Clean up duplicate lines in encode_prompt (#4369)

* Clean up duplicate line

* Clean up duplicate lines

* Clean up duplicate line

src/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl.py

@@ -305,7 +305,6 @@ class StableDiffusionXLControlNetPipeline(DiffusionPipeline, TextualInversionLoa
 
                 text_input_ids = text_inputs.input_ids
                 untruncated_ids = tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
-                untruncated_ids = tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
 
                 if untruncated_ids.shape[-1] >= text_input_ids.shape[-1] and not torch.equal(
                     text_input_ids, untruncated_ids

src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl.py

@@ -310,7 +310,6 @@ class StableDiffusionXLPipeline(DiffusionPipeline, FromSingleFileMixin, LoraLoad
 
                 text_input_ids = text_inputs.input_ids
                 untruncated_ids = tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
-                untruncated_ids = tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
 
                 if untruncated_ids.shape[-1] >= text_input_ids.shape[-1] and not torch.equal(
                     text_input_ids, untruncated_ids

src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_img2img.py

@@ -317,7 +317,6 @@ class StableDiffusionXLImg2ImgPipeline(DiffusionPipeline, FromSingleFileMixin, L
 
                 text_input_ids = text_inputs.input_ids
                 untruncated_ids = tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
-                untruncated_ids = tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
 
                 if untruncated_ids.shape[-1] >= text_input_ids.shape[-1] and not torch.equal(
                     text_input_ids, untruncated_ids

src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_inpaint.py

@@ -458,7 +458,6 @@ class StableDiffusionXLInpaintPipeline(
 
                 text_input_ids = text_inputs.input_ids
                 untruncated_ids = tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
-                untruncated_ids = tokenizer(prompt, padding="longest", return_tensors="pt").input_ids
 
                 if untruncated_ids.shape[-1] >= text_input_ids.shape[-1] and not torch.equal(
                     text_input_ids, untruncated_ids