error OverflowError: cannot fit 'int' into an index-sized integer
This is my test code:
'''
from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained(
"./",
torch_dtype=torch.float16,
variant="fp16",
).to("cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt=prompt, num_inference_steps=50, guidance_scale=3).images[0]
'''
Traceback (most recent call last):
File "D:****\demo.py", line **, in
image = pipe(prompt=prompt, num_inference_steps=50, guidance_scale=3).images[0]
File "d:\anaconda3\envs\pytorch2\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "d:\anaconda3\envs\pytorch2\lib\site-packages\diffusers\pipelines\stable_diffusion_xl\pipeline_stable_diffusion_xl.py", line 1054, in call
) = self.encode_prompt(
File "d:\anaconda3\envs\pytorch2\lib\site-packages\diffusers\pipelines\stable_diffusion_xl\pipeline_stable_diffusion_xl.py", line 363, in encode_prompt
text_inputs = tokenizer(
File "d:\anaconda3\envs\pytorch2\lib\site-packages\transformers\tokenization_utils_base.py", line 2803, in call
encodings = self._call_one(text=text, text_pair=text_pair, **all_kwargs)
File "d:\anaconda3\envs\pytorch2\lib\site-packages\transformers\tokenization_utils_base.py", line 2889, in _call_one
return self.batch_encode_plus(
File "d:\anaconda3\envs\pytorch2\lib\site-packages\transformers\tokenization_utils_base.py", line 3080, in batch_encode_plus
return self._batch_encode_plus(
File "d:\anaconda3\envs\pytorch2\lib\site-packages\transformers\tokenization_utils.py", line 807, in _batch_encode_plus
batch_outputs = self._batch_prepare_for_model(
File "d:\anaconda3\envs\pytorch2\lib\site-packages\transformers\tokenization_utils.py", line 879, in _batch_prepare_for_model
batch_outputs = self.pad(
File "d:\anaconda3\envs\pytorch2\lib\site-packages\transformers\tokenization_utils_base.py", line 3287, in pad
outputs = self._pad(
File "d:\anaconda3\envs\pytorch2\lib\site-packages\transformers\tokenization_utils_base.py", line 3656, in _pad
encoded_inputs["attention_mask"] = encoded_inputs["attention_mask"] + [0] * difference
OverflowError: cannot fit 'int' into an index-sized integer
hi do you have any updates to this? I'm facing the same issue as well. I think it's an issue with fp16 variant. What is your model?
hi do you have any updates to this? I'm facing the same issue as well. I think it's an issue with fp16 variant. What is your model?
nope，i don't know what to do now. This is my test code:
from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained(
"./",
torch_dtype=torch.float16,
variant="fp16",
).to("cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt=prompt, num_inference_steps=50, guidance_scale=3).images[0]
What's your python version?
What's your python version?
Python 3.10.13
torch 2.1.2+cu121
i solved it, check if your encoder token limit is overflowing, and if so, you can manually set the token limit
i solved it, check if your encoder token limit is overflowing, and if so, you can manually set the token limit
could you plz share more details about which params should i debug and which config file should be used?
i am still confused, thanks a lot.
i solved it, check if your encoder token limit is overflowing, and if so, you can manually set the token limit
Can you share the resolution steps, even I am getting this error
Manually set the maximum length like
self.tokenizer.model_max_length = 77 #
sample['key'] = f'{i:05}'
prompt = self.prompts[i%self.num_prompts]
sample['text_ids'] = self.tokenizer(
prompt, padding='max_length', max_length=self.tokenizer.model_max_length,#
truncation=True, return_tensors='pt').input_ids[0]