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Chat template: save and load correctly for processors (#33462)
* fix * add tests * fix tests * Update tests/models/llava/test_processor_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * fix * fix tests * update tests --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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@ -502,9 +502,12 @@ class ProcessorMixin(PushToHubMixin):
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output_chat_template_file = os.path.join(save_directory, CHAT_TEMPLATE_NAME)
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processor_dict = self.to_dict()
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chat_template = processor_dict.pop("chat_template", None)
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if chat_template is not None:
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chat_template_json_string = json.dumps({"chat_template": chat_template}, indent=2, sort_keys=True) + "\n"
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# Save `chat_template` in its own file. We can't get it from `processor_dict` as we popped it in `to_dict`
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# to avoid serializing chat template in json config file. So let's get it from `self` directly
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if self.chat_template is not None:
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chat_template_json_string = (
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json.dumps({"chat_template": self.chat_template}, indent=2, sort_keys=True) + "\n"
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)
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with open(output_chat_template_file, "w", encoding="utf-8") as writer:
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writer.write(chat_template_json_string)
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logger.info(f"chat template saved in {output_chat_template_file}")
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@ -11,6 +11,7 @@
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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 json
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import shutil
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import tempfile
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import unittest
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@ -32,11 +33,11 @@ class LlavaProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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def setUp(self):
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self.tmpdirname = tempfile.mkdtemp()
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image_processor = CLIPImageProcessor(do_center_crop=False)
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tokenizer = LlamaTokenizerFast.from_pretrained("huggyllama/llama-7b")
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processor = LlavaProcessor(image_processor=image_processor, tokenizer=tokenizer)
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processor_kwargs = self.prepare_processor_dict()
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processor = LlavaProcessor(image_processor, tokenizer, **processor_kwargs)
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processor.save_pretrained(self.tmpdirname)
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def get_tokenizer(self, **kwargs):
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@ -48,6 +49,28 @@ class LlavaProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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def tearDown(self):
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shutil.rmtree(self.tmpdirname)
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def prepare_processor_dict(self):
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return {"chat_template": "dummy_template"}
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@unittest.skip(
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"Skip because the model has no processor kwargs except for chat template and"
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"chat template is saved as a separate file. Stop skipping this test when the processor"
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"has new kwargs saved in config file."
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)
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def test_processor_to_json_string(self):
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pass
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def test_chat_template_is_saved(self):
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processor_loaded = self.processor_class.from_pretrained(self.tmpdirname)
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processor_dict_loaded = json.loads(processor_loaded.to_json_string())
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# chat templates aren't serialized to json in processors
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self.assertFalse("chat_template" in processor_dict_loaded.keys())
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# they have to be saved as separate file and loaded back from that file
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# so we check if the same template is loaded
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processor_dict = self.prepare_processor_dict()
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self.assertTrue(processor_loaded.chat_template == processor_dict.get("chat_template", None))
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def test_can_load_various_tokenizers(self):
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for checkpoint in ["Intel/llava-gemma-2b", "llava-hf/llava-1.5-7b-hf"]:
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processor = LlavaProcessor.from_pretrained(checkpoint)
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@ -11,20 +11,65 @@
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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 json
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import tempfile
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import unittest
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import torch
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from transformers import AutoProcessor, LlamaTokenizerFast, LlavaNextProcessor
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from transformers.testing_utils import 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 AutoProcessor
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from transformers import CLIPImageProcessor
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@require_vision
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class LlavaProcessorTest(unittest.TestCase):
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class LlavaNextProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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processor_class = LlavaNextProcessor
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def setUp(self):
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self.tmpdirname = tempfile.mkdtemp()
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image_processor = CLIPImageProcessor()
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tokenizer = LlamaTokenizerFast.from_pretrained("huggyllama/llama-7b")
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processor_kwargs = self.prepare_processor_dict()
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processor = LlavaNextProcessor(image_processor, tokenizer, **processor_kwargs)
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processor.save_pretrained(self.tmpdirname)
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def get_tokenizer(self, **kwargs):
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return LlavaNextProcessor.from_pretrained(self.tmpdirname, **kwargs).tokenizer
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def get_image_processor(self, **kwargs):
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return LlavaNextProcessor.from_pretrained(self.tmpdirname, **kwargs).image_processor
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def prepare_processor_dict(self):
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return {"chat_template": "dummy_template"}
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@unittest.skip(
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"Skip because the model has no processor kwargs except for chat template and"
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"chat template is saved as a separate file. Stop skipping this test when the processor"
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"has new kwargs saved in config file."
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)
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def test_processor_to_json_string(self):
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pass
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# Copied from tests.models.llava.test_processor_llava.LlavaProcessorTest.test_chat_template_is_saved
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def test_chat_template_is_saved(self):
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processor_loaded = self.processor_class.from_pretrained(self.tmpdirname)
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processor_dict_loaded = json.loads(processor_loaded.to_json_string())
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# chat templates aren't serialized to json in processors
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self.assertFalse("chat_template" in processor_dict_loaded.keys())
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# they have to be saved as separate file and loaded back from that file
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# so we check if the same template is loaded
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processor_dict = self.prepare_processor_dict()
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self.assertTrue(processor_loaded.chat_template == processor_dict.get("chat_template", None))
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def test_chat_template(self):
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processor = AutoProcessor.from_pretrained("llava-hf/llava-v1.6-vicuna-7b-hf")
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expected_prompt = "USER: <image>\nWhat is shown in this image? ASSISTANT:"
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@ -11,6 +11,7 @@
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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 json
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import shutil
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import tempfile
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import unittest
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@ -40,9 +41,10 @@ class LlavaOnevisionProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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image_processor = LlavaOnevisionImageProcessor()
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video_processor = LlavaOnevisionVideoProcessor()
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tokenizer = Qwen2TokenizerFast.from_pretrained("Qwen/Qwen2-0.5B-Instruct")
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processor_kwargs = self.prepare_processor_dict()
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processor = LlavaOnevisionProcessor(
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video_processor=video_processor, image_processor=image_processor, tokenizer=tokenizer
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video_processor=video_processor, image_processor=image_processor, tokenizer=tokenizer, **processor_kwargs
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)
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processor.save_pretrained(self.tmpdirname)
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@ -52,9 +54,32 @@ class LlavaOnevisionProcessorTest(ProcessorTesterMixin, unittest.TestCase):
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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 get_Video_processor(self, **kwargs):
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def get_video_processor(self, **kwargs):
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return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).video_processor
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def prepare_processor_dict(self):
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return {"chat_template": "dummy_template"}
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@unittest.skip(
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"Skip because the model has no processor kwargs except for chat template and"
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"chat template is saved as a separate file. Stop skipping this test when the processor"
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"has new kwargs saved in config file."
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)
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def test_processor_to_json_string(self):
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pass
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# Copied from tests.models.llava.test_processor_llava.LlavaProcessorTest.test_chat_template_is_saved
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def test_chat_template_is_saved(self):
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processor_loaded = self.processor_class.from_pretrained(self.tmpdirname)
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processor_dict_loaded = json.loads(processor_loaded.to_json_string())
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# chat templates aren't serialized to json in processors
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self.assertFalse("chat_template" in processor_dict_loaded.keys())
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# they have to be saved as separate file and loaded back from that file
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# so we check if the same template is loaded
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processor_dict = self.prepare_processor_dict()
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self.assertTrue(processor_loaded.chat_template == processor_dict.get("chat_template", None))
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def tearDown(self):
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shutil.rmtree(self.tmpdirname)
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