Fix the issue of blip model returning loss even when the label is not provided. (#21811)
* Fix the issue of blip model returning loss even when the label is not provoided * Fix ruff failure * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks
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@@ -990,7 +990,7 @@ class BlipForConditionalGeneration(BlipPreTrainedModel):
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>>> outputs = model(**inputs)
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```"""
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batch_size = pixel_values.shape[0]
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return_dict = return_dict if return_dict is not None else self.config.use_return_dict
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vision_outputs = self.vision_model(
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@@ -1002,12 +1002,6 @@ class BlipForConditionalGeneration(BlipPreTrainedModel):
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image_embeds = vision_outputs[0]
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if input_ids is None:
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input_ids = torch.LongTensor([[self.decoder_input_ids] * batch_size]).to(image_embeds.device)
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if labels is None:
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labels = input_ids.masked_fill(input_ids == self.decoder_pad_token_id, -100)
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outputs = self.text_decoder(
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input_ids=input_ids,
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attention_mask=attention_mask,
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@@ -24,7 +24,7 @@ import numpy as np
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import requests
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from transformers import BlipConfig, BlipTextConfig, BlipVisionConfig
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from transformers.testing_utils import require_torch, require_vision, slow, torch_device
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from transformers.testing_utils import require_torch, require_torch_gpu, require_vision, slow, torch_device
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from transformers.utils import is_torch_available, is_vision_available
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from ...test_configuration_common import ConfigTester
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@@ -1111,6 +1111,7 @@ class BlipModelIntegrationTest(unittest.TestCase):
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[30522, 1037, 3861, 1997, 1037, 2450, 3564, 2006, 1996, 3509, 2007, 2014, 3899, 102],
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)
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@require_torch_gpu
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def test_inference_image_captioning_fp16(self):
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model = BlipForConditionalGeneration.from_pretrained(
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"Salesforce/blip-image-captioning-base", torch_dtype=torch.float16
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