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Update forward signature test for vision models (#27681)

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* Update forward signature

* Empty-Commit
This commit is contained in:
NielsRogge
2023-11-27 15:48:17 +01:00
committed by GitHub
parent 1d7f406e19
commit 59499bbe8b
48 changed files with 1 additions and 612 deletions
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13
tests/models/beit/test_modeling_beit.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch BEiT model. """ """ Testing suite for the PyTorch BEiT model. """
import inspect
import unittest import unittest
from datasets import load_dataset from datasets import load_dataset
@@ -236,18 +235,6 @@ class BeitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/bit/test_modeling_bit.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch Bit model. """ """ Testing suite for the PyTorch Bit model. """
import inspect
import unittest import unittest
from transformers import BitConfig from transformers import BitConfig
@@ -202,18 +201,6 @@ class BitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self): def test_model_common_attributes(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/convnext/test_modeling_convnext.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ConvNext model. """ """ Testing suite for the PyTorch ConvNext model. """
import inspect
import unittest import unittest
from transformers import ConvNextConfig from transformers import ConvNextConfig
@@ -212,18 +211,6 @@ class ConvNextModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
def test_feed_forward_chunking(self): def test_feed_forward_chunking(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/convnextv2/test_modeling_convnextv2.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ConvNextV2 model. """ """ Testing suite for the PyTorch ConvNextV2 model. """
import inspect
import unittest import unittest
from transformers import ConvNextV2Config from transformers import ConvNextV2Config
@@ -265,18 +264,6 @@ class ConvNextV2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
loss = model(**inputs).loss loss = model(**inputs).loss
loss.backward() loss.backward()
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/cvt/test_modeling_cvt.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch CvT model. """ """ Testing suite for the PyTorch CvT model. """
import inspect
import unittest import unittest
from math import floor from math import floor
@@ -191,18 +190,6 @@ class CvtModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self): def test_model_common_attributes(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/data2vec/test_modeling_data2vec_vision.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch Data2VecVision model. """ """ Testing suite for the PyTorch Data2VecVision model. """
import inspect
import unittest import unittest
from transformers import Data2VecVisionConfig from transformers import Data2VecVisionConfig
@@ -220,18 +219,6 @@ class Data2VecVisionModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Te
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/deit/test_modeling_deit.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch DeiT model. """ """ Testing suite for the PyTorch DeiT model. """
import inspect
import unittest import unittest
import warnings import warnings
@@ -238,18 +237,6 @@ class DeiTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/dinat/test_modeling_dinat.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch Dinat model. """ """ Testing suite for the PyTorch Dinat model. """
import collections import collections
import inspect
import unittest import unittest
from transformers import DinatConfig from transformers import DinatConfig
@@ -264,18 +263,6 @@ class DinatModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_attention_outputs(self): def test_attention_outputs(self):
self.skipTest("Dinat's attention operation is handled entirely by NATTEN.") self.skipTest("Dinat's attention operation is handled entirely by NATTEN.")

13
tests/models/dinov2/test_modeling_dinov2.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch Dinov2 model. """ """ Testing suite for the PyTorch Dinov2 model. """
import inspect
import unittest import unittest
from transformers import Dinov2Config from transformers import Dinov2Config
@@ -265,18 +264,6 @@ class Dinov2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/donut/test_modeling_donut_swin.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch Donut Swin model. """ """ Testing suite for the PyTorch Donut Swin model. """
import collections import collections
import inspect
import unittest import unittest
from transformers import DonutSwinConfig from transformers import DonutSwinConfig
@@ -186,18 +185,6 @@ class DonutSwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_attention_outputs(self): def test_attention_outputs(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common() config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True config.return_dict = True

