我用macos启动janus-pro1B模型只能使用图生文，用文生图时报错，请帮忙解决

[packyzhou]

(janus_pro) zhoujingwei@MrJoe-Macbook-pro2022 Janus % python demo/app_januspro.py
/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/transformers/models/auto/image_processing_auto.py:590: FutureWarning: The image_processor_class argument is deprecated and will be removed in v4.42. Please use slow_image_processor_class, or fast_image_processor_class instead
warnings.warn(
Using a slow image processor as use_fast is unset and a slow processor was saved with this model. use_fast=True will be the default behavior in v4.48, even if the model was saved with a slow processor. This will result in minor differences in outputs. You'll still be able to use a slow processor with use_fast=False.
You are using the default legacy behaviour of the <class 'transformers.models.llama.tokenization_llama_fast.LlamaTokenizerFast'>. This is expected, and simply means that the legacy (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set legacy=False. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in huggingface/transformers#24565 - if you loaded a llama tokenizer from a GGUF file you can ignore this message.
Some kwargs in processor config are unused and will not have any effect: sft_format, ignore_id, image_tag, add_special_token, mask_prompt, num_image_tokens.
Running on local URL: http://127.0.0.1:7860

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Traceback (most recent call last):
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/gradio/queueing.py", line 536, in process_events
response = await route_utils.call_process_api(
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/gradio/route_utils.py", line 322, in call_process_api
output = await app.get_blocks().process_api(
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/gradio/blocks.py", line 1935, in process_api
result = await self.call_function(
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/gradio/blocks.py", line 1520, in call_function
prediction = await anyio.to_thread.run_sync( # type: ignore
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/anyio/to_thread.py", line 56, in run_sync
return await get_async_backend().run_sync_in_worker_thread(
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 2461, in run_sync_in_worker_thread
return await future
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/anyio/_backends/_asyncio.py", line 962, in run
result = context.run(func, *args)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/gradio/utils.py", line 826, in wrapper
response = f(*args, **kwargs)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "/Users/zhoujingwei/Desktop/worke/project/Janus/demo/app_januspro.py", line 160, in generate_image
output, patches = generate(input_ids,
File "/Users/zhoujingwei/Desktop/worke/project/Janus/demo/app_januspro.py", line 118, in generate
patches = vl_gpt.gen_vision_model.decode_code(generated_tokens.to(dtype=torch.int),
File "/Users/zhoujingwei/Desktop/worke/project/Janus/janus/models/vq_model.py", line 507, in decode_code
dec = self.decode(quant_b)
File "/Users/zhoujingwei/Desktop/worke/project/Janus/janus/models/vq_model.py", line 502, in decode
dec = self.decoder(quant)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
return forward_call(*args, **kwargs)
File "/Users/zhoujingwei/Desktop/worke/project/Janus/janus/models/vq_model.py", line 208, in forward
h = block.upsample(h)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
return forward_call(*args, **kwargs)
File "/Users/zhoujingwei/Desktop/worke/project/Janus/janus/models/vq_model.py", line 426, in forward
x = self.conv(x)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
return forward_call(*args, **kwargs)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/nn/modules/conv.py", line 554, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torch/nn/modules/conv.py", line 549, in _conv_forward
return F.conv2d(
RuntimeError: Input type (c10::BFloat16) and bias type (c10::Half) should be the same

[hail100]

可以改一下python依赖版本试试

torch==2.3.1
transformers==4.43.1
tokenizers==0.19.1

[packyzhou]

可以改一下python依赖版本试试

torch==2.3.1
transformers==4.43.1
tokenizers==0.19.1

更糟糕了，启动都启动不了

Traceback (most recent call last):
File "/Users/zhoujingwei/Desktop/worke/project/Janus/demo/app_januspro.py", line 4, in
from janus.models import MultiModalityCausalLM, VLChatProcessor
File "/Users/zhoujingwei/Desktop/worke/project/Janus/janus/models/init.py", line 20, in
from .image_processing_vlm import VLMImageProcessor
File "/Users/zhoujingwei/Desktop/worke/project/Janus/janus/models/image_processing_vlm.py", line 24, in
import torchvision
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torchvision/init.py", line 10, in
from torchvision import _meta_registrations, datasets, io, models, ops, transforms, utils # usort:skip
File "/Users/zhoujingwei/anaconda3/envs/janus_pro/lib/python3.9/site-packages/torchvision/_meta_registrations.py", line 163, in
@torch.library.register_fake("torchvision::nms")
AttributeError: module 'torch.library' has no attribute 'register_fake'