diff --git a/ai_edge_quantizer/params_generator.py b/ai_edge_quantizer/params_generator.py
index 14cc9ea6..8318d311 100644
--- a/ai_edge_quantizer/params_generator.py
+++ b/ai_edge_quantizer/params_generator.py
@@ -75,12 +75,10 @@ def generate_quantization_parameters(
     if model_qsvs is None:
       model_qsvs = {}
 
-    skip_subgraphs = set()
+    float_subgraphs = set()
     op_codes = self.flatbuffer_model.operatorCodes
     for sg_ind, subgraph in enumerate(self.flatbuffer_model.subgraphs):
-      if sg_ind in skip_subgraphs:
-        continue
-
+      no_quantize_this_subgraph = sg_ind in float_subgraphs
       graph_info = qtyping.GraphInfo(
           subgraph.tensors, self.flatbuffer_model.buffers
       )
@@ -109,14 +107,20 @@ def generate_quantization_parameters(
         algorithm_name, op_quant_config = (
             model_recipe_manager.get_quantization_configs(op_key, op_scope)
         )
-        if policy.is_non_quantizable_composite_op(op):
+        if (
+            policy.is_non_quantizable_composite_op(op)
+            or no_quantize_this_subgraph
+        ):
           algorithm_name = algorithm_manager.AlgorithmName.NO_QUANTIZE
 
         if algorithm_name == algorithm_manager.AlgorithmName.NO_QUANTIZE:
-          side_effect_subgraphs = (
-              tfl_flatbuffer_utils.get_op_side_effect_subgraphs(op)
-          )
-          skip_subgraphs.update(side_effect_subgraphs)
+          # Add side effect subgraphs to the float subgraphs
+          # if the op is not no quantized.
+          if not no_quantize_this_subgraph:
+            side_effect_subgraphs = (
+                tfl_flatbuffer_utils.get_op_side_effect_subgraphs(op)
+            )
+            float_subgraphs.update(side_effect_subgraphs)
 
           op_quant_results = self._get_params_for_no_quant_op(
               subgraph_op_id, op, subgraph.tensors