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compel = Compel(tokenizer=[pipeline.tokenizer, pipeline.tokenizer_2] ,
text_encoder=[pipeline.text_encoder, pipeline.text_encoder_2],
returned_embeddings_type=ReturnedEmbeddingsType.PENULTIMATE_HIDDEN_STATES_NON_NORMALIZED,
requires_pooled=[False, True],
truncate_long_prompts=False)
prompt_converted = "a cat playing with a ball++ in the forest"
negative_prompt_converted = "a long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long long negative prompt"
conditioning, pooled = compel([prompt_converted, negative_prompt_converted])
print(conditioning.shape, pooled.shape)
image = pipeline(prompt_embeds=conditioning[0:1], pooled_prompt_embeds=pooled[0:1],
negative_prompt_embeds=conditioning[1:2], negative_pooled_prompt_embeds=pooled[1:2],
num_inference_steps=24, width=768, height=768).images[0]
image
then it return
Traceback (most recent call last):
File "20231011_ylj.py", line 259, in <module>
conditioning, pooled = compel([prompt_converted, negative_prompt_converted])
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/compel.py", line 135, in __call__
output = self.build_conditioning_tensor(text_input)
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/compel.py", line 112, in build_conditioning_tensor
conditioning, _ = self.build_conditioning_tensor_for_conjunction(conjunction)
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/compel.py", line 186, in build_conditioning_tensor_for_conjunction
this_conditioning, this_options = self.build_conditioning_tensor_for_prompt_object(p)
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/compel.py", line 218, in build_conditioning_tensor_for_prompt_object
return self._get_conditioning_for_flattened_prompt(prompt), {}
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/compel.py", line 282, in _get_conditioning_for_flattened_prompt
return self.conditioning_provider.get_embeddings_for_weighted_prompt_fragments(
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/embeddings_provider.py", line 524, in get_embeddings_for_weighted_prompt_fragments
outputs = [provider.get_embeddings_for_weighted_prompt_fragments(text_batch, fragment_weights_batch, should_return_tokens=should_return_tokens, device=device) for provider in self.embedding_providers]
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/embeddings_provider.py", line 524, in <listcomp>
outputs = [provider.get_embeddings_for_weighted_prompt_fragments(text_batch, fragment_weights_batch, should_return_tokens=should_return_tokens, device=device) for provider in self.embedding_providers]
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/embeddings_provider.py", line 119, in get_embeddings_for_weighted_prompt_fragments
tokens, per_token_weights, mask = self.get_token_ids_and_expand_weights(fragments, weights, device=device)
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/embeddings_provider.py", line 280, in get_token_ids_and_expand_weights
return self._chunk_and_pad_token_ids(all_token_ids, all_token_weights, device=device)
File "/root/miniconda3/envs/Diffusion/lib/python3.8/site-packages/compel/embeddings_provider.py", line 307, in _chunk_and_pad_token_ids
chunk_token_ids += [self.tokenizer.pad_token_id] * pad_length
OverflowError: cannot fit 'int' into an index-sized integer
I don't know how to fix it
The text was updated successfully, but these errors were encountered:
hello,when I try this code
then it return
I don't know how to fix it
The text was updated successfully, but these errors were encountered: