Update more tests

tests/models/bit/test_modeling_bit.py

@@ -52,7 +52,6 @@ def __init__(
         hidden_act="relu",
         num_labels=3,
         scope=None,
-        out_features=["stage2", "stage3", "stage4"],
         out_indices=[2, 3, 4],
         num_groups=1,
     ):
@@ -69,7 +68,6 @@ def __init__(
         self.num_labels = num_labels
         self.scope = scope
         self.num_stages = len(hidden_sizes)
-        self.out_features = out_features
         self.out_indices = out_indices
         self.num_groups = num_groups
 
@@ -92,7 +90,6 @@ def get_config(self):
             depths=self.depths,
             hidden_act=self.hidden_act,
             num_labels=self.num_labels,
-            out_features=self.out_features,
             out_indices=self.out_indices,
             num_groups=self.num_groups,
         )
@@ -122,15 +119,15 @@ def create_and_check_backbone(self, config, pixel_values, labels):
         result = model(pixel_values)
 
         # verify feature maps
-        self.parent.assertEqual(len(result.feature_maps), len(config.out_features))
+        self.parent.assertEqual(len(result.feature_maps), len(config.out_indices))
         self.parent.assertListEqual(list(result.feature_maps[0].shape), [self.batch_size, self.hidden_sizes[1], 4, 4])
 
         # verify channels
-        self.parent.assertEqual(len(model.channels), len(config.out_features))
+        self.parent.assertEqual(len(model.channels), len(config.out_indices))
         self.parent.assertListEqual(model.channels, config.hidden_sizes[1:])
 
-        # verify backbone works with out_features=None
-        config.out_features = None
+        # verify backbone works with out_indices=None
+        config.out_indices = None
         model = BitBackbone(config=config)
         model.to(torch_device)
         model.eval()

tests/models/conditional_detr/test_modeling_conditional_detr.py

@@ -116,7 +116,6 @@ def get_config(self):
             depths=[1, 1, 2, 1],
             hidden_act="relu",
             num_labels=3,
-            out_features=["stage2", "stage3", "stage4"],
             out_indices=[2, 3, 4],
         )
         return ConditionalDetrConfig(

tests/models/convnext/test_modeling_convnext.py

@@ -54,7 +54,6 @@ def __init__(
         hidden_act="gelu",
         num_labels=10,
         initializer_range=0.02,
-        out_features=["stage2", "stage3", "stage4"],
         out_indices=[2, 3, 4],
         scope=None,
     ):
@@ -71,7 +70,6 @@ def __init__(
         self.hidden_act = hidden_act
         self.num_labels = num_labels
         self.initializer_range = initializer_range
-        self.out_features = out_features
         self.out_indices = out_indices
         self.scope = scope
 
@@ -94,7 +92,6 @@ def get_config(self):
             hidden_act=self.hidden_act,
             is_decoder=False,
             initializer_range=self.initializer_range,
-            out_features=self.out_features,
             out_indices=self.out_indices,
             num_labels=self.num_labels,
         )
@@ -124,15 +121,15 @@ def create_and_check_backbone(self, config, pixel_values, labels):
         result = model(pixel_values)
 
         # verify hidden states
-        self.parent.assertEqual(len(result.feature_maps), len(config.out_features))
+        self.parent.assertEqual(len(result.feature_maps), len(config.out_indices))
         self.parent.assertListEqual(list(result.feature_maps[0].shape), [self.batch_size, self.hidden_sizes[1], 4, 4])
 
         # verify channels
-        self.parent.assertEqual(len(model.channels), len(config.out_features))
+        self.parent.assertEqual(len(model.channels), len(config.out_indices))
         self.parent.assertListEqual(model.channels, config.hidden_sizes[1:])
 
