Manually generate generate_ids using BlipForConditionalGeneration
from transformers import BlipForConditionalGeneration,AutoProcessor,AutoTokenizerfrom PIL import Imageimport requestsimport torchprocessor= AutoProcessor.from_pretrained(“Salesforce/blip-image-captioning-base”)model= BlipForConditionalGeneration.from_pretrained(“Salesforce/blip-image-captioning-base”)tokenizer = AutoTokenizer.from_pretrained(“Salesforce/blip-image-captioning-base”)url = “http://images.cocodataset.org/val2017/000000039769.jpg”image = Image.open(requests.get(url, stream=True).raw)text = “A picture of”decoder_input_ids = [model.decoder_input_ids]print(decoder_input_ids)inputs.input_ids = decoder_input_ids=torch.tensor([decoder_input_ids])predicted_ids =for i in range(20):outputs = model(**inputs)logits = outputs.logits[:,i,:]print(outputs.logits.shape)predicted_id = logits.argmax(-1)predicted_ids.append(predicted_id.item())print(tokenizer.decode([predicted_id.squeeze()]))add predicted id to decoder_input_idsinputs.input_ids = torch.cat([inputs.input_ids, predicted_id.unsqueeze(0)], dim=1)for this code for every image i found same logits shape [1, 5, 30524] . and also every iteration the logits are remain same. no change in logtis for changing the inputs.input_ids. why i face this error? and how to solve this?