[TF FE] Fix centernet and correct FloorDiv translator for signed integer type (openvinotoolkit#22684)

### Details:
- Centernet's topk operation returns large int32 values (greater than
1000000), even though they are integer `FloorDiv`/`Div(inp_1, inp_2) +
Floor` operation is performed in float16 and because of that it causes
accuracy problems.

- To solve this need to performs FloorDiv operation in integer with a
subgraph:
```
res = x / y; if x > 0 and y > 0
res = x / y - 1; if (x < 0 xor y < 0) and (x mod y != 0)
```
 - checked on separate bus: no degradations caused.

### Tickets:
 - CVS-130526

---------

Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com>

Author: pavel-esir

src/frontends/tensorflow_common/src/op/binary_op.cpp

@@ -8,6 +8,7 @@
 #include "openvino/op/bitwise_and.hpp"
 #include "openvino/op/bitwise_or.hpp"
 #include "openvino/op/bitwise_xor.hpp"
+#include "openvino/op/ceiling.hpp"
 #include "openvino/op/concat.hpp"
 #include "openvino/op/convert.hpp"
 #include "openvino/op/divide.hpp"
@@ -26,9 +27,11 @@
 #include "openvino/op/minimum.hpp"
 #include "openvino/op/mod.hpp"
 #include "openvino/op/multiply.hpp"
+#include "openvino/op/negative.hpp"
 #include "openvino/op/not_equal.hpp"
 #include "openvino/op/power.hpp"
 #include "openvino/op/prelu.hpp"
+#include "openvino/op/select.hpp"
 #include "openvino/op/squared_difference.hpp"
 #include "openvino/op/subtract.hpp"
 #include "openvino/op/unsqueeze.hpp"
@@ -54,11 +57,27 @@ OutputVector translate_binary_op(const NodeContext& node,
 OutputVector translate_floor_div_op(const NodeContext& node) {
     auto floordiv_fn = [](const Output<Node>& x, const Output<Node>& y) -> shared_ptr<Node> {
         auto out_type = x.get_element_type();
-        if (out_type.is_integral()) {
-            auto float_x = make_shared<v0::Convert>(x, element::f32);
-            auto float_y = make_shared<v0::Convert>(y, element::f32);
-            return make_shared<v0::Convert>(make_shared<v0::Floor>(make_shared<v1::Divide>(float_x, float_y)),
-                                            out_type);
+        if (out_type.is_integral() && out_type.is_signed()) {
+            // when integer inputs have different signs remainder should be taken into account
+            // res = x / y; if x > 0 and y > 0
+            // res = x / y - 1; if (x < 0 xor y < 0) and (x mod y != 0)
+
+            auto zero_const = make_shared<v0::Constant>(out_type, Shape{}, 0);
+            auto minus_one_const = make_shared<v0::Constant>(out_type, Shape{}, -1);
+
+            auto x_less_cond = make_shared<v1::Less>(x, zero_const);
+            auto y_less_cond = make_shared<v1::Less>(y, zero_const);
+            auto xor_cond = make_shared<v1::LogicalXor>(x_less_cond, y_less_cond);
+
+            auto div = make_shared<v1::Divide>(x, y, false);
+            auto mod_xy = make_shared<v1::Mod>(x, y);
+            auto cond_mod = make_shared<v1::NotEqual>(mod_xy, zero_const);
+
+            auto cond = make_shared<v1::LogicalAnd>(cond_mod, xor_cond);
+            auto reminder = make_shared<v1::Select>(cond, minus_one_const, zero_const);
+            return make_shared<v1::Add>(div, reminder);
+        } else if (out_type.is_integral() && !out_type.is_signed()) {
+            return make_shared<v1::Divide>(x, y);
         } else {
             return make_shared<v0::Floor>(make_shared<v1::Divide>(x, y));
         }

tests/layer_tests/common/utils/common_utils.py

@@ -53,7 +53,7 @@ def generate_ir_python_api(coverage=False, **kwargs):
 
     out_dir = kwargs['output_dir'] + os.sep + kwargs['model_name'] + ".xml"
 
-    # TODO: Remove usage of legacy params from layer tests and switch to convert_model from tools.ovc
+    # TODO: CVS-132151 Remove usage of legacy params from layer tests and switch to convert_model from tools.ovc
     ov_model = convert_model(**kwargs)
     serialize(ov_model, out_dir)
 

tests/layer_tests/tensorflow_tests/test_tf_Div.py

@@ -36,7 +36,7 @@ def create_div_net(self, input_shape, input_type):
         dict(input_shape=[10, 20], input_type=np.float32),
         dict(input_shape=[2, 3, 4], input_type=np.float32),
         pytest.param(dict(input_shape=[8, 5], input_type=np.int32),
-                              marks=pytest.mark.xfail(reason='Ticket TBD - Divide inconsistent behavior on different systems')),
+                              marks=pytest.mark.xfail(reason='Ticket CVS-132377 - Divide inconsistent behavior on different systems')),
         dict(input_shape=[], input_type=np.float32),
     ]
 
@@ -47,4 +47,4 @@ def test_div_basic(self, params, ie_device, precision, ir_version, temp_dir,
                        use_new_frontend):
         self._test(*self.create_div_net(**params),
                    ie_device, precision, ir_version, temp_dir=temp_dir,
-                   use_new_frontend=use_new_frontend)
+                   use_new_frontend=use_new_frontend)

tests/layer_tests/tensorflow_tests/test_tf_FloorDiv.py

@@ -3,23 +3,26 @@
 
 import numpy as np
 import pytest
+import platform
 
 from common.tf_layer_test_class import CommonTFLayerTest
-from common.utils.tf_utils import permute_nchw_to_nhwc
 
