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pipeline.py

@@ -121,12 +121,13 @@ class StableDiffusionT5Pipeline(StableDiffusionPipeline):
         prompt,
         negative_prompt, #can be None
         device,
+        padding=None,
     ):
         def _tok(text):
             out = self.tokenizer(
                 text,
                 return_tensors="pt",
-                padding="max_length",
+                padding=padding,
                 max_length=self.tokenizer.model_max_length,
                 truncation=True,
             )
@@ -149,13 +150,14 @@ class StableDiffusionT5Pipeline(StableDiffusionPipeline):
         num_images_per_prompt,
         do_classifier_free_guidance,
         negative_prompt=None,
+        padding=None,
         **kwargs,
     ):
 
 
         scaling_factor = self.t5_projection.config.scaling_factor
 
-        pos_hidden, neg_hidden = self.encode_prompt_t5(prompt, negative_prompt, device)
+        pos_hidden, neg_hidden = self.encode_prompt_t5(prompt, negative_prompt, device, padding=padding)
 
         pos_embeds = self.t5_projection.text_projection(pos_hidden)
         pos_embeds = pos_embeds * scaling_factor