From b8aee2e918d7ba2d5e9e80162ae26b4806873307 Mon Sep 17 00:00:00 2001
From: David <37246112+conditionedstimulus@users.noreply.github.com>
Date: Wed, 15 May 2024 12:19:43 +0200
Subject: [PATCH] Remove unused module DETR based models (#30823)

* removing heads for classification from DETR models.

* quality fix
---
 .../modeling_conditional_detr.py              | 19 -------------------
 .../modeling_deformable_detr.py               | 19 -------------------
 src/transformers/models/deta/modeling_deta.py | 19 -------------------
 src/transformers/models/detr/modeling_detr.py | 18 ------------------
 .../modeling_table_transformer.py             | 19 -------------------
 5 files changed, 94 deletions(-)

diff --git a/src/transformers/models/conditional_detr/modeling_conditional_detr.py b/src/transformers/models/conditional_detr/modeling_conditional_detr.py
index 2eb0ea885cfa0c..eec95205244f1a 100644
--- a/src/transformers/models/conditional_detr/modeling_conditional_detr.py
+++ b/src/transformers/models/conditional_detr/modeling_conditional_detr.py
@@ -1091,25 +1091,6 @@ def forward(
         return outputs
 
 
-# Copied from transformers.models.detr.modeling_detr.DetrClassificationHead with Detr->ConditionalDetr
-class ConditionalDetrClassificationHead(nn.Module):
-    """Head for sentence-level classification tasks."""
-
-    def __init__(self, input_dim: int, inner_dim: int, num_classes: int, pooler_dropout: float):
-        super().__init__()
-        self.dense = nn.Linear(input_dim, inner_dim)
-        self.dropout = nn.Dropout(p=pooler_dropout)
-        self.out_proj = nn.Linear(inner_dim, num_classes)
-
-    def forward(self, hidden_states: torch.Tensor):
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.dense(hidden_states)
-        hidden_states = torch.tanh(hidden_states)
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.out_proj(hidden_states)
-        return hidden_states
-
-
 # Copied from transformers.models.detr.modeling_detr.DetrMLPPredictionHead with DetrMLPPredictionHead->MLP
 class MLP(nn.Module):
     """
diff --git a/src/transformers/models/deformable_detr/modeling_deformable_detr.py b/src/transformers/models/deformable_detr/modeling_deformable_detr.py
index 61f0f011617a7d..bab552da35d424 100755
--- a/src/transformers/models/deformable_detr/modeling_deformable_detr.py
+++ b/src/transformers/models/deformable_detr/modeling_deformable_detr.py
@@ -1066,25 +1066,6 @@ def forward(
         return outputs
 
 
-# Copied from transformers.models.detr.modeling_detr.DetrClassificationHead
-class DeformableDetrClassificationHead(nn.Module):
-    """Head for sentence-level classification tasks."""
-
-    def __init__(self, input_dim: int, inner_dim: int, num_classes: int, pooler_dropout: float):
-        super().__init__()
-        self.dense = nn.Linear(input_dim, inner_dim)
-        self.dropout = nn.Dropout(p=pooler_dropout)
-        self.out_proj = nn.Linear(inner_dim, num_classes)
-
-    def forward(self, hidden_states: torch.Tensor):
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.dense(hidden_states)
-        hidden_states = torch.tanh(hidden_states)
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.out_proj(hidden_states)
-        return hidden_states
-
-
 class DeformableDetrPreTrainedModel(PreTrainedModel):
     config_class = DeformableDetrConfig
     base_model_prefix = "model"
diff --git a/src/transformers/models/deta/modeling_deta.py b/src/transformers/models/deta/modeling_deta.py
index 86ced383a0cc34..bd2faad271c661 100644
--- a/src/transformers/models/deta/modeling_deta.py
+++ b/src/transformers/models/deta/modeling_deta.py
@@ -1032,25 +1032,6 @@ def forward(
         return outputs
 
 
-# Copied from transformers.models.detr.modeling_detr.DetrClassificationHead
-class DetaClassificationHead(nn.Module):
-    """Head for sentence-level classification tasks."""
-
-    def __init__(self, input_dim: int, inner_dim: int, num_classes: int, pooler_dropout: float):
-        super().__init__()
-        self.dense = nn.Linear(input_dim, inner_dim)
-        self.dropout = nn.Dropout(p=pooler_dropout)
-        self.out_proj = nn.Linear(inner_dim, num_classes)
-
-    def forward(self, hidden_states: torch.Tensor):
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.dense(hidden_states)
-        hidden_states = torch.tanh(hidden_states)
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.out_proj(hidden_states)
-        return hidden_states
-
-
 class DetaPreTrainedModel(PreTrainedModel):
     config_class = DetaConfig
     base_model_prefix = "model"
diff --git a/src/transformers/models/detr/modeling_detr.py b/src/transformers/models/detr/modeling_detr.py
index ea8735da9f3d45..3ac3c13550af32 100644
--- a/src/transformers/models/detr/modeling_detr.py
+++ b/src/transformers/models/detr/modeling_detr.py
@@ -875,24 +875,6 @@ def forward(
         return outputs
 
 
-class DetrClassificationHead(nn.Module):
-    """Head for sentence-level classification tasks."""
-
-    def __init__(self, input_dim: int, inner_dim: int, num_classes: int, pooler_dropout: float):
-        super().__init__()
-        self.dense = nn.Linear(input_dim, inner_dim)
-        self.dropout = nn.Dropout(p=pooler_dropout)
-        self.out_proj = nn.Linear(inner_dim, num_classes)
-
-    def forward(self, hidden_states: torch.Tensor):
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.dense(hidden_states)
-        hidden_states = torch.tanh(hidden_states)
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.out_proj(hidden_states)
-        return hidden_states
-
-
 class DetrPreTrainedModel(PreTrainedModel):
     config_class = DetrConfig
     base_model_prefix = "model"
diff --git a/src/transformers/models/table_transformer/modeling_table_transformer.py b/src/transformers/models/table_transformer/modeling_table_transformer.py
index 05a548fd5ac92d..73d6a73398fbee 100644
--- a/src/transformers/models/table_transformer/modeling_table_transformer.py
+++ b/src/transformers/models/table_transformer/modeling_table_transformer.py
@@ -782,25 +782,6 @@ def forward(
         return outputs
 
 
-# Copied from transformers.models.detr.modeling_detr.DetrClassificationHead with Detr->TableTransformer
-class TableTransformerClassificationHead(nn.Module):
-    """Head for sentence-level classification tasks."""
-
-    def __init__(self, input_dim: int, inner_dim: int, num_classes: int, pooler_dropout: float):
-        super().__init__()
-        self.dense = nn.Linear(input_dim, inner_dim)
-        self.dropout = nn.Dropout(p=pooler_dropout)
-        self.out_proj = nn.Linear(inner_dim, num_classes)
-
-    def forward(self, hidden_states: torch.Tensor):
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.dense(hidden_states)
-        hidden_states = torch.tanh(hidden_states)
-        hidden_states = self.dropout(hidden_states)
-        hidden_states = self.out_proj(hidden_states)
-        return hidden_states
-
-
 class TableTransformerPreTrainedModel(PreTrainedModel):
     config_class = TableTransformerConfig
     base_model_prefix = "model"