13
tests/models/dpt/test_modeling_dpt.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch DPT model. """ """ Testing suite for the PyTorch DPT model. """
import inspect
import unittest import unittest
from transformers import DPTConfig from transformers import DPTConfig
@@ -195,18 +194,6 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/dpt/test_modeling_dpt_auto_backbone.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch DPT model. """ """ Testing suite for the PyTorch DPT model. """
import inspect
import unittest import unittest
from transformers import Dinov2Config, DPTConfig from transformers import Dinov2Config, DPTConfig
@@ -154,18 +153,6 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_inputs_embeds(self): def test_inputs_embeds(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_for_depth_estimation(self): def test_for_depth_estimation(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_for_depth_estimation(*config_and_inputs) self.model_tester.create_and_check_for_depth_estimation(*config_and_inputs)

13
tests/models/dpt/test_modeling_dpt_hybrid.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch DPT model. """ """ Testing suite for the PyTorch DPT model. """
import inspect
import unittest import unittest
from transformers import DPTConfig from transformers import DPTConfig
@@ -209,18 +208,6 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/efficientformer/test_modeling_efficientformer.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch EfficientFormer model. """ """ Testing suite for the PyTorch EfficientFormer model. """
import inspect
import unittest import unittest
import warnings import warnings
from typing import List from typing import List
@@ -223,18 +222,6 @@ class EfficientFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.T
def test_model_common_attributes(self): def test_model_common_attributes(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_hidden_states_output(self): def test_hidden_states_output(self):
def check_hidden_states_output(inputs_dict, config, model_class): def check_hidden_states_output(inputs_dict, config, model_class):
model = model_class(config) model = model_class(config)

13
tests/models/efficientnet/test_modeling_efficientnet.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch EfficientNet model. """ """ Testing suite for the PyTorch EfficientNet model. """
import inspect
import unittest import unittest
from transformers import EfficientNetConfig from transformers import EfficientNetConfig
@@ -172,18 +171,6 @@ class EfficientNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Test
def test_feed_forward_chunking(self): def test_feed_forward_chunking(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/focalnet/test_modeling_focalnet.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch FocalNet model. """ """ Testing suite for the PyTorch FocalNet model. """
import collections import collections
import inspect
import unittest import unittest
from transformers import FocalNetConfig from transformers import FocalNetConfig
@@ -299,18 +298,6 @@ class FocalNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes[:-1]:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def check_hidden_states_output(self, inputs_dict, config, model_class, image_size): def check_hidden_states_output(self, inputs_dict, config, model_class, image_size):
model = model_class(config) model = model_class(config)
model.to(torch_device) model.to(torch_device)

13
tests/models/glpn/test_modeling_glpn.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch GLPN model. """ """ Testing suite for the PyTorch GLPN model. """
import inspect
import unittest import unittest
from transformers import is_torch_available, is_vision_available from transformers import is_torch_available, is_vision_available
@@ -177,18 +176,6 @@ class GLPNModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self): def test_model_common_attributes(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_attention_outputs(self): def test_attention_outputs(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common() config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True config.return_dict = True

13
tests/models/levit/test_modeling_levit.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch LeViT model. """ """ Testing suite for the PyTorch LeViT model. """
import inspect
import unittest import unittest
import warnings import warnings
from math import ceil, floor from math import ceil, floor
@@ -218,18 +217,6 @@ class LevitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_attention_outputs(self): def test_attention_outputs(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_hidden_states_output(self): def test_hidden_states_output(self):
def check_hidden_states_output(inputs_dict, config, model_class): def check_hidden_states_output(inputs_dict, config, model_class):
model = model_class(config) model = model_class(config)

13
tests/models/mask2former/test_modeling_mask2former.py
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@@ -14,7 +14,6 @@
# limitations under the License. # limitations under the License.
""" Testing suite for the PyTorch Mask2Former model. """ """ Testing suite for the PyTorch Mask2Former model. """
import inspect
import unittest import unittest
import numpy as np import numpy as np
@@ -242,18 +241,6 @@ class Mask2FormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
def test_multi_gpu_data_parallel_forward(self): def test_multi_gpu_data_parallel_forward(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in ["facebook/mask2former-swin-small-coco-instance"]: for model_name in ["facebook/mask2former-swin-small-coco-instance"]:

