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Export TensorFlow models to ONNX with dynamic input shapes (#19255)

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* validate onnx models with a different input geometry than saved with

* only test working features for now

* simpler test skipping

* rm TODO

* expose batch_size/seq_length on vit

* skip certain name, feature, framework parameterizations known to fail validation

* Trigger CI

* Trigger CI
This commit is contained in:
Dean Wyatte
2022-10-07 08:53:03 -06:00
committed by GitHub
parent 5fef17f490
commit a26d71d6ae
5 changed files with 63 additions and 15 deletions
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28
tests/onnx/test_onnx_v2.py
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@@ -284,10 +284,12 @@ class OnnxExportTestCaseV2(TestCase):
Integration tests ensuring supported models are correctly exported
"""
def _onnx_export(self, test_name, name, model_name, feature, onnx_config_class_constructor, device="cpu"):
def _onnx_export(
self, test_name, name, model_name, feature, onnx_config_class_constructor, device="cpu", framework="pt"
):
from transformers.onnx import export
model_class = FeaturesManager.get_model_class_for_feature(feature)
model_class = FeaturesManager.get_model_class_for_feature(feature, framework=framework)
config = AutoConfig.from_pretrained(model_name)
model = model_class.from_config(config)
@@ -296,6 +298,22 @@ class OnnxExportTestCaseV2(TestCase):
if model.__class__.__name__.startswith("Yolos") and device != "cpu":
return
# ONNX inference fails with the following name, feature, framework parameterizations
# See: https://github.com/huggingface/transformers/issues/19357
if (name, feature, framework) in {
("deberta-v2", "question-answering", "pt"),
("deberta-v2", "multiple-choice", "pt"),
("roformer", "multiple-choice", "pt"),
("groupvit", "default", "pt"),
("perceiver", "masked-lm", "pt"),
("perceiver", "sequence-classification", "pt"),
("perceiver", "image-classification", "pt"),
("bert", "multiple-choice", "tf"),
("camembert", "multiple-choice", "tf"),
("roberta", "multiple-choice", "tf"),
}:
return
onnx_config = onnx_config_class_constructor(model.config)
if is_torch_available():
@@ -364,13 +382,13 @@ class OnnxExportTestCaseV2(TestCase):
@require_tf
@require_vision
def test_tensorflow_export(self, test_name, name, model_name, feature, onnx_config_class_constructor):
self._onnx_export(test_name, name, model_name, feature, onnx_config_class_constructor)
self._onnx_export(test_name, name, model_name, feature, onnx_config_class_constructor, framework="tf")
@parameterized.expand(_get_models_to_test(TENSORFLOW_EXPORT_WITH_PAST_MODELS), skip_on_empty=True)
@slow
@require_tf
def test_tensorflow_export_with_past(self, test_name, name, model_name, feature, onnx_config_class_constructor):
self._onnx_export(test_name, name, model_name, feature, onnx_config_class_constructor)
self._onnx_export(test_name, name, model_name, feature, onnx_config_class_constructor, framework="tf")
@parameterized.expand(_get_models_to_test(TENSORFLOW_EXPORT_SEQ2SEQ_WITH_PAST_MODELS), skip_on_empty=True)
@slow
@@ -378,7 +396,7 @@ class OnnxExportTestCaseV2(TestCase):
def test_tensorflow_export_seq2seq_with_past(
self, test_name, name, model_name, feature, onnx_config_class_constructor
):
self._onnx_export(test_name, name, model_name, feature, onnx_config_class_constructor)
self._onnx_export(test_name, name, model_name, feature, onnx_config_class_constructor, framework="tf")
class StableDropoutTestCase(TestCase):