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[TF Hub] Set seed for input data generation and fix integer input data (#19765)

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* [TF Hub] Set seed for input data generation and fix integer input data

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>

* Clean-up workflow

* Update precommit model scope

* Avoid legacy generator

---------

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
This commit is contained in:
Roman Kazantsev 2023-09-13 00:30:39 +04:00 committed by GitHub
parent 9250d17e01
commit d1a8c8f914
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3 changed files with 10 additions and 9 deletions
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2
.github/workflows/linux.yml vendored
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@ -850,8 +850,6 @@ jobs:
- name: TensorFlow Hub Tests - TF FE
run: |
python3 -m pip install openvino --find-links=${{ env.INSTALL_DIR }}/tools
python3 -m pip install -r ${{ env.MODEL_HUB_TESTS_INSTALL_DIR }}/tf_hub_tests/requirements.txt
export PYTHONPATH=${{ env.MODEL_HUB_TESTS_INSTALL_DIR }}:$PYTHONPATH

14
tests/model_hub_tests/models_hub_common/test_convert_model.py
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@ -7,6 +7,10 @@ from models_hub_common.multiprocessing_utils import multiprocessing_run
from openvino import convert_model
from openvino.runtime import Core
# set seed to have deterministic input data generation
# to avoid sporadic issues in inference results
rng = np.random.default_rng(seed=56190)
class TestConvertModel:
infer_timeout = 600
@ -19,15 +23,13 @@ class TestConvertModel:
def prepare_input(self, input_shape, input_type):
if input_type in [np.float32, np.float64]:
return np.random.randint(-2, 2, size=input_shape).astype(input_type)
elif input_type in [np.int8, np.int16, np.int32, np.int64]:
return np.random.randint(-5, 5, size=input_shape).astype(input_type)
elif input_type in [np.uint8, np.uint16]:
return np.random.randint(0, 5, size=input_shape).astype(input_type)
return 2.0 * rng.random(size=input_shape, dtype=input_type)
elif input_type in [np.uint8, np.uint16, np.int8, np.int16, np.int32, np.int64]:
return rng.integers(0, 5, size=input_shape).astype(input_type)
elif input_type in [str]:
return np.broadcast_to("Some string", input_shape)
elif input_type in [bool]:
return np.random.randint(0, 2, size=input_shape).astype(input_type)
return rng.integers(0, 2, size=input_shape).astype(input_type)
else:
assert False, "Unsupported type {}".format(input_type)

3
tests/model_hub_tests/tf_hub_tests/precommit_models
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@ -8,9 +8,10 @@ movenet/multipose/lightning,https://tfhub.dev/google/movenet/multipose/lightning
imagenet/efficientnet_v2_imagenet1k_b0/feature_vector,https://tfhub.dev/google/imagenet/efficientnet_v2_imagenet1k_b0/feature_vector/2?tf-hub-format=compressed
imagenet/mobilenet_v1_100_224/classification,https://tfhub.dev/google/imagenet/mobilenet_v1_100_224/classification/5?tf-hub-format=compressed,skip,119718 - Accuracy issue
magenta/arbitrary-image-stylization-v1-256,https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2?tf-hub-format=compressed
small_bert/bert_en_uncased_L-4_H-256_A-4,https://tfhub.dev/tensorflow/small_bert/bert_en_uncased_L-4_H-256_A-4/2?tf-hub-format=compressed,skip,119718 - Accuracy issue
# secure notebook models
unet/industrial/class_1,https://tfhub.dev/nvidia/unet/industrial/class_1/1?tf-hub-format=compressed
movenet/singlepose/thunder,https://tfhub.dev/google/movenet/singlepose/thunder/4?tf-hub-format=compressed
esrgan-tf2,https://tfhub.dev/captain-pool/esrgan-tf2/1?tf-hub-format=compressed
film,https://tfhub.dev/google/film/1?tf-hub-format=compressed,skip,119907 - incorrect test data
film,https://tfhub.dev/google/film/1?tf-hub-format=compressed,skip,119718 - Accuracy issue
planet/vision/classifier/planet_v2,https://tfhub.dev/google/planet/vision/classifier/planet_v2/1?tf-hub-format=compressed