From 804c4a2f3fc64b42519dbbe426cd3c6dffb120d3 Mon Sep 17 00:00:00 2001
From: "codeflash-ai[bot]"
 <148906541+codeflash-ai[bot]@users.noreply.github.com>
Date: Wed, 29 Oct 2025 17:32:49 +0000
Subject: [PATCH] Optimize BlockManifest.describe_outputs
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The optimization extracts the `OutputDefinition` list creation from inside the `describe_outputs()` method to a module-level constant `_OUTPUT_DEFINITIONS`. This eliminates redundant object creation on every method call.

**Key Performance Gains:**
- **Object Creation Elimination**: Instead of creating two `OutputDefinition` objects and a list every time `describe_outputs()` is called, these objects are created once at module import time
- **Memory Allocation Reduction**: Avoids repeated memory allocation for the same static data structure
- **Method Call Overhead Reduction**: The method now simply returns a pre-existing list reference instead of constructing objects

**Why This Works:**
In Python, object creation (especially with `__init__` calls) and list construction have overhead. Since the output definitions are static and never change, creating them once at module load time and reusing the same objects is significantly faster.

**Test Case Performance:**
The optimization shows consistent 10-15x speedups across all test cases, with individual calls dropping from ~5μs to ~300-400ns. The most dramatic improvement appears in the large-scale test with 1000 calls (1.62ms → 134μs), demonstrating how the benefit compounds with frequent usage. This pattern is ideal for workflows where `describe_outputs()` is called repeatedly during execution planning or validation phases.
---
 .../models/roboflow/instance_segmentation/v1.py  | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/inference/core/workflows/core_steps/models/roboflow/instance_segmentation/v1.py b/inference/core/workflows/core_steps/models/roboflow/instance_segmentation/v1.py
index 7ff43093b1..ce2ea34006 100644
--- a/inference/core/workflows/core_steps/models/roboflow/instance_segmentation/v1.py
+++ b/inference/core/workflows/core_steps/models/roboflow/instance_segmentation/v1.py
@@ -48,6 +48,14 @@
 )
 from inference_sdk import InferenceConfiguration, InferenceHTTPClient
 
+_OUTPUT_DEFINITIONS = [
+    OutputDefinition(name=INFERENCE_ID_KEY, kind=[STRING_KIND]),
+    OutputDefinition(
+        name="predictions",
+        kind=[INSTANCE_SEGMENTATION_PREDICTION_KIND],
+    ),
+]
+
 LONG_DESCRIPTION = """
 Run inference on an instance segmentation model hosted on or uploaded to Roboflow.
 
@@ -159,13 +167,7 @@ def get_parameters_accepting_batches(cls) -> List[str]:
 
     @classmethod
     def describe_outputs(cls) -> List[OutputDefinition]:
-        return [
-            OutputDefinition(name=INFERENCE_ID_KEY, kind=[STRING_KIND]),
-            OutputDefinition(
-                name="predictions",
-                kind=[INSTANCE_SEGMENTATION_PREDICTION_KIND],
-            ),
-        ]
+        return _OUTPUT_DEFINITIONS
 
     @classmethod
     def get_execution_engine_compatibility(cls) -> Optional[str]: