[TF FE] Stabilize binary comparison ops (Equal, NonEqual, Less, etc.)…

… tests on all platforms (openvinotoolkit#26205)

**Details:** Stabilize binary comparison ops (Equal, NonEqual, Less,
etc.) tests on all platforms

**Ticket:** 145795

---------

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

tests/layer_tests/tensorflow_tests/test_tf_BinaryComparison.py

@@ -0,0 +1,96 @@
+# Copyright (C) 2018-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import pytest
+import tensorflow as tf
+from common.tf_layer_test_class import CommonTFLayerTest
+from common.utils.tf_utils import mix_array_with_several_values
+
+rng = np.random.default_rng(23356)
+
+
+class TestBinaryComparison(CommonTFLayerTest):
+    def _generate_value(self, input_shape, input_type):
+        if np.issubdtype(input_type, np.floating):
+            gen_value = rng.uniform(-5.0, 5.0, input_shape).astype(input_type)
+        elif np.issubdtype(input_type, np.signedinteger):
+            gen_value = rng.integers(-8, 8, input_shape).astype(input_type)
+        else:
+            gen_value = rng.integers(8, 16, input_shape).astype(input_type)
+        return gen_value
+
+    def _prepare_input(self, inputs_info):
+        assert 'x:0' in inputs_info, "Test error: inputs_info must contain `x`"
+        x_shape = inputs_info['x:0']
+        input_type = self.input_type
+
+        inputs_data = {}
+        y_value = None
+        if self.is_const:
+            y_value = self.y_value
+            y_shape = y_value.shape
+        else:
+            assert 'y:0' in inputs_info, "Test error: inputs_info must contain `y`"
+            y_shape = inputs_info['y:0']
+            y_value = self._generate_value(y_shape, input_type)
+            inputs_data['y:0'] = y_value
+
+        # generate x value so that some elements will be equal, less, greater than y value element-wise
+        squeeze_dims = 0 if len(y_shape) <= len(x_shape) else len(y_shape) - len(x_shape)
+        zeros_list = [0] * squeeze_dims
+        y_value = y_value[tuple(zeros_list)]
+        y_value_minus_one = y_value - 1
+        y_value_plus_one = y_value + 1
+
+        x_value = self._generate_value(x_shape, input_type)
+        # mix input data with preferable values
+        x_value = mix_array_with_several_values(x_value, [y_value, y_value_plus_one, y_value_minus_one], rng)
+        inputs_data['x:0'] = x_value
+
+        return inputs_data
+
+    def create_binary_comparison_net(self, input_shape1, input_shape2, binary_op, is_const, input_type):
+        compare_ops_map = {
+            'Equal': tf.raw_ops.Equal,
+            'NotEqual': tf.raw_ops.NotEqual,
+            'Greater': tf.raw_ops.Greater,
+            'GreaterEqual': tf.raw_ops.GreaterEqual,
+            'Less': tf.raw_ops.Less,
+            'LessEqual': tf.raw_ops.LessEqual,
+        }
+
+        self.input_type = input_type
+        self.is_const = is_const
+        tf.compat.v1.reset_default_graph()
+        # Create the graph and model
+        with tf.compat.v1.Session() as sess:
+            x = tf.compat.v1.placeholder(input_type, input_shape1, 'x')
+            y = tf.compat.v1.placeholder(input_type, input_shape2, 'y')
+            if is_const:
+                self.y_value = self._generate_value(input_shape2, input_type)
+                y = tf.constant(self.y_value, dtype=input_type)
+            compare_ops_map[binary_op](x=x, y=y)
+            tf.compat.v1.global_variables_initializer()
+
+            tf_net = sess.graph_def
+
+        return tf_net, None
+
+    @pytest.mark.parametrize('input_shape1', [[], [4], [3, 4], [2, 3, 4]])
+    @pytest.mark.parametrize('input_shape2', [[4], [3, 4]])
+    @pytest.mark.parametrize('binary_op', ['Equal', 'NotEqual', 'Greater', 'GreaterEqual', 'Less', 'LessEqual'])
+    @pytest.mark.parametrize('is_const', [False, True])
+    @pytest.mark.parametrize('input_type', [np.int8, np.uint8, np.int16,
+                                            np.int32, np.int64,
+                                            np.float16, np.float32, np.float64])
+    @pytest.mark.precommit
+    @pytest.mark.nightly
+    def test_binary_comparison(self, input_shape1, input_shape2, binary_op, is_const, input_type,
+                               ie_device, precision, ir_version, temp_dir,
+                               use_legacy_frontend):
+        if ie_device == 'GPU' and input_type == np.int16 and is_const:
+            pytest.skip('150501: Accuracy error on GPU for int16 type and constant operand')
+        self._test(*self.create_binary_comparison_net(input_shape1, input_shape2, binary_op, is_const, input_type),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_legacy_frontend=use_legacy_frontend)

