Upgrade to Transformers v4.45

examples/audio-classification/run_audio_classification.py

@@ -46,7 +46,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.14.0", "To fix: pip install -r examples/pytorch/audio-classification/requirements.txt")

examples/contrastive-image-text/run_bridgetower.py

@@ -56,7 +56,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/contrastive-image-text/requirements.txt")

examples/contrastive-image-text/run_clip.py

@@ -61,7 +61,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/contrastive-image-text/requirements.txt")

examples/image-classification/run_image_classification.py

@@ -63,7 +63,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=2.14.0", "To fix: pip install -r examples/pytorch/image-classification/requirements.txt")

examples/language-modeling/run_clm.py

@@ -62,7 +62,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=2.14.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")

examples/language-modeling/run_mlm.py

@@ -61,7 +61,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=2.14.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")

examples/language-modeling/run_multitask_prompt_tuning.py

@@ -60,7 +60,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risk.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")

examples/language-modeling/run_prompt_tuning_clm.py

@@ -62,7 +62,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/language-modeling/requirements.txt")

examples/question-answering/run_qa.py

@@ -60,7 +60,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")

examples/question-answering/run_seq2seq_qa.py

@@ -56,7 +56,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/question-answering/requirements.txt")

examples/speech-recognition/run_speech_recognition_ctc.py

@@ -59,7 +59,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.18.0", "To fix: pip install -r examples/pytorch/speech-recognition/requirements.txt")

examples/speech-recognition/run_speech_recognition_seq2seq.py

@@ -55,7 +55,7 @@ def check_optimum_habana_min_version(*a, **b):
 
 
 # Will error if the minimal version of Transformers is not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.18.0", "To fix: pip install -r examples/pytorch/speech-recognition/requirements.txt")
@@ -580,7 +580,8 @@ def compute_metrics(pred):
             # save feature extractor, tokenizer and config
             feature_extractor.save_pretrained(training_args.output_dir)
             tokenizer.save_pretrained(training_args.output_dir)
-            config.save_pretrained(training_args.output_dir)
+            # TODO: uncomment the line below when this is fixed in Transformers
+            # config.save_pretrained(training_args.output_dir)
 
     processor = AutoProcessor.from_pretrained(training_args.output_dir)
 

examples/stable-diffusion/unconditional_image_generation.py

@@ -19,7 +19,7 @@ def check_optimum_habana_min_version(*a, **b):
         return ()
 
 
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 # Setup logging

examples/summarization/run_summarization.py

@@ -65,7 +65,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/summarization/requirements.txt")

examples/text-classification/run_glue.py

@@ -57,7 +57,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/text-classification/requirements.txt")

examples/translation/run_translation.py

@@ -62,7 +62,7 @@ def check_optimum_habana_min_version(*a, **b):
 logger = logging.getLogger(__name__)
 
 # Will error if the minimal version of Transformers and Optimum Habana are not installed. Remove at your own risks.
-check_min_version("4.43.0")
+check_min_version("4.45.0")
 check_optimum_habana_min_version("1.14.0.dev0")
 
 require_version("datasets>=1.8.0", "To fix: pip install -r examples/pytorch/translation/requirements.txt")

optimum/habana/transformers/generation/__init__.py

@@ -3,7 +3,6 @@
 from .stopping_criteria import (
     gaudi_EosTokenCriteria_call,
     gaudi_MaxLengthCriteria_call,
-    gaudi_MaxNewTokensCriteria_call,
     gaudi_MaxTimeCriteria_call,
     gaudi_StoppingCriteriaList_call,
 )

optimum/habana/transformers/generation/candidate_generator.py

@@ -8,8 +8,8 @@
 
 
 if TYPE_CHECKING:
+    from transformers.generation.logits_process import LogitsProcessorList
     from transformers.modeling_utils import PreTrainedModel
-    from transfromers.generation.logits_process import LogitsProcessorList
 
     from .configuration_utils import GaudiGenerationConfig
 

optimum/habana/transformers/generation/stopping_criteria.py

@@ -52,18 +52,6 @@ def gaudi_MaxLengthCriteria_call(
         return create_return_const_tensor(input_ids, is_done)
 
 
-def gaudi_MaxNewTokensCriteria_call(
-    self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs
-) -> Union[torch.BoolTensor, bool]:
-    token_idx = kwargs.get("token_idx", None)
-    if token_idx is not None:
-        assert not kwargs["needs_tensor_output"]
-        return token_idx >= self.max_length
-    else:
-        is_done = input_ids.shape[-1] >= self.max_length
-        return create_return_const_tensor(input_ids, is_done)
-
-
 def gaudi_MaxTimeCriteria_call(
     self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs
 ) -> Union[torch.BoolTensor, bool]: