Check model inputs - hidden states

src/transformers/models/aimv2/modeling_aimv2.py

@@ -444,7 +444,7 @@ def get_input_embeddings(self) -> nn.Module:
         return self.embeddings.patch_embed
 
     @deprecate_kwarg("attention_mask", version="v4.58.0")
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,
@@ -520,7 +520,7 @@ def get_input_embeddings(self) -> nn.Module:
     def set_input_embeddings(self, value):
         self.embeddings.token_embedding = value
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,

src/transformers/models/aimv2/modular_aimv2.py

@@ -488,7 +488,7 @@ def get_input_embeddings(self) -> nn.Module:
         return self.embeddings.patch_embed
 
     @deprecate_kwarg("attention_mask", version="v4.58.0")
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,
@@ -564,7 +564,7 @@ def get_input_embeddings(self) -> nn.Module:
     def set_input_embeddings(self, value):
         self.embeddings.token_embedding = value
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,

src/transformers/models/apertus/modeling_apertus.py

@@ -339,7 +339,7 @@ def __init__(self, config: ApertusConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/arcee/modeling_arcee.py

@@ -344,7 +344,7 @@ def __init__(self, config: ArceeConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/aria/modeling_aria.py

@@ -721,7 +721,7 @@ def __init__(self, config: AriaTextConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/audio_spectrogram_transformer/modeling_audio_spectrogram_transformer.py

@@ -366,7 +366,7 @@ class PreTrainedModel
         for layer, heads in heads_to_prune.items():
             self.encoder.layer[layer].attention.prune_heads(heads)
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/aya_vision/modeling_aya_vision.py

@@ -263,7 +263,7 @@ def get_placeholder_mask(
             )
         return special_image_mask
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/aya_vision/modular_aya_vision.py

@@ -162,7 +162,7 @@ def get_image_features(
         image_features = self.multi_modal_projector(selected_image_feature)
         return image_features
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/bitnet/modeling_bitnet.py

@@ -343,7 +343,7 @@ def __init__(self, config: BitNetConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/blip/modeling_blip.py

@@ -508,7 +508,7 @@ def __init__(self, config: BlipVisionConfig):
 
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,

src/transformers/models/blip_2/modeling_blip_2.py

@@ -495,7 +495,7 @@ def __init__(self, config: Blip2VisionConfig):
 
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,
@@ -1007,7 +1007,7 @@ def get_extended_attention_mask(
         extended_attention_mask = (1.0 - extended_attention_mask) * -10000.0
         return extended_attention_mask
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/cohere/modeling_cohere.py

@@ -376,7 +376,7 @@ def __init__(self, config: CohereConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/cohere2/modeling_cohere2.py

@@ -351,7 +351,7 @@ def __init__(self, config: Cohere2Config):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/cohere2_vision/modeling_cohere2_vision.py

@@ -213,7 +213,7 @@ def get_placeholder_mask(
             )
         return special_image_mask
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,
@@ -306,7 +306,7 @@ def vision_tower(self):
     def multi_modal_projector(self):
         return self.model.multi_modal_projector
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/cohere2_vision/modular_cohere2_vision.py

@@ -107,7 +107,7 @@ def get_image_features(self, pixel_values: torch.FloatTensor):
         image_features = self.multi_modal_projector(selected_image_feature)
         return image_features
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,
@@ -160,7 +160,7 @@ class Cohere2VisionForConditionalGeneration(AyaVisionForConditionalGeneration):
     def get_image_features(self, pixel_values: torch.FloatTensor):
         return self.model.get_image_features(pixel_values=pixel_values)
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/csm/modeling_csm.py

@@ -409,7 +409,7 @@ def __init__(self, config):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,
@@ -662,7 +662,7 @@ def __init__(self, config):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/csm/modular_csm.py

@@ -156,7 +156,7 @@ def __init__(self, config):
         self.embed_tokens = nn.Embedding((config.num_codebooks * config.vocab_size), config.backbone_hidden_size)
         self.inputs_embeds_projector = nn.Linear(config.backbone_hidden_size, config.hidden_size, bias=False)
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,
@@ -395,7 +395,7 @@ def __init__(self, config):
         super().__init__(config)
         self.embed_tokens = CsmBackboneModelEmbeddings(config)
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(self, **super_kwargs):
         r"""

src/transformers/models/deepseek_v2/modeling_deepseek_v2.py

@@ -491,7 +491,7 @@ def __init__(self, config: DeepseekV2Config):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/deepseek_v3/modeling_deepseek_v3.py

@@ -539,7 +539,7 @@ def __init__(self, config: DeepseekV3Config):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/deit/modeling_deit.py

@@ -441,7 +441,7 @@ class PreTrainedModel
         for layer, heads in heads_to_prune.items():
             self.encoder.layer[layer].attention.prune_heads(heads)
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,

src/transformers/models/diffllama/modeling_diffllama.py

@@ -608,7 +608,7 @@ def __init__(self, config: DiffLlamaConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/dinov2/modeling_dinov2.py

@@ -501,7 +501,7 @@ class PreTrainedModel
         for layer, heads in heads_to_prune.items():
             self.encoder.layer[layer].attention.prune_heads(heads)
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,
@@ -624,7 +624,7 @@ def __init__(self, config):
     def get_input_embeddings(self) -> Dinov2PatchEmbeddings:
         return self.embeddings.patch_embeddings
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self, pixel_values: torch.Tensor, output_hidden_states: Optional[bool] = None, **kwargs

src/transformers/models/dinov2_with_registers/modeling_dinov2_with_registers.py

@@ -518,7 +518,7 @@ class PreTrainedModel
         for layer, heads in heads_to_prune.items():
             self.encoder.layer[layer].attention.prune_heads(heads)
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,
@@ -644,7 +644,7 @@ def __init__(self, config):
     def get_input_embeddings(self) -> Dinov2WithRegistersPatchEmbeddings:
         return self.embeddings.patch_embeddings
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/dinov3_vit/modeling_dinov3_vit.py

@@ -499,7 +499,7 @@ def __init__(self, config: DINOv3ViTConfig):
     def get_input_embeddings(self):
         return self.embeddings.patch_embeddings
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,

src/transformers/models/dinov3_vit/modular_dinov3_vit.py

@@ -389,7 +389,7 @@ def __init__(self, config: DINOv3ViTConfig):
     def get_input_embeddings(self):
         return self.embeddings.patch_embeddings
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,

src/transformers/models/doge/modeling_doge.py

@@ -530,7 +530,7 @@ def __init__(self, config: DogeConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/dots1/modeling_dots1.py

@@ -454,7 +454,7 @@ def __init__(self, config: Dots1Config):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/dpt/modeling_dpt.py

@@ -808,7 +808,7 @@ class PreTrainedModel
         for layer, heads in heads_to_prune.items():
             self.encoder.layer[layer].attention.prune_heads(heads)
 
-    @check_model_inputs
+    @check_model_inputs(post_ln_hiddens=False)
     @auto_docstring
     def forward(
         self,

src/transformers/models/efficientloftr/modeling_efficientloftr.py

@@ -680,7 +680,7 @@ def __init__(self, config: EfficientLoFTRConfig):
 
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/emu3/modeling_emu3.py

@@ -1166,7 +1166,7 @@ def __init__(self, config: Emu3Config):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/eomt/modeling_eomt.py

@@ -1087,7 +1087,7 @@ def get_loss_dict(
     def get_loss(self, loss_dict: dict[str, Tensor]) -> Tensor:
         return sum(loss_dict.values())
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/eomt/modular_eomt.py

@@ -492,7 +492,7 @@ def _disable_attention_mask(attn_mask, prob, num_query_tokens, encoder_start_tok
 
         return attn_mask
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/ernie4_5/modeling_ernie4_5.py

@@ -342,7 +342,7 @@ def __init__(self, config: Ernie4_5Config):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/ernie4_5_moe/modeling_ernie4_5_moe.py

@@ -510,7 +510,7 @@ def __init__(self, config: Ernie4_5_MoeConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,

src/transformers/models/ernie4_5_moe/modular_ernie4_5_moe.py

@@ -248,7 +248,7 @@ def __init__(self, config: Ernie4_5_MoeConfig):
         # Initialize weights and apply final processing
         self.post_init()
 
-    @check_model_inputs
+    @check_model_inputs()
     @auto_docstring
     def forward(
         self,