tests/layer_tests/tensorflow_tests/test_tf_BinaryOps.py

@@ -53,13 +53,7 @@ def create_add_placeholder_const_net(self, x_shape, y_shape, op_type):
             'Pow': tf.raw_ops.Pow,
             'Maximum': tf.raw_ops.Maximum,
             'Minimum': tf.raw_ops.Minimum,
-            'Equal': tf.raw_ops.Equal,
-            'NotEqual': tf.raw_ops.NotEqual,
             'Mod': tf.raw_ops.Mod,
-            'Greater': tf.raw_ops.Greater,
-            'GreaterEqual': tf.raw_ops.GreaterEqual,
-            'Less': tf.raw_ops.Less,
-            'LessEqual': tf.raw_ops.LessEqual,
             'LogicalAnd': tf.raw_ops.LogicalAnd,
             'LogicalOr': tf.raw_ops.LogicalOr,
             'FloorMod': tf.raw_ops.FloorMod,
@@ -95,8 +89,8 @@ def create_add_placeholder_const_net(self, x_shape, y_shape, op_type):
     @pytest.mark.parametrize('y_shape', [[4], [2, 3, 4]])
     @pytest.mark.parametrize("op_type",
                              ['Add', 'AddV2', 'Sub', 'Mul', 'Div', 'RealDiv', 'SquaredDifference', 'Pow',
-                              'Maximum', 'Minimum', 'Equal', 'NotEqual', 'Mod', 'Greater', 'GreaterEqual', 'Less',
-                              'LessEqual', 'LogicalAnd', 'LogicalOr', 'FloorMod', 'FloorDiv', 'Xdivy'])
+                              'Maximum', 'Minimum', 'Mod', 'LogicalAnd', 'LogicalOr', 'FloorMod',
+                              'FloorDiv', 'Xdivy'])
     @pytest.mark.nightly
     @pytest.mark.precommit
     @pytest.mark.xfail(condition=platform.system() == 'Darwin' and platform.machine() == 'arm64',
@@ -109,8 +103,5 @@ def test_binary_op(self, x_shape, y_shape, ie_device, precision, ir_version, tem
             pytest.skip("For Mod and Pow GPU has inference mismatch")
         if op_type in ['Mod', 'FloorDiv', 'FloorMod']:
             pytest.skip("Inference mismatch for Mod and FloorDiv")
-        if ie_device == 'GPU' and precision == 'FP16' and op_type in ['Equal', 'NotEqual', 'Greater', 'GreaterEqual',
-                                                                      'Less', 'LessEqual']:
-            pytest.skip("Accuracy mismatch on GPU")
         self._test(*self.create_add_placeholder_const_net(x_shape=x_shape, y_shape=y_shape, op_type=op_type), ie_device,
                    precision, ir_version, temp_dir=temp_dir, use_legacy_frontend=use_legacy_frontend)