[TF FE][MOC] Fix leftovers for Keras LSTM fusion transformation (#25268)

**Details:** Fix leftovers for Keras LSTM fusion transformation
#25170

**Tickets:** TBD

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

Author: rkazants

src/common/transformations/src/transformations/op_conversions/convert_ti_to_sequences.cpp

@@ -351,20 +351,10 @@ bool check_condition_true_pattern(const std::shared_ptr<op::v0::Result>& cond_re
     const auto& condition_map = condition_matcher.get_pattern_value_map();
     const auto& cond_const =
         ov::as_type_ptr<op::v0::Constant>(condition_map.at(cond_const_label).get_node_shared_ptr());
-    if (!cond_const) {
+    bool cond_value = false;
+    if (!ov::op::util::get_constant_value(cond_const, cond_value) || !cond_value) {
         return false;
     }
-    if (ov::shape_size(cond_const->get_shape()) != 1)
-        return false;
-    const auto& type = cond_const->get_output_element_type(0);
-    if (type != ov::element::boolean) {
-        return false;
-    }
-    bool cond_value = cond_const->cast_vector<bool>()[0];
-    if (!cond_value) {
-        return false;
-    }
-
     // number of iteration is retrieve from the first input port
     num_iters_output = loop->input_value(0);
 

src/frontends/tensorflow_common/src/helper_transforms/tensor_list_ops_resolver.cpp

@@ -172,7 +172,7 @@ uint64_t get_new_param_idx(const std::vector<uint64_t>& remove_parameter_idxs, u
     for (auto remove_idx : remove_parameter_idxs) {
         FRONT_END_GENERAL_CHECK(old_idx != remove_idx,
                                 "[TensorFlow Frontend] internal error: incorrect old_idx for "
-                                "TensorListSliceInputAndConcatOutputReplacer transformation");
+                                "TensorListInLoopOptimization transformation");
         if (remove_idx < old_idx) {
             ++num_removed;
         }
@@ -181,7 +181,7 @@ uint64_t get_new_param_idx(const std::vector<uint64_t>& remove_parameter_idxs, u
     // compute shifted index
     FRONT_END_GENERAL_CHECK(num_removed <= old_idx,
                             "[TensorFlow Frontend] internal error: incorrect new parameter index computation "
-                            "TensorListSliceInputAndConcatOutputReplacer transformation");
+                            "TensorListInLoopOptimization transformation");
     return old_idx - num_removed;
 }
 }  // namespace
@@ -478,7 +478,7 @@ ov::frontend::tensorflow::pass::TensorListInLoopOptimization::TensorListInLoopOp
                 std::dynamic_pointer_cast<TensorListSetItem>(body_result->get_input_node_shared_ptr(0));
             FRONT_END_GENERAL_CHECK(tensor_list_set_item,
                                     "[TensorFlow Frontend] internal error: tensor_list_set_item is nullptr in "
-                                    "TensorListSliceInputAndConcatOutputReplacer");
+                                    "TensorListInLoopOptimization");
             // unsqueeze newly generated data at this iteration
             // that will be concatenated
             auto new_data = tensor_list_set_item->input_value(2);
@@ -501,13 +501,13 @@ ov::frontend::tensorflow::pass::TensorListInLoopOptimization::TensorListInLoopOp
                 const auto& body_param = body_params[param_idx];
                 FRONT_END_GENERAL_CHECK(body_param->get_output_target_inputs(0).size() == 1,
                                         "[TensorFlow Frontend] internal error: tensor list must have only consumer "
-                                        "TensorListGetItem operation in TensorListSliceInputAndConcatOutputReplacer");
+                                        "TensorListGetItem operation in TensorListInLoopOptimization");
                 auto target_input = *(body_param->get_output_target_inputs(0).begin());
                 auto tensor_list_get_item =
                     std::dynamic_pointer_cast<TensorListGetItem>(target_input.get_node()->shared_from_this());
                 FRONT_END_GENERAL_CHECK(tensor_list_get_item,
                                         "[TensorFlow Frontend] internal error: tensor list must have only consumer "
-                                        "TensorListGetItem operation in TensorListSliceInputAndConcatOutputReplacer");
+                                        "TensorListGetItem operation in TensorListInLoopOptimization");
 
                 auto new_shape = body_param->get_output_partial_shape(0);
                 if (new_shape.rank().is_static() && new_shape.rank().get_length() > 0) {