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* upadte * Update src/transformers/models/paligemma/processing_paligemma.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * update docs * better example in tests * support image tokens * read token * Update tests/models/paligemma/test_processing_paligemma.py Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com> * nit: naming * Update docs/source/en/model_doc/paligemma.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * conflicts after rebasing --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
85 lines
3.7 KiB
Python
85 lines
3.7 KiB
Python
# Copyright 2024 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import shutil
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import tempfile
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import unittest
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from transformers import AutoProcessor, GemmaTokenizerFast, PaliGemmaProcessor
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from transformers.testing_utils import require_read_token, require_vision
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from transformers.utils import is_vision_available
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from ...test_processing_common import ProcessorTesterMixin
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if is_vision_available():
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from transformers import SiglipImageProcessor
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@require_vision
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@require_read_token
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class PaliGemmaProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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processor_class = PaliGemmaProcessor
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def setUp(self):
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self.tmpdirname = tempfile.mkdtemp()
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image_processor = SiglipImageProcessor(do_center_crop=False)
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tokenizer = GemmaTokenizerFast.from_pretrained("google/gemma-7b")
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image_processor.image_seq_length = 32
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processor = PaliGemmaProcessor(image_processor=image_processor, tokenizer=tokenizer)
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processor.save_pretrained(self.tmpdirname)
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def get_tokenizer(self, **kwargs):
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return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).tokenizer
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def get_image_processor(self, **kwargs):
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return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).image_processor
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def tearDown(self):
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shutil.rmtree(self.tmpdirname)
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def test_text_with_image_tokens(self):
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image_processor = self.get_component("image_processor")
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tokenizer = self.get_component("tokenizer")
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processor = self.processor_class(tokenizer=tokenizer, image_processor=image_processor)
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text_multi_images = "<image><image><bos>Dummy text!"
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text_single_image = "<image><bos>Dummy text!"
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text_no_image = "Dummy text!"
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image = self.prepare_image_inputs()[0]
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out_noimage = processor(text=text_no_image, images=image, return_tensors="np")
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out_singlimage = processor(text=text_single_image, images=image, return_tensors="np")
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for k in out_noimage:
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self.assertTrue(out_noimage[k].tolist() == out_singlimage[k].tolist())
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out_multiimages = processor(text=text_multi_images, images=[image, image], return_tensors="np")
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out_noimage = processor(text=text_no_image, images=[[image, image]], return_tensors="np")
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# We can't be sure what is users intention, whether user want "one text + two images" or user forgot to add the second text
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with self.assertRaises(ValueError):
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out_noimage = processor(text=text_no_image, images=[image, image], return_tensors="np")
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for k in out_noimage:
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self.assertTrue(out_noimage[k].tolist() == out_multiimages[k].tolist())
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text_batched = ["Dummy text!", "Dummy text!"]
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text_batched_with_image = ["<image><bos>Dummy text!", "<image><bos>Dummy text!"]
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out_images = processor(text=text_batched_with_image, images=[image, image], return_tensors="np")
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out_noimage_nested = processor(text=text_batched, images=[[image], [image]], return_tensors="np")
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out_noimage = processor(text=text_batched, images=[image, image], return_tensors="np")
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for k in out_noimage:
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self.assertTrue(out_noimage[k].tolist() == out_images[k].tolist() == out_noimage_nested[k].tolist())
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