Remove warning from examples (#3023)

### Changes Add `subset_size` to PTQ samples after merging #2995 to remove the warning message CI: https://github.com/openvinotoolkit/nncf/actions/runs/11436915496
openvinotoolkit · Oct 21, 2024 · d33ce2f · d33ce2f
1 parent 7c94b23
commit d33ce2f
Show file tree

Hide file tree

Showing 5 changed files with 5 additions and 1 deletion.
diff --git a/examples/post_training_quantization/onnx/yolov8_quantize_with_accuracy_control/main.py b/examples/post_training_quantization/onnx/yolov8_quantize_with_accuracy_control/main.py
@@ -190,6 +190,7 @@ def validation_ac(
         model,
         quantization_dataset,
         quantization_dataset,
+        subset_size=len(data_loader),
         validation_fn=validation_fn,
         max_drop=0.003,
         preset=nncf.QuantizationPreset.MIXED,

diff --git a/.../post_training_quantization/openvino/anomaly_stfpm_quantize_with_accuracy_control/main.py b/.../post_training_quantization/openvino/anomaly_stfpm_quantize_with_accuracy_control/main.py
@@ -159,6 +159,7 @@ def transform_fn(data_item):
     ov_quantized_model = nncf.quantize_with_accuracy_control(
         model=ov_model,
         calibration_dataset=calibration_dataset,
+        subset_size=len(anomaly_images),
         validation_dataset=validation_dataset,
         validation_fn=validation_fn,
         max_drop=max_accuracy_drop,

diff --git a/examples/post_training_quantization/openvino/yolov8/main.py b/examples/post_training_quantization/openvino/yolov8/main.py
@@ -120,6 +120,7 @@ def transform_fn(data_item: Dict):
     quantized_model = nncf.quantize(
         model,
         quantization_dataset,
+        subset_size=len(data_loader),
         preset=nncf.QuantizationPreset.MIXED,
         ignored_scope=nncf.IgnoredScope(
             types=["Multiply", "Subtract", "Sigmoid"],

diff --git a/examples/post_training_quantization/openvino/yolov8_quantize_with_accuracy_control/main.py b/examples/post_training_quantization/openvino/yolov8_quantize_with_accuracy_control/main.py
@@ -183,6 +183,7 @@ def validation_ac(
         model,
         quantization_dataset,
         quantization_dataset,
+        subset_size=len(data_loader),
         validation_fn=validation_fn,
         max_drop=0.003,
         preset=nncf.QuantizationPreset.MIXED,

diff --git a/examples/post_training_quantization/torch/ssd300_vgg16/main.py b/examples/post_training_quantization/torch/ssd300_vgg16/main.py
@@ -152,7 +152,7 @@ def main():
 
     # Quantize model
     calibration_dataset = nncf.Dataset(dataset, partial(transform_fn, device=device))
-    quantized_model = nncf.quantize(model, calibration_dataset)
+    quantized_model = nncf.quantize(model, calibration_dataset, subset_size=len(dataset))
 
     # Convert to OpenVINO
     dummy_input = torch.randn(1, 3, 480, 480)