3.10/site-packages/transformers/utils/import_utils.py", line 1112, in _get_module
    raise RuntimeError(
RuntimeError: Failed to import transformers.models.clip.modeling_clip because of the following error (look up to see its traceback):
oneflow.utils.hooks is not implemented, please submit an issue at  
'https://github.com/Oneflow-Inc/oneflow/issues' including the log information of the error, the 
minimum reproduction code, and the system information.

Traceback (most recent call last):
  File "/workspace/node/threads/base.py", line 77, in image_generator
    image = pipe(
  File "/workspace/env/lib/python3.10/site-packages/oneflow/autograd/autograd_mode.py", line 154, in wrapper
    return func(*args, **kwargs)
  File "/workspace/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_oneflow.py", line 676, in __call__
    noise_pred = unet_graph(latent_model_input, t, text_embeddings)
  File "/workspace/diffusers/src/diffusers/oneflow_graph_compile_cache.py", line 63, in __call__
    return self.graph_(*args, **kwargs)
  File "/workspace/env/lib/python3.10/site-packages/oneflow/nn/graph/graph.py", line 250, in __call__
    return self.__run(*args, **kwargs)
  File "/workspace/env/lib/python3.10/site-packages/oneflow/nn/graph/graph.py", line 1481, in __run
    oneflow._oneflow_internal.nn.graph.RunLazyNNGraph(
oneflow._oneflow_internal.exception.RuntimeError: Error: nn.Graph ONLY accepts static inputs tensor meta, please check whether your input tensor meta each step is the same as the input of first call graph.
The excepted tensor meta is: shape=(), dtype=oneflow.int64, device=cpu:0, but the actual tensor meta is: shape=(), dtype=oneflow.float64, device=cpu:0. The input index is 1.

Python 3.7.3 (default, Jan 22 2021, 20:04:44) 
[GCC 8.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from diffusers import OneFlowStableDiffusionPipeline
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ImportError: cannot import name 'OneFlowStableDiffusionPipeline' from 'diffusers' (unknown location)

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