remove last_hidden_state for task-specific model

src/transformers/models/rt_detr/modeling_rt_detr.py

@@ -278,8 +278,6 @@ class RTDetrObjectDetectionOutput(ModelOutput):
             Optional, only returned when auxiliary losses are activated (i.e. `config.auxiliary_loss` is set to `True`)
             and labels are provided. It is a list of dictionaries containing the two above keys (`logits` and
             `pred_boxes`) for each decoder layer.
-        last_hidden_state (`torch.FloatTensor` of shape `(batch_size, num_queries, hidden_size)`):
-            Sequence of hidden-states at the output of the last layer of the decoder of the model.
         intermediate_hidden_states (`torch.FloatTensor` of shape `(batch_size, config.decoder_layers, num_queries, hidden_size)`):
             Stacked intermediate hidden states (output of each layer of the decoder).
         intermediate_logits (`torch.FloatTensor` of shape `(batch_size, config.decoder_layers, num_queries, config.num_labels)`):
@@ -329,7 +327,6 @@ class RTDetrObjectDetectionOutput(ModelOutput):
     logits: torch.FloatTensor = None
     pred_boxes: torch.FloatTensor = None
     auxiliary_outputs: Optional[List[Dict]] = None
-    last_hidden_state: torch.FloatTensor = None
     intermediate_hidden_states: torch.FloatTensor = None
     intermediate_logits: torch.FloatTensor = None
     intermediate_reference_points: torch.FloatTensor = None
@@ -2659,7 +2656,6 @@ def forward(
             logits=logits,
             pred_boxes=pred_boxes,
             auxiliary_outputs=auxiliary_outputs,
-            last_hidden_state=outputs.last_hidden_state,
             intermediate_hidden_states=outputs.intermediate_hidden_states,
             intermediate_logits=outputs.intermediate_logits,
             intermediate_reference_points=outputs.intermediate_reference_points,