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

* [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>

.github/workflows/linux.yml

@@ -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

tests/model_hub_tests/models_hub_common/test_convert_model.py

@@ -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)
+            return 2.0 * rng.random(size=input_shape, dtype=input_type)
-        elif input_type in [np.int8, np.int16, np.int32, np.int64]:
+        elif input_type in [np.uint8, np.uint16, np.int8, np.int16, np.int32, np.int64]:
-            return np.random.randint(-5, 5, size=input_shape).astype(input_type)
+            return rng.integers(0, 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)
         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)
 

tests/model_hub_tests/tf_hub_tests/precommit_models

@@ -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