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Enable more test_torchscript (#16679)

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* update _create_and_check_torchscript

* Enable test_torchscript

* clear_class_registry

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2022-04-11 18:23:35 +02:00
committed by GitHub
parent 3918d6a9d6
commit c04619ecf3
32 changed files with 9 additions and 39 deletions
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1
tests/beit/test_modeling_beit.py
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@@ -192,7 +192,6 @@ class BeitModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False

1
tests/canine/test_modeling_canine.py
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@@ -219,7 +219,6 @@ class CanineModelTest(ModelTesterMixin, unittest.TestCase):
else ()
)
test_torchscript = False
test_mismatched_shapes = False
test_resize_embeddings = False
test_pruning = False

1
tests/clip/test_modeling_clip.py
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@@ -151,7 +151,6 @@ class CLIPVisionModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (CLIPVisionModel,) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False

1
tests/convnext/test_modeling_convnext.py
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@@ -138,7 +138,6 @@ class ConvNextModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False
has_attentions = False

1
tests/ctrl/test_modeling_ctrl.py
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@@ -174,7 +174,6 @@ class CTRLModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
all_model_classes = (CTRLModel, CTRLLMHeadModel, CTRLForSequenceClassification) if is_torch_available() else ()
all_generative_model_classes = (CTRLLMHeadModel,) if is_torch_available() else ()
test_pruning = True
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False

1
tests/data2vec/test_modeling_data2vec_audio.py
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@@ -372,7 +372,6 @@ class Data2VecAudioModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_headmasking = False
test_torchscript = False
def setUp(self):
self.model_tester = Data2VecAudioModelTester(self)

1
tests/decision_transformer/test_modeling_decision_transformer.py
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@@ -148,6 +148,7 @@ class DecisionTransformerModelTest(ModelTesterMixin, GenerationTesterMixin, unit
test_inputs_embeds = False
test_model_common_attributes = False
test_gradient_checkpointing = False
test_torchscript = False
def setUp(self):
self.model_tester = DecisionTransformerModelTester(self)

1
tests/deit/test_modeling_deit.py
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@@ -169,7 +169,6 @@ class DeiTModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False

1
tests/distilbert/test_modeling_distilbert.py
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@@ -211,7 +211,6 @@ class DistilBertModelTest(ModelTesterMixin, unittest.TestCase):
)
fx_compatible = True
test_pruning = True
test_torchscript = True
test_resize_embeddings = True
test_resize_position_embeddings = True

1
tests/dpt/test_modeling_dpt.py
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@@ -154,7 +154,6 @@ class DPTModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (DPTModel, DPTForDepthEstimation, DPTForSemanticSegmentation) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False

1
tests/fnet/test_modeling_fnet.py
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@@ -284,7 +284,6 @@ class FNetModelTest(ModelTesterMixin, unittest.TestCase):
# Skip Tests
test_pruning = False
test_torchscript = False
test_head_masking = False
test_pruning = False

1
tests/glpn/test_modeling_glpn.py
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@@ -150,7 +150,6 @@ class GLPNModelTest(ModelTesterMixin, unittest.TestCase):
test_head_masking = False
test_pruning = False
test_resize_embeddings = False
test_torchscript = False
def setUp(self):
self.model_tester = GLPNModelTester(self)

2
tests/hubert/test_modeling_hubert.py
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@@ -300,7 +300,6 @@ class HubertModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (HubertForCTC, HubertForSequenceClassification, HubertModel) if is_torch_available() else ()
test_pruning = False
test_headmasking = False
test_torchscript = False
def setUp(self):
self.model_tester = HubertModelTester(self)
@@ -445,7 +444,6 @@ class HubertRobustModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (HubertForCTC, HubertForSequenceClassification, HubertModel) if is_torch_available() else ()
test_pruning = False
test_headmasking = False
test_torchscript = False
def setUp(self):
self.model_tester = HubertModelTester(

1
tests/maskformer/test_modeling_maskformer.py
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@@ -177,7 +177,6 @@ class MaskFormerModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (MaskFormerModel, MaskFormerForInstanceSegmentation) if is_torch_available() else ()
is_encoder_decoder = False
test_torchscript = False
test_pruning = False
test_head_masking = False
test_missing_keys = False

1
tests/mpnet/test_modeling_mpnet.py
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@@ -205,7 +205,6 @@ class MPNetModelTest(ModelTesterMixin, unittest.TestCase):
else ()
)
test_pruning = False
test_torchscript = True
test_resize_embeddings = True
def setUp(self):

5
tests/prophetnet/test_modeling_prophetnet.py
View File

@@ -890,7 +890,6 @@ class ProphetNetModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.Test
all_model_classes = (ProphetNetModel, ProphetNetForConditionalGeneration) if is_torch_available() else ()
all_generative_model_classes = (ProphetNetForConditionalGeneration,) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
is_encoder_decoder = True
@@ -1100,7 +1099,7 @@ class ProphetNetStandaloneDecoderModelTest(ModelTesterMixin, GenerationTesterMix
all_model_classes = (ProphetNetDecoder, ProphetNetForCausalLM) if is_torch_available() else ()
all_generative_model_classes = (ProphetNetForCausalLM,) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
is_encoder_decoder = False
@@ -1128,7 +1127,7 @@ class ProphetNetStandaloneDecoderModelTest(ModelTesterMixin, GenerationTesterMix
class ProphetNetStandaloneEncoderModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (ProphetNetEncoder,) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
is_encoder_decoder = False

