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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. """
import inspect
import unittest
from datasets import load_dataset
@@ -236,18 +235,6 @@ class BeitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import BitConfig
@@ -202,18 +201,6 @@ class BitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self):
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import ConvNextConfig
@@ -212,18 +211,6 @@ class ConvNextModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
def test_feed_forward_chunking(self):
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import ConvNextV2Config
@@ -265,18 +264,6 @@ class ConvNextV2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
loss = model(**inputs).loss
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from math import floor
@@ -191,18 +190,6 @@ class CvtModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self):
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import Data2VecVisionConfig
@@ -220,18 +219,6 @@ class Data2VecVisionModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Te
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
import warnings
@@ -238,18 +237,6 @@ class DeiTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import collections
import inspect
import unittest
from transformers import DinatConfig
@@ -264,18 +263,6 @@ class DinatModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
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. """
import inspect
import unittest
from transformers import Dinov2Config
@@ -265,18 +264,6 @@ class Dinov2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import collections
import inspect
import unittest
from transformers import DonutSwinConfig
@@ -186,18 +185,6 @@ class DonutSwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
x = model.get_output_embeddings()
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):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
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. """
import inspect
import unittest
from transformers import DPTConfig
@@ -195,18 +194,6 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import Dinov2Config, DPTConfig
@@ -154,18 +153,6 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_inputs_embeds(self):
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import DPTConfig
@@ -209,18 +208,6 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
import warnings
from typing import List
@@ -223,18 +222,6 @@ class EfficientFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.T
def test_model_common_attributes(self):
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 check_hidden_states_output(inputs_dict, config, model_class):
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. """
import inspect
import unittest
from transformers import EfficientNetConfig
@@ -172,18 +171,6 @@ class EfficientNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Test
def test_feed_forward_chunking(self):
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):
config_and_inputs = self.model_tester.prepare_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. """
import collections
import inspect
import unittest
from transformers import FocalNetConfig
@@ -299,18 +298,6 @@ class FocalNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
x = model.get_output_embeddings()
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):
model = model_class(config)
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. """
import inspect
import unittest
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):
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):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
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. """
import inspect
import unittest
import warnings
from math import ceil, floor
@@ -218,18 +217,6 @@ class LevitModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_attention_outputs(self):
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 check_hidden_states_output(inputs_dict, config, model_class):
model = model_class(config)

13
tests/models/mask2former/test_modeling_mask2former.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" Testing suite for the PyTorch Mask2Former model. """
import inspect
import unittest
import numpy as np
@@ -242,18 +241,6 @@ class Mask2FormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
def test_multi_gpu_data_parallel_forward(self):
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
def test_model_from_pretrained(self):
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. """
import copy
import inspect
import unittest
import numpy as np
@@ -266,18 +265,6 @@ class MaskFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
def test_multi_gpu_data_parallel_forward(self):
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
def test_model_from_pretrained(self):
for model_name in ["facebook/maskformer-swin-small-coco"]:

13
tests/models/maskformer/test_modeling_maskformer_swin.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch MaskFormer Swin model. """
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
@@ -234,18 +233,6 @@ class MaskFormerSwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.Te
x = model.get_output_embeddings()
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")
def test_attention_outputs(self):
pass

13
tests/models/mgp_str/test_modeling_mgp_str.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" Testing suite for the PyTorch MGP-STR model. """
import inspect
import unittest
import requests
@@ -151,18 +150,6 @@ class MgpstrModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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")
def test_feed_forward_chunking(self):
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. """
import inspect
import unittest
from transformers import MobileNetV1Config
@@ -177,18 +176,6 @@ class MobileNetV1ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
def test_attention_outputs(self):
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/mobilenet_v2/test_modeling_mobilenet_v2.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch MobileNetV2 model. """
import inspect
import unittest
from transformers import MobileNetV2Config
@@ -228,18 +227,6 @@ class MobileNetV2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
def test_attention_outputs(self):
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import MobileViTConfig
@@ -221,18 +220,6 @@ class MobileViTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
def test_attention_outputs(self):
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import MobileViTV2Config
@@ -228,18 +227,6 @@ class MobileViTV2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
def test_multi_gpu_data_parallel_forward(self):
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):
config_and_inputs = self.model_tester.prepare_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. """
import collections
import inspect
import unittest
from transformers import NatConfig
@@ -261,18 +260,6 @@ class NatModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
self.skipTest("Nat's attention operation is handled entirely by NATTEN.")

