[onert/python] Add documentation for inference_benchmark.py sample

runtime/onert/sample/minimal-python/inference_benchmark.md

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+# inference_benchmark.py — Inference Performance & Memory Benchmark
+
+This sample measures end-to-end inference latency and RSS memory usage for an ONERT model, with optional static input shapes.
+
+## Purpose
+
+- Load an NNFW package
+- (Optionally) override input shapes
+- Perform warm-up and measured inference runs
+- Report:
+  - Prepare / I/O / execution latency (ms)
+  - RSS memory delta (KB) for model load, prepare, execute, and peak
+
+## Usage
+
+```bash
+python inference_benchmark.py <nnpackage_path> [--backends BACKENDS] [--input-shape SHAPES …] [--repeat N]
+```
+
+| Argument           | Description                                                                      |
+| ------------------ | -------------------------------------------------------------------------------- |
+| `<nnpackage_path>` | Path to your `.nnpackage` directory or model file                                |
+| `--backends`       | Backend to use (e.g. `cpu`, `gpu`). Default: `cpu`                                |
+| `--input-shape`    | One or more comma-separated shape strings, e.g. `1,224,224,3 1,10`                 |
+| `--repeat`         | Number of timed inference repetitions (after 3 warm-up runs). Default: `5`        |
+
+## Example
+```bash
+# Measure on CPU with default shapes, 5 repeats
+python inference_benchmark.py /path/to/model.nnpackage
+
+# Measure on GPU with two inputs: [1,224,224,3] and [1,10], 10 repeats
+python inference_benchmark.py /path/to/model.nnpackage \
+  --backends gpu \
+  --input-shape 1,224,224,3 1,10 \
+  --repeat 10
+```
+
+## What It Does
+
+1. Warm-up
+Runs `infer()` 3 times (results discarded) to stabilize performance metrics.
+
+2. Benchmark
+Runs `infer()` N times, accumulating:
+   - I/O time (`io_time_ms`)
+   - Run time (`run_time_ms`)
+
+3. Memory Measurement
+Uses `psutil` to sample `RSS` before model load, after prepare, and after execution.
+
+4. Reporting
+Prints latency statistics and memory deltas:
+```
+======= Inference Benchmark =======
+- Warmup runs   : 3
+- Measured runs : 5
+- Prepare       : 12.345 ms
+- Avg I/O       :  0.123 ms
+- Avg Run       :  1.234 ms
+===================================
+RSS
+- MODEL_LOAD    : 15000 KB
+- PREPARE       : 30000 KB
+- EXECUTE       : 32000 KB
+- PEAK          : 32000 KB
+===================================
+```