-        # verify backbone works with out_features=None
-        config.out_features = None
+        # verify backbone works with out_indices=None
+        config.out_indices = None
         model = ConvNextBackbone(config=config)
         model.to(torch_device)
         model.eval()

tests/models/convnextv2/test_modeling_convnextv2.py

@@ -55,7 +55,6 @@ def __init__(
         hidden_act="gelu",
         num_labels=10,
         initializer_range=0.02,
-        out_features=["stage2", "stage3", "stage4"],
         out_indices=[2, 3, 4],
         scope=None,
     ):
@@ -72,7 +71,6 @@ def __init__(
         self.hidden_act = hidden_act
         self.num_labels = num_labels
         self.initializer_range = initializer_range
-        self.out_features = out_features
         self.out_indices = out_indices
         self.scope = scope
 
@@ -96,7 +94,6 @@ def get_config(self):
             hidden_act=self.hidden_act,
             is_decoder=False,
             initializer_range=self.initializer_range,
-            out_features=self.out_features,
             out_indices=self.out_indices,
             num_labels=self.num_labels,
         )
@@ -126,15 +123,15 @@ def create_and_check_backbone(self, config, pixel_values, labels):
         result = model(pixel_values)
 
         # verify hidden states
-        self.parent.assertEqual(len(result.feature_maps), len(config.out_features))
+        self.parent.assertEqual(len(result.feature_maps), len(config.out_indices))
         self.parent.assertListEqual(list(result.feature_maps[0].shape), [self.batch_size, self.hidden_sizes[1], 4, 4])
 
         # verify channels
-        self.parent.assertEqual(len(model.channels), len(config.out_features))
+        self.parent.assertEqual(len(model.channels), len(config.out_indices))
         self.parent.assertListEqual(model.channels, config.hidden_sizes[1:])
 
-        # verify backbone works with out_features=None
-        config.out_features = None
+        # verify backbone works with out_indices=None
+        config.out_indices = None
         model = ConvNextV2Backbone(config=config)
         model.to(torch_device)
         model.eval()

tests/models/deformable_detr/test_modeling_deformable_detr.py

@@ -130,7 +130,6 @@ def get_config(self):
             depths=[1, 1, 2, 1],
             hidden_act="relu",
             num_labels=3,
-            out_features=["stage2", "stage3", "stage4"],
             out_indices=[2, 3, 4],
         )
         return DeformableDetrConfig(

tests/models/detr/test_modeling_detr.py

@@ -112,7 +112,6 @@ def get_config(self):
             depths=[1, 1, 2, 1],
             hidden_act="relu",
             num_labels=3,
-            out_features=["stage2", "stage3", "stage4"],
             out_indices=[2, 3, 4],
         )
         return DetrConfig(

tests/models/dinat/test_modeling_dinat.py

@@ -65,7 +65,6 @@ def __init__(
         scope=None,
         use_labels=True,
         num_labels=10,
-        out_features=["stage1", "stage2"],
         out_indices=[1, 2],
     ):
         self.parent = parent
@@ -91,7 +90,6 @@ def __init__(
         self.scope = scope
         self.use_labels = use_labels
         self.num_labels = num_labels
-        self.out_features = out_features
         self.out_indices = out_indices
 
     def prepare_config_and_inputs(self):
@@ -125,7 +123,6 @@ def get_config(self):
             patch_norm=self.patch_norm,
             layer_norm_eps=self.layer_norm_eps,
             initializer_range=self.initializer_range,
-            out_features=self.out_features,
             out_indices=self.out_indices,
         )
 
@@ -166,14 +163,14 @@ def create_and_check_backbone(self, config, pixel_values, labels):
         result = model(pixel_values)
 
         # verify hidden states
-        self.parent.assertEqual(len(result.feature_maps), len(config.out_features))
+        self.parent.assertEqual(len(result.feature_maps), len(config.out_indices))
         self.parent.assertListEqual(list(result.feature_maps[0].shape), [self.batch_size, model.channels[0], 16, 16])
 
         # verify channels
-        self.parent.assertEqual(len(model.channels), len(config.out_features))
+        self.parent.assertEqual(len(model.channels), len(config.out_indices))
 