13
tests/models/maskformer/test_modeling_maskformer.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch MaskFormer model. """ """ Testing suite for the PyTorch MaskFormer model. """
import copy import copy
import inspect
import unittest import unittest
import numpy as np import numpy as np
@@ -266,18 +265,6 @@ class MaskFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
def test_multi_gpu_data_parallel_forward(self): def test_multi_gpu_data_parallel_forward(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in ["facebook/maskformer-swin-small-coco"]: for model_name in ["facebook/maskformer-swin-small-coco"]:

13
tests/models/maskformer/test_modeling_maskformer_swin.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch MaskFormer Swin model. """ """ Testing suite for the PyTorch MaskFormer Swin model. """
import collections import collections
import inspect
import unittest import unittest
from typing import Dict, List, Tuple from typing import Dict, List, Tuple
@@ -234,18 +233,6 @@ class MaskFormerSwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Te
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
@unittest.skip(reason="MaskFormerSwin is only used as backbone and doesn't support output_attentions") @unittest.skip(reason="MaskFormerSwin is only used as backbone and doesn't support output_attentions")
def test_attention_outputs(self): def test_attention_outputs(self):
pass pass

13
tests/models/mgp_str/test_modeling_mgp_str.py
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@@ -14,7 +14,6 @@
# limitations under the License. # limitations under the License.
""" Testing suite for the PyTorch MGP-STR model. """ """ Testing suite for the PyTorch MGP-STR model. """
import inspect
import unittest import unittest
import requests import requests
@@ -151,18 +150,6 @@ class MgpstrModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
@unittest.skip(reason="MgpstrModel does not support feedforward chunking") @unittest.skip(reason="MgpstrModel does not support feedforward chunking")
def test_feed_forward_chunking(self): def test_feed_forward_chunking(self):
pass pass

13
tests/models/mobilenet_v1/test_modeling_mobilenet_v1.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch MobileNetV1 model. """ """ Testing suite for the PyTorch MobileNetV1 model. """
import inspect
import unittest import unittest
from transformers import MobileNetV1Config from transformers import MobileNetV1Config
@@ -177,18 +176,6 @@ class MobileNetV1ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
def test_attention_outputs(self): def test_attention_outputs(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/mobilenet_v2/test_modeling_mobilenet_v2.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch MobileNetV2 model. """ """ Testing suite for the PyTorch MobileNetV2 model. """
import inspect
import unittest import unittest
from transformers import MobileNetV2Config from transformers import MobileNetV2Config
@@ -228,18 +227,6 @@ class MobileNetV2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
def test_attention_outputs(self): def test_attention_outputs(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/mobilevit/test_modeling_mobilevit.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch MobileViT model. """ """ Testing suite for the PyTorch MobileViT model. """
import inspect
import unittest import unittest
from transformers import MobileViTConfig from transformers import MobileViTConfig
@@ -221,18 +220,6 @@ class MobileViTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
def test_attention_outputs(self): def test_attention_outputs(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/mobilevitv2/test_modeling_mobilevitv2.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch MobileViTV2 model. """ """ Testing suite for the PyTorch MobileViTV2 model. """
import inspect
import unittest import unittest
from transformers import MobileViTV2Config from transformers import MobileViTV2Config
@@ -228,18 +227,6 @@ class MobileViTV2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
def test_multi_gpu_data_parallel_forward(self): def test_multi_gpu_data_parallel_forward(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/nat/test_modeling_nat.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch Nat model. """ """ Testing suite for the PyTorch Nat model. """
import collections import collections
import inspect
import unittest import unittest
from transformers import NatConfig from transformers import NatConfig
@@ -261,18 +260,6 @@ class NatModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_attention_outputs(self): def test_attention_outputs(self):
self.skipTest("Nat's attention operation is handled entirely by NATTEN.") self.skipTest("Nat's attention operation is handled entirely by NATTEN.")

