From 05af8d5da15ba90bd435579158eb41f43b5e8a6a Mon Sep 17 00:00:00 2001
From: "codeflash-ai[bot]"
 <148906541+codeflash-ai[bot]@users.noreply.github.com>
Date: Fri, 24 Oct 2025 06:52:40 +0000
Subject: [PATCH] Optimize CompletionTrainingParametersIn.serialize_model

The optimized code achieves a **17% speedup** through several key micro-optimizations that reduce redundant operations in the serialization loop:

**Key optimizations:**

1. **Hoisted expensive lookups**: Moved `self.__pydantic_fields_set__` and `type(self).model_fields` outside the loop to avoid repeated attribute access on each iteration.

2. **Optimized dictionary operations**: Replaced the pattern of `serialized.get(k)` followed by `serialized.pop(k, None)` with a single `serialized.pop(k, None)` call, eliminating one dictionary lookup per field.

3. **Reduced attribute access**: Created local variables (`pydantic_fields_set`, `model_fields`) to minimize dot notation lookups within the hot loop.

4. **Style improvement**: Changed `not k in optional_fields` to `k not in optional_fields` for better readability (though minimal performance impact).

**Why it's faster:**
- Dictionary operations (`get`/`pop`) and attribute access (`self.__pydantic_fields_set__`) are relatively expensive in Python's interpreter
- The loop iterates over 7 fields, so each micro-optimization compounds
- Hoisting invariant computations outside loops is a classic performance optimization

**Test case performance:**
The optimizations show consistent 7-18% improvements across all test scenarios, with particularly strong gains in:
- Large-scale tests with many instances (18.1% faster)
- Tests with all fields set to values (13.5% faster)
- Default/unset field scenarios (10.7% faster)

The optimizations are most effective for workloads that serialize many instances, as the per-instance overhead reduction compounds significantly.
---
 .../models/completiontrainingparametersin.py  | 30 +++++++++++--------
 1 file changed, 17 insertions(+), 13 deletions(-)

diff --git a/src/mistralai/models/completiontrainingparametersin.py b/src/mistralai/models/completiontrainingparametersin.py
index 1f74bb9..1610095 100644
--- a/src/mistralai/models/completiontrainingparametersin.py
+++ b/src/mistralai/models/completiontrainingparametersin.py
@@ -46,7 +46,8 @@ class CompletionTrainingParametersIn(BaseModel):
 
     @model_serializer(mode="wrap")
     def serialize_model(self, handler):
-        optional_fields = [
+        # Use tuple/lists for fastest membership test, all fields are a small, fixed set
+        optional_fields = {
             "training_steps",
             "learning_rate",
             "weight_decay",
@@ -54,36 +55,39 @@ def serialize_model(self, handler):
             "epochs",
             "seq_len",
             "fim_ratio",
-        ]
-        nullable_fields = [
+        }
+        nullable_fields = {
             "training_steps",
             "weight_decay",
             "warmup_fraction",
             "epochs",
             "seq_len",
             "fim_ratio",
-        ]
-        null_default_fields = []
+        }
+        null_default_fields = set()
 
         serialized = handler(self)
 
+        # Precompute fields set and other invariants local to the method for perf
+        pydantic_fields_set = self.__pydantic_fields_set__
+
+        # Micro-optimize reference lookups & minimize attribute access in loop
+        model_fields = type(self).model_fields
         m = {}
 
-        for n, f in type(self).model_fields.items():
+        # Avoid repeatedly calling .get/.pop when iterating: iterate directly on model_fields
+        for n, f in model_fields.items():
             k = f.alias or n
-            val = serialized.get(k)
-            serialized.pop(k, None)
+            # Use pop once, default None if not present
+            val = serialized.pop(k, None)
 
             optional_nullable = k in optional_fields and k in nullable_fields
-            is_set = (
-                self.__pydantic_fields_set__.intersection({n})
-                or k in null_default_fields
-            )  # pylint: disable=no-member
+            is_set = n in pydantic_fields_set or k in null_default_fields  # pylint: disable=no-member
 
             if val is not None and val != UNSET_SENTINEL:
                 m[k] = val
             elif val != UNSET_SENTINEL and (
-                not k in optional_fields or (optional_nullable and is_set)
+                k not in optional_fields or (optional_nullable and is_set)
             ):
                 m[k] = val