Refactor type casting in Cython files for improved clarity and consistency

- Updated various Cython files to explicitly cast types, enhancing type safety and readability.
- Adjusted the `engine_name` property in `InferenceEngine` and its subclasses to be set directly in the constructor.
- Modified the `request` method in `_SessionWithBase` to accept `*args` for better flexibility.
- Ensured proper type casting for return values in methods across multiple classes, including `Inference`, `CoreMLEngine`, and `TensorRTEngine`.

These changes aim to streamline the codebase and improve maintainability by enforcing consistent type usage.

engines/coreml_engine.pyx

@@ -28,10 +28,7 @@ cdef class CoreMLEngine(InferenceEngine):
         self.batch_size = 1
 
         constants_inf.log(<str>f'CoreML model: {self.img_width}x{self.img_height}')
-
-    @property
-    def engine_name(self):
-        return "coreml"
+        self.engine_name = <str>"coreml"
 
     @staticmethod
     def get_engine_filename():
@@ -49,10 +46,10 @@ cdef class CoreMLEngine(InferenceEngine):
         raise ValueError("No .mlpackage or .mlmodel found in zip")
 
     cdef tuple get_input_shape(self):
-        return self.img_height, self.img_width
+        return <tuple>(self.img_height, self.img_width)
 
     cdef int get_batch_size(self):
-        return 1
+        return <int>1
 
     cdef run(self, input_data):
         cdef int w = self.img_width