13
tests/models/poolformer/test_modeling_poolformer.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch PoolFormer model. """ """ Testing suite for the PyTorch PoolFormer model. """
import inspect
import unittest import unittest
from transformers import is_torch_available, is_vision_available from transformers import is_torch_available, is_vision_available
@@ -208,18 +207,6 @@ class PoolFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
loss = model(**inputs).loss loss = model(**inputs).loss
loss.backward() loss.backward()
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: for model_name in POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

13
tests/models/pvt/test_modeling_pvt.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch Pvt model. """ """ Testing suite for the PyTorch Pvt model. """
import inspect
import unittest import unittest
from transformers import is_torch_available, is_vision_available from transformers import is_torch_available, is_vision_available
@@ -253,18 +252,6 @@ class PvtModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
loss = model(**inputs).loss loss = model(**inputs).loss
loss.backward() loss.backward()
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in PVT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: for model_name in PVT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

13
tests/models/regnet/test_modeling_regnet.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch RegNet model. """ """ Testing suite for the PyTorch RegNet model. """
import inspect
import unittest import unittest
from transformers import RegNetConfig from transformers import RegNetConfig
@@ -161,18 +160,6 @@ class RegNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self): def test_model_common_attributes(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/resnet/test_modeling_resnet.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ResNet model. """ """ Testing suite for the PyTorch ResNet model. """
import inspect
import unittest import unittest
from transformers import ResNetConfig from transformers import ResNetConfig
@@ -206,18 +205,6 @@ class ResNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self): def test_model_common_attributes(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/sam/test_modeling_sam.py
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@@ -16,7 +16,6 @@
import gc import gc
import inspect
import unittest import unittest
import requests import requests
@@ -338,18 +337,6 @@ class SamModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/segformer/test_modeling_segformer.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch SegFormer model. """ """ Testing suite for the PyTorch SegFormer model. """
import inspect
import unittest import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available from transformers import SegformerConfig, is_torch_available, is_vision_available
@@ -212,18 +211,6 @@ class SegformerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
def test_model_common_attributes(self): def test_model_common_attributes(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_attention_outputs(self): def test_attention_outputs(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common() config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True config.return_dict = True

13
tests/models/swiftformer/test_modeling_swiftformer.py
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@@ -16,7 +16,6 @@
import copy import copy
import inspect
import unittest import unittest
from transformers import PretrainedConfig, SwiftFormerConfig from transformers import PretrainedConfig, SwiftFormerConfig
@@ -177,18 +176,6 @@ class SwiftFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/swin/test_modeling_swin.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch Swin model. """ """ Testing suite for the PyTorch Swin model. """
import collections import collections
import inspect
import unittest import unittest
from transformers import SwinConfig from transformers import SwinConfig
@@ -300,18 +299,6 @@ class SwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_attention_outputs(self): def test_attention_outputs(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common() config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True config.return_dict = True

13
tests/models/swin2sr/test_modeling_swin2sr.py
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@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
""" Testing suite for the PyTorch Swin2SR model. """ """ Testing suite for the PyTorch Swin2SR model. """
import inspect
import unittest import unittest
from transformers import Swin2SRConfig from transformers import Swin2SRConfig
@@ -232,18 +231,6 @@ class Swin2SRModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
@slow @slow
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: for model_name in SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

13
tests/models/swinv2/test_modeling_swinv2.py
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@@ -14,7 +14,6 @@
# limitations under the License. # limitations under the License.
""" Testing suite for the PyTorch Swinv2 model. """ """ Testing suite for the PyTorch Swinv2 model. """
import collections import collections
import inspect
import unittest import unittest
from transformers import Swinv2Config from transformers import Swinv2Config
@@ -220,18 +219,6 @@ class Swinv2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_attention_outputs(self): def test_attention_outputs(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common() config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True config.return_dict = True

13
tests/models/timesformer/test_modeling_timesformer.py
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@@ -16,7 +16,6 @@
import copy import copy
import inspect
import unittest import unittest
import numpy as np import numpy as np
@@ -204,18 +203,6 @@ class TimesformerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/upernet/test_modeling_upernet.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch UperNet framework. """ """ Testing suite for the PyTorch UperNet framework. """
import inspect
import unittest import unittest
from huggingface_hub import hf_hub_download from huggingface_hub import hf_hub_download
@@ -170,18 +169,6 @@ class UperNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
def create_and_test_config_common_properties(self): def create_and_test_config_common_properties(self):
return return
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_for_semantic_segmentation(self): def test_for_semantic_segmentation(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_for_semantic_segmentation(*config_and_inputs) self.model_tester.create_and_check_for_semantic_segmentation(*config_and_inputs)