+rng = np.random.default_rng()
+
+def list_arm_platforms():
+    return ['arm', 'armv7l', 'aarch64', 'arm64', 'ARM64']
 
 class TestFloorDiv(CommonTFLayerTest):
     def create_add_placeholder_const_net(self, x_shape, dtype, ir_version, use_new_frontend):
         import tensorflow as tf
-
+        self.dtype = dtype
         tf.compat.v1.reset_default_graph()
 
         # Create the graph and model
         with tf.compat.v1.Session() as sess:
             x = tf.compat.v1.placeholder(dtype, x_shape, 'Input')
             constant_value = np.array(-10).astype(dtype)
             y = tf.constant(constant_value)
-            x = tf.raw_ops.Abs(x=x)
             res = tf.raw_ops.FloorDiv(x=x, y=y)
 
             tf.compat.v1.global_variables_initializer()
@@ -29,12 +32,28 @@ def create_add_placeholder_const_net(self, x_shape, dtype, ir_version, use_new_f
 
         return tf_net, ref_net
 
+    def _prepare_input(self, inputs_info):
+        tensor_name = list(inputs_info.keys())[0]
+        x_shape = inputs_info[tensor_name]
+        inputs_data = {}
+        if np.issubdtype(self.dtype, np.floating):
+            inputs_data[tensor_name] = rng.uniform(-5.0, 5.0, x_shape).astype(self.dtype)
+        elif np.issubdtype(self.dtype, np.signedinteger):
+            inputs_data[tensor_name] = rng.integers(-8, 8, x_shape).astype(self.dtype)
+        else:
+            inputs_data[tensor_name] = rng.integers(0, 8, x_shape).astype(self.dtype)
+        return inputs_data
+
     # TODO: implement tests for 2 Consts + Add
 
+    
     test_data_1D = [
         dict(x_shape=[], dtype=np.int32),
         dict(x_shape=[2], dtype=np.int64),
         dict(x_shape=[2, 4, 5], dtype=np.int32),
+        dict(x_shape=[2, 4, 5], dtype=np.uint32),
+        dict(x_shape=[2, 4, 5], dtype=np.uint64),
+
         dict(x_shape=[], dtype=np.float32),
         dict(x_shape=[2], dtype=np.float64),
         dict(x_shape=[2, 4, 5], dtype=np.float32),
@@ -45,7 +64,66 @@ def create_add_placeholder_const_net(self, x_shape, dtype, ir_version, use_new_f
     @pytest.mark.precommit_tf_fe
     def test_add_placeholder_const_1D(self, params, ie_device, precision, ir_version, temp_dir,
                                       use_new_frontend):
+        if platform.system() == 'Linux' and platform.machine() in list_arm_platforms() and np.issubdtype(params['dtype'], np.signedinteger):
+            pytest.xfail(reason='Ticket CVS-132377 - Divide inconsistent behavior on different systems')
+
         self._test(*self.create_add_placeholder_const_net(**params, ir_version=ir_version,
                                                           use_new_frontend=use_new_frontend),
                    ie_device, precision, ir_version, temp_dir=temp_dir,
                    use_new_frontend=use_new_frontend)
+
+
+class TestFloorDivStaticInput(CommonTFLayerTest):
+    min = -100
+    max = 200
+    step = 1
+    dtype = np.int32
+
+    def create_flordiv_tf_net(self, min, max, step, y, dtype, ir_version, use_new_frontend):
+        import tensorflow as tf
+        x = np.arange(min, max, step, dtype=dtype)
+        
+        self.min = min
+        self.max = max
+        self.step = step
+        self.dtype = dtype
+
+        tf.compat.v1.reset_default_graph()
+
+        with tf.compat.v1.Session() as sess:
+            x = tf.compat.v1.placeholder(dtype, x.shape, 'Input')
+            y = tf.constant(np.array(y).astype(dtype))
+            res = tf.raw_ops.FloorDiv(x=x, y=y)
+
+            tf.compat.v1.global_variables_initializer()
+            tf_net = sess.graph_def
+
+        ref_net = None
+
+        return tf_net, ref_net
+    
+    def _prepare_input(self, inputs_dict):
+        for input in inputs_dict.keys():
+            inputs_dict[input] = np.arange(self.min, self.max, self.step, dtype=self.dtype)
+        return inputs_dict
+
+    test_inputs = [
+        dict(min=-20, max=20, step=1, y=[10]),
+        dict(min=-20, max=20, step=1, y=[5]),
+        dict(min=-20, max=20, step=1, y=[6]),
+        dict(min=-20, max=20, step=1, y=[-5]),
+        dict(min=-20, max=20, step=1, y=[-6]),
+        dict(min=-1e5, max=1e5, step=100, y=[1e5]),
+    ]
+    @pytest.mark.parametrize("params", test_inputs)
+    @pytest.mark.parametrize("dtype", [np.int32, np.int64])
+    @pytest.mark.nightly
+    @pytest.mark.precommit_tf_fe
+    @pytest.mark.xfail(condition=platform.system() == 'Linux' and platform.machine() in list_arm_platforms(),
+                       reason='Ticket CVS-132377 - Divide inconsistent behavior on different systems')
+    def test_floordiv(self, params, dtype, ie_device, precision, ir_version, temp_dir,
+                                      use_new_frontend):
+        self._test(*self.create_flordiv_tf_net(**params, dtype=dtype, ir_version=ir_version,
+                                                          use_new_frontend=use_new_frontend),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                    use_new_frontend=use_new_frontend)