NXP backend: Move optimization in keep_one_empty_buffer.py to Model builder (#14163)

### Summary
Move optimization in keep_one_empty_buffer.py to IR Model builder. This
functionality is not an optimization, but a required housekeeping step to 
build a valid IR model for Neutron Converter.

### Test plan
All tests where a subgraph is delegated to Neutron.

Author: roman-janik-nxp

backends/nxp/backend/ir/converter/builder/model_builder.py

@@ -412,6 +412,26 @@ def _make_outputs_channels_first(self):
 
         self.get_sub_graph().outputs.tmp_outputs = new_outputs
 
+    def _keep_one_empty_buffer(self):
+        """Create a single empty `Buffer` object and assign it to all tensors in the model that don't have static data."""
+        empty_buffer = self.get_first_empty_buffer()
+
+        for t in self.get_tensors().vector:
+            if tensor_has_data(t):
+                # The buffer of `t` is not empty.
+                continue
+
+            if t.tmp_buffer == empty_buffer:
+                # Already optimized.
+                continue
+
+            if t.is_variable:
+                # The data of the tensor will change at runtime, so it shouldn't share the buffer with other tensors.
+                continue
+
+            # It's safe to replace the buffer.
+            t.tmp_buffer = empty_buffer
+
     def finish(self) -> tflite_model.Model:
         """Finalize and optimize the converted TFLite model. Then return it.
 
@@ -430,6 +450,8 @@ def finish(self) -> tflite_model.Model:
             self.conversion_config.optimization_blacklist,
         )
 
+        self._keep_one_empty_buffer()
+
         # Remove outputs, which are not produced by any node. Otherwise, there would be errors after inference.
         operator_outputs = []
         for op in self.get_operators().vector:

backends/nxp/backend/ir/tflite_optimizer/optimizations/keep_one_empty_buffer.py

@@ -20,9 +20,6 @@
 from executorch.backends.nxp.backend.ir.tflite_optimizer.optimizations.fuse_fully_connected_and_add_operators import (
     FuseFullyConnectedAndAddOperators,
 )
-from executorch.backends.nxp.backend.ir.tflite_optimizer.optimizations.keep_one_empty_buffer import (
-    KeepOneEmptyBuffer,
-)
 from executorch.backends.nxp.backend.ir.tflite_optimizer.optimizations.move_relu_before_concat import (
     MoveActivationBeforeConcatenation,
 )
@@ -36,7 +33,6 @@
 
 
 class Optimization(Enum):
-    KEEP_ONE_EMPTY_BUFFER = 0
     FUSE_ACTIVATION_FUNCTIONS = 1
     FUSE_FULLY_CONNECTED_AND_ADD = 2
 
@@ -76,9 +72,6 @@ def __init__(
         self._builder = builder
 
         self.optimization_map = {
-            Optimization.KEEP_ONE_EMPTY_BUFFER: KeepOneEmptyBuffer(
-                builder, conversion_config
-            ),
             Optimization.FUSE_ACTIVATION_FUNCTIONS: FuseActivationFunctions(
                 builder, conversion_config
             ),