13
tests/models/videomae/test_modeling_videomae.py
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@@ -16,7 +16,6 @@
import copy import copy
import inspect
import unittest import unittest
import numpy as np import numpy as np
@@ -228,18 +227,6 @@ class VideoMAEModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vit/test_modeling_vit.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ViT model. """ """ Testing suite for the PyTorch ViT model. """
import inspect
import unittest import unittest
from transformers import ViTConfig from transformers import ViTConfig
@@ -224,18 +223,6 @@ class ViTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vit_hybrid/test_modeling_vit_hybrid.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ViT Hybrid model. """ """ Testing suite for the PyTorch ViT Hybrid model. """
import inspect
import unittest import unittest
from transformers import ViTHybridConfig from transformers import ViTHybridConfig
@@ -185,18 +184,6 @@ class ViTHybridModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vit_mae/test_modeling_vit_mae.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ViTMAE model. """ """ Testing suite for the PyTorch ViTMAE model. """
import inspect
import math import math
import tempfile import tempfile
import unittest import unittest
@@ -192,18 +191,6 @@ class ViTMAEModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vit_msn/test_modeling_vit_msn.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ViTMSN model. """ """ Testing suite for the PyTorch ViTMSN model. """
import inspect
import unittest import unittest
from transformers import ViTMSNConfig from transformers import ViTMSNConfig
@@ -183,18 +182,6 @@ class ViTMSNModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vitdet/test_modeling_vitdet.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ViTDet model. """ """ Testing suite for the PyTorch ViTDet model. """
import inspect
import unittest import unittest
from transformers import VitDetConfig from transformers import VitDetConfig
@@ -210,18 +209,6 @@ class VitDetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vitmatte/test_modeling_vitmatte.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch VitMatte model. """ """ Testing suite for the PyTorch VitMatte model. """
import inspect
import unittest import unittest
from huggingface_hub import hf_hub_download from huggingface_hub import hf_hub_download
@@ -189,18 +188,6 @@ class VitMatteModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
def test_model_common_attributes(self): def test_model_common_attributes(self):
pass pass
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/yolos/test_modeling_yolos.py
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@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch YOLOS model. """ """ Testing suite for the PyTorch YOLOS model. """
import inspect
import unittest import unittest
from transformers import YolosConfig from transformers import YolosConfig
@@ -217,18 +216,6 @@ class YolosModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings() x = model.get_output_embeddings()
self.assertTrue(x is None or isinstance(x, nn.Linear)) self.assertTrue(x is None or isinstance(x, nn.Linear))
def test_forward_signature(self):
config, _ = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
model = model_class(config)
signature = inspect.signature(model.forward)
# signature.parameters is an OrderedDict => so arg_names order is deterministic
arg_names = [*signature.parameters.keys()]
expected_arg_names = ["pixel_values"]
self.assertListEqual(arg_names[:1], expected_arg_names)
def test_model(self): def test_model(self):
config_and_inputs = self.model_tester.prepare_config_and_inputs() config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs) self.model_tester.create_and_check_model(*config_and_inputs)

2
tests/test_modeling_common.py
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@@ -543,7 +543,7 @@ class ModelTesterMixin:
) )
self.assertListEqual(arg_names[: len(expected_arg_names)], expected_arg_names) self.assertListEqual(arg_names[: len(expected_arg_names)], expected_arg_names)
else: else:
expected_arg_names = ["input_ids"] expected_arg_names = [model.main_input_name]
self.assertListEqual(arg_names[:1], expected_arg_names) self.assertListEqual(arg_names[:1], expected_arg_names)
def check_training_gradient_checkpointing(self, gradient_checkpointing_kwargs=None): def check_training_gradient_checkpointing(self, gradient_checkpointing_kwargs=None):