[TF FE] Run HSVToRGB tests on all platforms (openvinotoolkit#27945)

**Details:** Run HSVToRGB tests on all platforms

**Ticket:** TBD

---------

Signed-off-by: Kazantsev, Roman <[email protected]>

tests/layer_tests/tensorflow_tests/test_tf_HSVToRGB.py

@@ -1,32 +1,28 @@
 # Copyright (C) 2018-2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-import platform
-
 import numpy as np
 import pytest
 import tensorflow as tf
 from common.tf_layer_test_class import CommonTFLayerTest
 
+rng = np.random.default_rng(23345)
+
+
 class TestHSVToRGB(CommonTFLayerTest):
     def _prepare_input(self, inputs_info):
         assert 'images:0' in inputs_info
-        if self.special_case == "Black Image":
-            images_shape = inputs_info['images:0']
-            inputs_data = {}
-            inputs_data['images:0'] = np.zeros(images_shape).astype(self.input_type) 
-        elif self.special_case == "Grayscale Image":
-            images_shape = inputs_info['images:0']
-            inputs_data = {}
+        images_shape = inputs_info['images:0']
+        inputs_data = {}
+        if self.special_case == 'Black Image':
+            inputs_data['images:0'] = np.zeros(images_shape).astype(self.input_type)
+        elif self.special_case == 'Grayscale Image':
             inputs_data['images:0'] = np.broadcast_to([0, 0, 0.5], images_shape).astype(self.input_type)
         else:
-            images_shape = inputs_info['images:0']
-            inputs_data = {} 
-            inputs_data['images:0'] = np.random.rand(*images_shape).astype(self.input_type)
-
+            inputs_data['images:0'] = rng.uniform(0.0, 1.0, images_shape).astype(self.input_type)
         return inputs_data
 
-    def create_hsv_to_rgb_net(self, input_shape, input_type, special_case=False):
+    def create_hsv_to_rgb_net(self, input_shape, input_type, special_case):
         self.special_case = special_case
         self.input_type = input_type
         tf.compat.v1.reset_default_graph()
@@ -39,27 +35,16 @@ def create_hsv_to_rgb_net(self, input_shape, input_type, special_case=False):
 
         return tf_net, None
 
-    # Each input is a tensor of with values in [0,1].
-    # The last dimension must be size 3.
-    test_data_basic = [
-        dict(input_shape=[7, 7, 3], input_type=np.float32, special_case="Black Image"),
-        dict(input_shape=[7, 7, 3], input_type=np.float32, special_case="Grayscale Image"),
-        dict(input_shape=[5, 5, 3], input_type=np.float32),
-        dict(input_shape=[5, 23, 27, 3], input_type=np.float64),
-        dict(input_shape=[3, 4, 13, 15, 3], input_type=np.float64),
-    ]
-
-    @pytest.mark.parametrize("params", test_data_basic)
+    @pytest.mark.parametrize('input_shape', [[3], [5, 3], [4, 5, 3], [5, 21, 21, 3]])
+    @pytest.mark.parametrize('input_type', [np.float16, np.float32, np.float64])
+    @pytest.mark.parametrize('special_case', [None, 'Black Image', 'Grayscale Image'])
     @pytest.mark.precommit
     @pytest.mark.nightly
-    @pytest.mark.xfail(condition=platform.system() in ('Darwin', 'Linux') and platform.machine() in ['arm', 'armv7l',
-                                                                                                     'aarch64',
-                                                                                                     'arm64', 'ARM64'],
-                       reason='Ticket - 126314, 132699')
-    def test_hsv_to_rgb_basic(self, params, ie_device, precision, ir_version, temp_dir,
-                                   use_legacy_frontend):
+    def test_hsv_to_rgb_basic(self, input_shape, input_type, special_case,
+                              ie_device, precision, ir_version, temp_dir,
+                              use_legacy_frontend):
         if ie_device == 'GPU':
-            pytest.skip("Accuracy mismatch on GPU")
-        self._test(*self.create_hsv_to_rgb_net(**params),
+            pytest.skip('158898: accuracy issue on GPU')
+        self._test(*self.create_hsv_to_rgb_net(input_shape, input_type, special_case),
                    ie_device, precision, ir_version, temp_dir=temp_dir,
-                   use_legacy_frontend=use_legacy_frontend)
+                   use_legacy_frontend=use_legacy_frontend, custom_eps=3 * 1e-3)