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Table transformer #1900

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Table transformer #1900

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890f733
try
Jun 6, 2024
ed771b3
fix
Jun 6, 2024
43030b5
cleaner
Jun 6, 2024
d0b5fec
fix test
Jun 7, 2024
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1 change: 1 addition & 0 deletions optimum/onnxruntime/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -129,6 +129,7 @@ class ORTConfigManager:
"pegasus": "bert",
"roberta": "bert",
"segformer": "vit",
"table-transformer": "vit",
"t5": "bert",
"vit": "vit",
"whisper": "bart",
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2 changes: 1 addition & 1 deletion optimum/utils/normalized_config.py
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Expand Up @@ -217,7 +217,6 @@ class NormalizedConfigManager:
'perceiver',
'roformer',
'squeezebert',
'table-transformer',
"""

# Contribution note: Please add new models in alphabetical order
Expand Down Expand Up @@ -273,6 +272,7 @@ class NormalizedConfigManager:
"segformer": NormalizedSegformerConfig,
"speech-to-text": SpeechToTextLikeNormalizedTextConfig,
"splinter": NormalizedTextConfig,
"table-transformer": NormalizedVisionConfig,
"t5": T5LikeNormalizedTextConfig,
"trocr": TrOCRLikeNormalizedTextConfig,
"vision-encoder-decoder": NormalizedEncoderDecoderConfig,
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17 changes: 13 additions & 4 deletions tests/onnxruntime/test_optimization.py
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Expand Up @@ -35,6 +35,7 @@
from optimum.onnxruntime import (
AutoOptimizationConfig,
ORTConfig,
ORTModelForCustomTasks,
ORTModelForImageClassification,
ORTModelForSemanticSegmentation,
ORTModelForSequenceClassification,
Expand Down Expand Up @@ -172,6 +173,7 @@ def test_compare_original_seq2seq_model_with_optimized_model(self, model_cls, mo

# Contribution note: Please add test models in alphabetical order. Find test models here: https://huggingface.co/hf-internal-testing.
SUPPORTED_IMAGE_ARCHITECTURES_WITH_MODEL_ID = (
(ORTModelForCustomTasks, "hf-internal-testing/tiny-random-TableTransformerModel"),
(ORTModelForSemanticSegmentation, "hf-internal-testing/tiny-random-segformer"),
(ORTModelForImageClassification, "hf-internal-testing/tiny-random-vit"),
)
Expand All @@ -191,11 +193,18 @@ def test_compare_original_image_model_with_optimized_model(self, model_cls, mode
# Verify the ORTConfig was correctly created and saved
self.assertEqual(ort_config.to_dict(), expected_ort_config.to_dict())

image = torch.ones((1, model.config.num_channels, model.config.image_size, model.config.image_size))
model_outputs = model(image)
optimized_model_outputs = optimized_model(image)
image_size = getattr(model.config, "image_size", 224)
image = torch.ones((1, model.config.num_channels, image_size, image_size))
model_outputs = model(pixel_values=image)
optimized_model_outputs = optimized_model(pixel_values=image)

# Compare tensors outputs
self.assertTrue(torch.equal(model_outputs.logits, optimized_model_outputs.logits))
if hasattr(model_outputs, 'logits'):
self.assertTrue(torch.equal(model_outputs.logits, optimized_model_outputs.logits), "Logits do not match")
elif hasattr(model_outputs, 'last_hidden_state'):
self.assertTrue(torch.equal(model_outputs.last_hidden_state, optimized_model_outputs.last_hidden_state), "last_hidden_state does not match")
else:
raise ValueError("Model outputs do not have logits or last_hidden_state")
gc.collect()

def test_optimization_details(self):
Expand Down