ultralytics 8.3.53 New Export argument validation (#18185)

Signed-off-by: Mohammed Yasin <32206511+Y-T-G@users.noreply.github.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docs/en/reference/engine/exporter.md

@@ -23,6 +23,10 @@ keywords: YOLOv8, export formats, ONNX, TensorRT, CoreML, machine learning model
 
 <br><br><hr><br>
 
+## ::: ultralytics.engine.exporter.validate_args
+
+<br><br><hr><br>
+
 ## ::: ultralytics.engine.exporter.gd_outputs
 
 <br><br><hr><br>

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = "8.3.52"
+__version__ = "8.3.53"
 
 import os
 

ultralytics/engine/exporter.py

@@ -101,23 +101,47 @@ from ultralytics.utils.torch_utils import TORCH_1_13, get_latest_opset, select_d
 def export_formats():
     """Ultralytics YOLO export formats."""
     x = [
-        ["PyTorch", "-", ".pt", True, True],
+        ["PyTorch", "-", ".pt", True, True, []],
-        ["TorchScript", "torchscript", ".torchscript", True, True],
+        ["TorchScript", "torchscript", ".torchscript", True, True, ["optimize", "batch"]],
-        ["ONNX", "onnx", ".onnx", True, True],
+        ["ONNX", "onnx", ".onnx", True, True, ["half", "dynamic", "simplify", "opset", "batch"]],
-        ["OpenVINO", "openvino", "_openvino_model", True, False],
+        ["OpenVINO", "openvino", "_openvino_model", True, False, ["half", "int8", "batch"]],
-        ["TensorRT", "engine", ".engine", False, True],
+        ["TensorRT", "engine", ".engine", False, True, ["half", "dynamic", "simplify", "int8", "batch"]],
-        ["CoreML", "coreml", ".mlpackage", True, False],
+        ["CoreML", "coreml", ".mlpackage", True, False, ["half", "int8", "nms", "batch"]],
-        ["TensorFlow SavedModel", "saved_model", "_saved_model", True, True],
+        ["TensorFlow SavedModel", "saved_model", "_saved_model", True, True, ["keras", "int8", "batch"]],
-        ["TensorFlow GraphDef", "pb", ".pb", True, True],
+        ["TensorFlow GraphDef", "pb", ".pb", True, True, ["batch"]],
-        ["TensorFlow Lite", "tflite", ".tflite", True, False],
+        ["TensorFlow Lite", "tflite", ".tflite", True, False, ["half", "int8", "batch"]],
-        ["TensorFlow Edge TPU", "edgetpu", "_edgetpu.tflite", True, False],
+        ["TensorFlow Edge TPU", "edgetpu", "_edgetpu.tflite", True, False, []],
-        ["TensorFlow.js", "tfjs", "_web_model", True, False],
+        ["TensorFlow.js", "tfjs", "_web_model", True, False, ["half", "int8", "batch"]],
-        ["PaddlePaddle", "paddle", "_paddle_model", True, True],
+        ["PaddlePaddle", "paddle", "_paddle_model", True, True, ["batch"]],
-        ["MNN", "mnn", ".mnn", True, True],
+        ["MNN", "mnn", ".mnn", True, True, ["batch", "int8", "half"]],
-        ["NCNN", "ncnn", "_ncnn_model", True, True],
+        ["NCNN", "ncnn", "_ncnn_model", True, True, ["half", "batch"]],
-        ["IMX", "imx", "_imx_model", True, True],
+        ["IMX", "imx", "_imx_model", True, True, ["int8"]],
     ]
-    return dict(zip(["Format", "Argument", "Suffix", "CPU", "GPU"], zip(*x)))
+    return dict(zip(["Format", "Argument", "Suffix", "CPU", "GPU", "Arguments"], zip(*x)))
+
+
+def validate_args(format, passed_args, valid_args):
+    """
+    Validates arguments based on format.
+
+    Args:
+        format (str): The export format.
+        passed_args (Namespace): The arguments used during export.
+        valid_args (dict): List of valid arguments for the format.
+
+    Raises:
+        AssertionError: If an argument that's not supported by the export format is used, or if format doesn't have the supported arguments listed.
+    """
+    # Only check valid usage of these args
+    export_args = ["half", "int8", "dynamic", "keras", "nms", "batch"]
+
+    assert valid_args is not None, f"ERROR ❌️ valid arguments for '{format}' not listed."
+    custom = {"batch": 1, "data": None, "device": None}  # exporter defaults
+    default_args = get_cfg(DEFAULT_CFG, custom)
+    for arg in export_args:
+        not_default = getattr(passed_args, arg, None) != getattr(default_args, arg, None)
+        if not_default:
+            assert arg in valid_args, f"ERROR ❌️ argument '{arg}' is not supported for format='{format}'"
 
 
 def gd_outputs(gd):
@@ -182,7 +206,8 @@ class Exporter:
             fmt = "engine"
         if fmt in {"mlmodel", "mlpackage", "mlprogram", "apple", "ios", "coreml"}:  # 'coreml' aliases
             fmt = "coreml"
-        fmts = tuple(export_formats()["Argument"][1:])  # available export formats
+        fmts_dict = export_formats()
+        fmts = tuple(fmts_dict["Argument"][1:])  # available export formats
         if fmt not in fmts:
             import difflib
 
@@ -224,7 +249,8 @@ class Exporter:
             assert dla in {"0", "1"}, f"Expected self.args.device='dla:0' or 'dla:1, but got {self.args.device}."
         self.device = select_device("cpu" if self.args.device is None else self.args.device)
 
-        # Checks
+        # Argument compatibility checks
+        validate_args(fmt, self.args, fmts_dict["Arguments"][flags.index(True) + 1])
         if imx and not self.args.int8:
             LOGGER.warning("WARNING ⚠️ IMX only supports int8 export, setting int8=True.")
             self.args.int8 = True

ultralytics/utils/benchmarks.py

@@ -90,7 +90,7 @@ def benchmark(
 
     y = []
     t0 = time.time()
-    for i, (name, format, suffix, cpu, gpu) in enumerate(zip(*export_formats().values())):
+    for i, (name, format, suffix, cpu, gpu, _) in enumerate(zip(*export_formats().values())):
         emoji, filename = "❌", None  # export defaults
         try:
             # Checks