13
tests/models/poolformer/test_modeling_poolformer.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch PoolFormer model. """
import inspect
import unittest
from transformers import is_torch_available, is_vision_available
@@ -208,18 +207,6 @@ class PoolFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCa
loss = model(**inputs).loss
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
def test_model_from_pretrained(self):
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. """
import inspect
import unittest
from transformers import is_torch_available, is_vision_available
@@ -253,18 +252,6 @@ class PvtModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
loss = model(**inputs).loss
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
def test_model_from_pretrained(self):
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. """
import inspect
import unittest
from transformers import RegNetConfig
@@ -161,18 +160,6 @@ class RegNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self):
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/resnet/test_modeling_resnet.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ResNet model. """
import inspect
import unittest
from transformers import ResNetConfig
@@ -206,18 +205,6 @@ class ResNetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
def test_model_common_attributes(self):
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/sam/test_modeling_sam.py
View File

@@ -16,7 +16,6 @@
import gc
import inspect
import unittest
import requests
@@ -338,18 +337,6 @@ class SamModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
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):
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):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True

13
tests/models/swiftformer/test_modeling_swiftformer.py
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@@ -16,7 +16,6 @@
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
@@ -177,18 +176,6 @@ class SwiftFormerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import collections
import inspect
import unittest
from transformers import SwinConfig
@@ -300,18 +299,6 @@ class SwinModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True

13
tests/models/swin2sr/test_modeling_swin2sr.py
View File

@@ -13,7 +13,6 @@
# See the License for the specific language governing permissions and
# limitations under the License.
""" Testing suite for the PyTorch Swin2SR model. """
import inspect
import unittest
from transformers import Swin2SRConfig
@@ -232,18 +231,6 @@ class Swin2SRModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
x = model.get_output_embeddings()
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
def test_model_from_pretrained(self):
for model_name in SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

13
tests/models/swinv2/test_modeling_swinv2.py
View File

@@ -14,7 +14,6 @@
# limitations under the License.
""" Testing suite for the PyTorch Swinv2 model. """
import collections
import inspect
import unittest
from transformers import Swinv2Config
@@ -220,18 +219,6 @@ class Swinv2ModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True

13
tests/models/timesformer/test_modeling_timesformer.py
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@@ -16,7 +16,6 @@
import copy
import inspect
import unittest
import numpy as np
@@ -204,18 +203,6 @@ class TimesformerModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestC
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
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):
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_for_semantic_segmentation(*config_and_inputs)

13
tests/models/videomae/test_modeling_videomae.py
View File

@@ -16,7 +16,6 @@
import copy
import inspect
import unittest
import numpy as np
@@ -228,18 +227,6 @@ class VideoMAEModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vit/test_modeling_vit.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ViT model. """
import inspect
import unittest
from transformers import ViTConfig
@@ -224,18 +223,6 @@ class ViTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import unittest
from transformers import ViTHybridConfig
@@ -185,18 +184,6 @@ class ViTHybridModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCas
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_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. """
import inspect
import math
import tempfile
import unittest
@@ -192,18 +191,6 @@ class ViTMAEModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vit_msn/test_modeling_vit_msn.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ViTMSN model. """
import inspect
import unittest
from transformers import ViTMSNConfig
@@ -183,18 +182,6 @@ class ViTMSNModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vitdet/test_modeling_vitdet.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch ViTDet model. """
import inspect
import unittest
from transformers import VitDetConfig
@@ -210,18 +209,6 @@ class VitDetModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/vitmatte/test_modeling_vitmatte.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch VitMatte model. """
import inspect
import unittest
from huggingface_hub import hf_hub_download
@@ -189,18 +188,6 @@ class VitMatteModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase
def test_model_common_attributes(self):
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

13
tests/models/yolos/test_modeling_yolos.py
View File

@@ -15,7 +15,6 @@
""" Testing suite for the PyTorch YOLOS model. """
import inspect
import unittest
from transformers import YolosConfig
@@ -217,18 +216,6 @@ class YolosModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
x = model.get_output_embeddings()
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):
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_model(*config_and_inputs)

2
tests/test_modeling_common.py
View File

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