1
tests/regnet/test_modeling_regnet.py
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@@ -127,7 +127,6 @@ class RegNetModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (RegNetModel, RegNetForImageClassification) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False
has_attentions = False

1
tests/resnet/test_modeling_resnet.py
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@@ -127,7 +127,6 @@ class ResNetModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (ResNetModel, ResNetForImageClassification) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False
has_attentions = False

1
tests/segformer/test_modeling_segformer.py
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@@ -165,7 +165,6 @@ class SegformerModelTest(ModelTesterMixin, unittest.TestCase):
test_head_masking = False
test_pruning = False
test_resize_embeddings = False
test_torchscript = False
def setUp(self):
self.model_tester = SegformerModelTester(self)

1
tests/sew/test_modeling_sew.py
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@@ -303,7 +303,6 @@ class SEWModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (SEWForCTC, SEWModel, SEWForSequenceClassification) if is_torch_available() else ()
test_pruning = False
test_headmasking = False
test_torchscript = False
def setUp(self):
self.model_tester = SEWModelTester(self)

1
tests/speech_to_text/test_modeling_speech_to_text.py
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@@ -273,7 +273,6 @@ class Speech2TextModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.Tes
is_encoder_decoder = True
test_pruning = False
test_missing_keys = False
test_torchscript = True
input_name = "input_features"

1
tests/squeezebert/test_modeling_squeezebert.py
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@@ -229,7 +229,6 @@ class SqueezeBertModelTest(ModelTesterMixin, unittest.TestCase):
else None
)
test_pruning = False
test_torchscript = True
test_resize_embeddings = True
test_head_masking = False

1
tests/swin/test_modeling_swin.py
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@@ -177,7 +177,6 @@ class SwinModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False

2
tests/t5/test_modeling_t5.py
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@@ -512,7 +512,6 @@ class T5ModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
fx_compatible = True
all_parallelizable_model_classes = (T5Model, T5ForConditionalGeneration) if is_torch_available() else ()
test_pruning = False
test_torchscript = True
test_resize_embeddings = True
test_model_parallel = True
is_encoder_decoder = True
@@ -777,7 +776,6 @@ class T5EncoderOnlyModelTester:
class T5EncoderOnlyModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (T5EncoderModel,) if is_torch_available() else ()
test_pruning = False
test_torchscript = True
test_resize_embeddings = False
test_model_parallel = True
all_parallelizable_model_classes = (T5EncoderModel,) if is_torch_available() else ()

1
tests/tapas/test_modeling_tapas.py
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@@ -422,7 +422,6 @@ class TapasModelTest(ModelTesterMixin, unittest.TestCase):
else None
)
test_pruning = False
test_torchscript = False
test_resize_embeddings = True
test_head_masking = False

10
tests/test_modeling_common.py
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@@ -617,19 +617,21 @@ class ModelTesterMixin:
model.eval()
inputs = self._prepare_for_class(inputs_dict, model_class)
main_input_name = model_class.main_input_name
try:
if model.config.is_encoder_decoder:
model.config.use_cache = False # FSTM still requires this hack -> FSTM should probably be refactored similar to BART afterward
input_ids = inputs["input_ids"]
main_input = inputs[main_input_name]
attention_mask = inputs["attention_mask"]
decoder_input_ids = inputs["decoder_input_ids"]
decoder_attention_mask = inputs["decoder_attention_mask"]
traced_model = torch.jit.trace(
model, (input_ids, attention_mask, decoder_input_ids, decoder_attention_mask)
model, (main_input, attention_mask, decoder_input_ids, decoder_attention_mask)
)
else:
input_ids = inputs["input_ids"]
traced_model = torch.jit.trace(model, input_ids)
main_input = inputs[main_input_name]
traced_model = torch.jit.trace(model, main_input)
except RuntimeError:
self.fail("Couldn't trace module.")

1
tests/transfo_xl/test_modeling_transfo_xl.py
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@@ -238,7 +238,6 @@ class TransfoXLModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestC
)
all_generative_model_classes = (TransfoXLLMHeadModel,) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = True
test_mismatched_shapes = False

1
tests/unispeech/test_modeling_unispeech.py
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@@ -305,7 +305,6 @@ class UniSpeechRobustModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_headmasking = False
test_torchscript = False
def setUp(self):
self.model_tester = UniSpeechModelTester(

1
tests/van/test_modeling_van.py
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@@ -124,7 +124,6 @@ class VanModelTest(ModelTesterMixin, unittest.TestCase):
all_model_classes = (VanModel, VanForImageClassification) if is_torch_available() else ()
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False
has_attentions = False

1
tests/vit/test_modeling_vit.py
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@@ -158,7 +158,6 @@ class ViTModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_torchscript = False
test_resize_embeddings = False
test_head_masking = False

2
tests/wav2vec2/test_modeling_wav2vec2.py
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@@ -413,7 +413,6 @@ class Wav2Vec2ModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_headmasking = False
test_torchscript = False
def setUp(self):
self.model_tester = Wav2Vec2ModelTester(self)
@@ -652,7 +651,6 @@ class Wav2Vec2RobustModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_headmasking = False
test_torchscript = False
def setUp(self):
self.model_tester = Wav2Vec2ModelTester(

1
tests/wavlm/test_modeling_wavlm.py
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@@ -316,7 +316,6 @@ class WavLMModelTest(ModelTesterMixin, unittest.TestCase):
)
test_pruning = False
test_headmasking = False
test_torchscript = False
def setUp(self):
self.model_tester = WavLMModelTester(self)