Use convert_model in tests #2102
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Additional details and impacted files@@ Coverage Diff @@
## develop #2102 +/- ##
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+ Coverage 0 36.16% +36.16%
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Files 0 476 +476
Lines 0 42494 +42494
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+ Hits 0 15369 +15369
- Misses 0 27125 +27125
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KodiaqQ
reviewed
Sep 4, 2023
KodiaqQ
reviewed
Sep 4, 2023
tests/post_training/requirements.txt
Outdated
| @@ -7,7 +7,7 @@ onnx==1.13.1 | |||
| onnxruntime==1.14.1 | |||
| pytest | |||
| pytest-cov | |||
| openvino-dev==2023.0.1 | |||
| openvino-dev==2023.1.0.dev20230811 | |||
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Why was it changed? Do we have any proof that this package is not buggy?
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2023.1.0.dev20230811 have some bug that was fixed on current release branch.
But with 2023.0.1 mo.convert_model does not support quantized models.
Until dump new openvino package it's the best option.
AlexanderDokuchaev
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post_training_quantization/149/ |
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Update e2e test will be done in another PR. |
KodiaqQ
approved these changes
Sep 15, 2023
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post_training_quantization/152 - with dump fp32 models |
alexsu52
reviewed
Sep 18, 2023
| @@ -9,7 +9,7 @@ | |||
| # See the License for the specific language governing permissions and | |||
| # limitations under the License. | |||
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| __version__ = "2.5.0" | |||
| __version__ = "2.6.0" | |||
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@KodiaqQ, I suggest to merge this PR after NNCF 2.6.0 release.
alexsu52
approved these changes
Sep 19, 2023
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Changes
Use mo.convert_model instead of converting via onnx in tests.
nncf.__version__ >= 2.6.0inception_resnet_v2, levit_128, vgg11in test_quantize_conformance.py (120012)Reason for changes
New api in openvino to convert PT models
Related tickets
117885