Change potential `inputs_embeds` padding `logger.warning` to `logger.warning_once` (#31411)

change embeddings padding warning to warning_once

src/transformers/models/biogpt/modeling_biogpt.py

@@ -888,7 +888,7 @@ class BioGptForSequenceClassification(BioGptPreTrainedModel):
                 sequence_length = (torch.ne(input_ids, self.config.pad_token_id).sum(-1) - 1).to(logits.device)
             else:
                 sequence_length = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/bloom/modeling_bloom.py

@@ -1007,7 +1007,7 @@ class BloomForSequenceClassification(BloomPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/ctrl/modeling_ctrl.py

@@ -797,7 +797,7 @@ class CTRLForSequenceClassification(CTRLPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/ctrl/modeling_tf_ctrl.py

@@ -884,7 +884,7 @@ class TFCTRLForSequenceClassification(TFCTRLPreTrainedModel, TFSequenceClassific
                 in_logits = tf.gather(logits, sequence_lengths, batch_dims=1, axis=1)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/deprecated/transfo_xl/modeling_tf_transfo_xl.py

@@ -1084,7 +1084,7 @@ class TFTransfoXLForSequenceClassification(TFTransfoXLPreTrainedModel, TFSequenc
                 in_logits = tf.gather(logits, sequence_lengths, batch_dims=1, axis=1)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/deprecated/transfo_xl/modeling_transfo_xl.py

@@ -1251,7 +1251,7 @@ class TransfoXLForSequenceClassification(TransfoXLPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/falcon/modeling_falcon.py

@@ -1422,7 +1422,7 @@ class FalconForSequenceClassification(FalconPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/gpt2/modeling_gpt2.py

@@ -1693,7 +1693,7 @@ class GPT2ForSequenceClassification(GPT2PreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/gpt2/modeling_tf_gpt2.py

@@ -1194,7 +1194,7 @@ class TFGPT2ForSequenceClassification(TFGPT2PreTrainedModel, TFSequenceClassific
                 in_logits = tf.gather(logits, sequence_lengths, batch_dims=1, axis=1)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/gpt_bigcode/modeling_gpt_bigcode.py

@@ -1397,7 +1397,7 @@ class GPTBigCodeForSequenceClassification(GPTBigCodePreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/gpt_neo/modeling_gpt_neo.py

@@ -1116,7 +1116,7 @@ class GPTNeoForSequenceClassification(GPTNeoPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/gpt_neox/modeling_gpt_neox.py

@@ -1206,7 +1206,7 @@ class GPTNeoXForSequenceClassification(GPTNeoXPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/gptj/modeling_gptj.py

@@ -1278,7 +1278,7 @@ class GPTJForSequenceClassification(GPTJPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/gptj/modeling_tf_gptj.py

@@ -958,7 +958,7 @@ class TFGPTJForSequenceClassification(TFGPTJPreTrainedModel, TFSequenceClassific
                 in_logits = tf.gather(logits, sequence_lengths, batch_dims=1, axis=1)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/mistral/modeling_tf_mistral.py

@@ -1015,7 +1015,7 @@ class TFMistralForSequenceClassification(TFMistralPreTrainedModel, TFSequenceCla
                 in_logits = tf.gather(logits, sequence_lengths, batch_dims=1, axis=1)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/mpt/modeling_mpt.py

@@ -726,7 +726,7 @@ class MptForSequenceClassification(MptPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/openai/modeling_openai.py

@@ -814,7 +814,7 @@ class OpenAIGPTForSequenceClassification(OpenAIGPTPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/openai/modeling_tf_openai.py

@@ -892,7 +892,7 @@ class TFOpenAIGPTForSequenceClassification(TFOpenAIGPTPreTrainedModel, TFSequenc
                 in_logits = tf.gather(logits, sequence_lengths, batch_dims=1, axis=1)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )

src/transformers/models/opt/modeling_opt.py

@@ -1275,7 +1275,7 @@ class OPTForSequenceClassification(OPTPreTrainedModel):
                 sequence_lengths = sequence_lengths.to(logits.device)
             else:
                 sequence_lengths = -1
-                logger.warning(
+                logger.warning_once(
                     f"{self.__class__.__name__} will not detect padding tokens in `inputs_embeds`. Results may be "
                     "unexpected if using padding tokens in conjunction with `inputs_embeds.`"
                 )