-        # verify backbone works with out_features=None
-        config.out_features = None
+        # verify backbone works with out_indices=None
+        config.out_indices = None
         model = DinatBackbone(config=config)
         model.to(torch_device)
         model.eval()

tests/models/swin/test_modeling_swin.py

@@ -67,7 +67,6 @@ def __init__(
         use_labels=True,
         type_sequence_label_size=10,
         encoder_stride=8,
-        out_features=["stage1", "stage2"],
         out_indices=[1, 2],
     ):
         self.parent = parent
@@ -94,7 +93,6 @@ def __init__(
         self.use_labels = use_labels
         self.type_sequence_label_size = type_sequence_label_size
         self.encoder_stride = encoder_stride
-        self.out_features = out_features
         self.out_indices = out_indices
 
     def prepare_config_and_inputs(self):
@@ -128,7 +126,6 @@ def get_config(self):
             layer_norm_eps=self.layer_norm_eps,
             initializer_range=self.initializer_range,
             encoder_stride=self.encoder_stride,
-            out_features=self.out_features,
             out_indices=self.out_indices,
         )
 
@@ -150,14 +147,14 @@ def create_and_check_backbone(self, config, pixel_values, labels):
         result = model(pixel_values)
 
         # verify hidden states
-        self.parent.assertEqual(len(result.feature_maps), len(config.out_features))
+        self.parent.assertEqual(len(result.feature_maps), len(config.out_indices))
         self.parent.assertListEqual(list(result.feature_maps[0].shape), [self.batch_size, model.channels[0], 16, 16])
 
         # verify channels
-        self.parent.assertEqual(len(model.channels), len(config.out_features))
+        self.parent.assertEqual(len(model.channels), len(config.out_indices))
 
-        # verify backbone works with out_features=None
-        config.out_features = None
+        # verify backbone works with out_indices=None
+        config.out_indices = None
         model = SwinBackbone(config=config)
         model.to(torch_device)
         model.eval()

tests/models/tvp/test_modeling_tvp.py

@@ -118,7 +118,6 @@ def get_config(self):
             hidden_sizes=[64, 128],
             depths=[2, 2],
             hidden_act="relu",
-            out_features=["stage2"],
             out_indices=[2],
         )
         return TvpConfig(

tests/models/upernet/test_modeling_upernet.py

@@ -62,7 +62,7 @@ def __init__(
         hidden_act="gelu",
         type_sequence_label_size=10,
         initializer_range=0.02,
-        out_features=["stage2", "stage3", "stage4"],
+        out_indices=[2, 3, 4],
         num_labels=3,
         scope=None,
     ):
@@ -79,7 +79,7 @@ def __init__(
         self.hidden_act = hidden_act
         self.type_sequence_label_size = type_sequence_label_size
         self.initializer_range = initializer_range
-        self.out_features = out_features
+        self.out_indices = out_indices
         self.num_labels = num_labels
         self.scope = scope
         self.num_hidden_layers = num_stages
@@ -104,7 +104,7 @@ def get_backbone_config(self):
             is_training=self.is_training,
             intermediate_size=self.intermediate_size,
             hidden_act=self.hidden_act,
-            out_features=self.out_features,
+            out_indices=self.out_indices,
         )
 
     def get_config(self):

tests/models/zoedepth/test_modeling_zoedepth.py

@@ -52,7 +52,7 @@ def __init__(
         num_hidden_layers=2,
         num_attention_heads=2,
         intermediate_size=8,
-        out_features=["stage1", "stage2"],
+        out_indices=[1, 2],
         apply_layernorm=False,
         reshape_hidden_states=False,
         neck_hidden_sizes=[2, 2],
@@ -69,7 +69,7 @@ def __init__(
         self.num_hidden_layers = num_hidden_layers
         self.num_attention_heads = num_attention_heads
         self.intermediate_size = intermediate_size
-        self.out_features = out_features
+        self.out_indices = out_indices
         self.apply_layernorm = apply_layernorm
         self.reshape_hidden_states = reshape_hidden_states
         self.use_labels = use_labels
@@ -113,7 +113,7 @@ def get_backbone_config(self):
             num_attention_heads=self.num_attention_heads,
             intermediate_size=self.intermediate_size,
             is_training=self.is_training,
-            out_features=self.out_features,
+            out_indices=self.out_indices,
             reshape_hidden_states=self.reshape_hidden_states,
         )