refactor: calibration for resources and accuracy over same scale range (#710)

src/execute.rs

@@ -826,10 +826,7 @@ pub(crate) fn calibrate(
     let range = if let Some(scales) = scales {
         scales
     } else {
-        match target {
-            CalibrationTarget::Resources { .. } => (8..10).collect::<Vec<crate::Scale>>(),
-            CalibrationTarget::Accuracy => (10..14).collect::<Vec<crate::Scale>>(),
-        }
+        (10..14).collect::<Vec<crate::Scale>>()
     };
 
     let div_rebasing = if let Some(div_rebasing) = div_rebasing {

tests/integration_tests.rs

@@ -560,7 +560,7 @@ mod native_tests {
                 crate::native_tests::setup_py_env();
                 let test_dir = TempDir::new(test).unwrap();
                 let path = test_dir.path().to_str().unwrap(); crate::native_tests::mv_test_(path, test);
-                accuracy_measurement(path, test.to_string(), "private", "private", "public", 1, "resources", 18.0, false);
+                accuracy_measurement(path, test.to_string(), "private", "private", "public", 1, "resources", 3.1, false);
                 test_dir.close().unwrap();
             }
 

tests/python/binding_tests.py

@@ -113,13 +113,13 @@ def test_calibrate_over_user_range():
     data_path = os.path.join(
         examples_path,
         'onnx',
-        '1l_average',
+        '1l_relu',
         'input.json'
     )
     model_path = os.path.join(
         examples_path,
         'onnx',
-        '1l_average',
+        '1l_relu',
         'network.onnx'
     )
     output_path = os.path.join(
@@ -147,13 +147,13 @@ def test_calibrate():
     data_path = os.path.join(
         examples_path,
         'onnx',
-        '1l_average',
+        '1l_relu',
         'input.json'
     )
     model_path = os.path.join(
         examples_path,
         'onnx',
-        '1l_average',
+        '1l_relu',
         'network.onnx'
     )
     output_path = os.path.join(
@@ -183,7 +183,7 @@ def test_model_compile():
     model_path = os.path.join(
         examples_path,
         'onnx',
-        '1l_average',
+        '1l_relu',
         'network.onnx'
     )
     compiled_model_path = os.path.join(
@@ -205,7 +205,7 @@ def test_forward():
     data_path = os.path.join(
         examples_path,
         'onnx',
-        '1l_average',
+        '1l_relu',
         'input.json'
     )
     model_path = os.path.join(