[test] Use Python development module with warnings as errors for testing

bindings/pyroot/pythonizations/test/generate_keras_functional.py

@@ -1,3 +1,5 @@
+import warnings
+
 def generate_keras_functional(dst_dir):
 
     import numpy as np
@@ -16,8 +18,18 @@
 
         model.compile(optimizer='adam', loss='mean_squared_error', metrics=['mae'])
         model.summary()
-        model.fit(x_train, y_train, epochs=1, verbose=0)
-        model.save(f"{dst_dir}/Functional_{name}_test.keras")
+        if len(model.trainable_weights) > 0:
+            model.fit(x_train, y_train, epochs=1, verbose=0)
+
+        with warnings.catch_warnings():
+            # Some object inside TensorFlow/Keras has an outdated __array__ implementation
+            warnings.filterwarnings(
+                "ignore",
+                category=DeprecationWarning,
+                message=".*__array__.*copy keyword.*"
+            )
+            model.save(f"{dst_dir}/Functional_{name}_test.keras")
+
         print("generated and saved functional model",name)
 
 
@@ -211,7 +223,7 @@
     sub = layers.Subtract()([d1, d2])
     mul = layers.Multiply()([d1, d2])
     merged = layers.Concatenate()([add, sub, mul])
-    merged = layers.LeakyReLU(alpha=0.1)(merged)
+    merged = layers.LeakyReLU(negative_slope=0.1)(merged)
     out = layers.Dense(4, activation="softmax")(merged)
     model = models.Model([inp1, inp2], out)
     train_and_save(model, "Layer_Combination_3")

bindings/pyroot/pythonizations/test/generate_keras_sequential.py

@@ -1,3 +1,5 @@
+import warnings
+
 def generate_keras_sequential(dst_dir):
 
     import numpy as np
@@ -9,10 +11,19 @@
         x_train = np.random.rand(32, *model.input_shape[1:])
         y_train = np.random.rand(32, *model.output_shape[1:])
         model.compile(optimizer='adam', loss='mean_squared_error', metrics=['mae'])
-        model.fit(x_train, y_train, epochs=1, verbose=0)
+        if len(model.trainable_weights) > 0:
+            model.fit(x_train, y_train, epochs=1, verbose=0)
         model.summary()
         print("fitting sequential model",name)
-        model.save(f"{dst_dir}/Sequential_{name}_test.keras")
+
+        with warnings.catch_warnings():
+            # Some object inside TensorFlow/Keras has an outdated __array__ implementation
+            warnings.filterwarnings(
+                "ignore",
+                category=DeprecationWarning,
+                message=".*__array__.*copy keyword.*"
+            )
+            model.save(f"{dst_dir}/Sequential_{name}_test.keras")
 
 
     # Binary Ops: Add, Subtract, Multiply are not typical in Sequential - skipping those
@@ -193,7 +204,7 @@
         layers.Permute((2, 1)),
         layers.Flatten(),
         layers.Dense(32),
-        layers.LeakyReLU(alpha=0.1),
+        layers.LeakyReLU(negative_slope=0.1),
         layers.Dense(10, activation='softmax'),
     ])
     train_and_save(modelB, "Layer_Combination_2")
@@ -210,4 +221,4 @@
         layers.Dense(8, activation='swish'),
         layers.Dense(3, activation='softmax'),
     ])
-    train_and_save(modelC, "Layer_Combination_3")
+    train_and_save(modelC, "Layer_Combination_3")

bindings/pyroot/pythonizations/test/parser_test_function.py

@@ -2,10 +2,6 @@
 
 '''
 The test file contains two types of functions:
-    is_accurate:
-        - This function checks whether the inference results from SOFIE and Keras are accurate within a specified
-          tolerance. Since the inference result from Keras is not flattened, the function flattens both tensors before
-          performing the comparison.
 
     generate_and_test_inference:
         - This function accepts the following inputs:
@@ -29,7 +25,7 @@
           shape from the model object.
         - Convert the inference results to NumPy arrays:
           The SOFIE result is of type vector<float>, and the Keras result is a TensorFlow tensor. Both are converted to
-          NumPy arrays before being passed to the is_accurate function for comparison.
+          NumPy arrays before being passed to the np.testing.assert_allclose function for comparison.
 
 '''
 def is_channels_first_supported() :
@@ -42,16 +38,6 @@ def is_channels_first_supported() :
 
       return True
 
-def is_accurate(tensor_a, tensor_b, tolerance=1e-2):
-    tensor_a = tensor_a.flatten()
-    tensor_b = tensor_b.flatten()
-    for i in range(len(tensor_a)):
-        difference = abs(tensor_a[i] - tensor_b[i])
-        if difference > tolerance:
-            print(tensor_a[i], tensor_b[i])
-            return False
-    return True
-
 def generate_and_test_inference(model_file_path: str, generated_header_file_dir: str = None, batch_size=1):
 
     import keras
@@ -81,7 +67,6 @@ def generate_and_test_inference(model_file_path: str, generated_header_file_dir:
     sofie_model_namespace = getattr(ROOT, "TMVA_SOFIE_" + model_name)
     inference_session = sofie_model_namespace.Session(generated_header_file_path.removesuffix(".hxx") + ".dat")
     keras_model = keras.models.load_model(model_file_path)
-    keras_model.load_weights(model_file_path)
 
     input_tensors = []
     for model_input in keras_model.inputs:
@@ -91,11 +76,17 @@ def generate_and_test_inference(model_file_path: str, generated_header_file_dir:
     sofie_inference_result = inference_session.infer(*input_tensors)
     sofie_output_tensor_shape = list(rmodel.GetTensorShape(rmodel.GetOutputTensorNames()[0]))   # get output shape
                                                                                                 # from SOFIE
-    keras_inference_result = keras_model(input_tensors)
+    # Keras explicitly forbids input tensor lists of size 1
+    if len(keras_model.inputs) == 1:
+        keras_inference_result = keras_model(input_tensors[0])
+    else:
+        keras_inference_result = keras_model(input_tensors)
     if sofie_output_tensor_shape != list(keras_inference_result.shape):
         raise AssertionError("Output tensor dimensions from SOFIE and Keras do not match")
-    sofie_inference_result = np.asarray(sofie_inference_result)
-    keras_inference_result = np.asarray(keras_inference_result)
-    is_inference_accurate = is_accurate(sofie_inference_result, keras_inference_result)
-    if not is_inference_accurate:
-        raise AssertionError("Inference results from SOFIE and Keras do not match")
+
+    np.testing.assert_allclose(
+        np.asarray(sofie_inference_result).flatten(),
+        np.asarray(keras_inference_result).flatten(),
+        atol=1e-2,
+        rtol=0.  # explicitly disable relative tolerance (NumPy uses |a - b| <= atol + rtol * |b|)
+    )

cmake/modules/RootMacros.cmake

@@ -2014,7 +2014,7 @@ function(ROOT_ADD_PYUNITTESTS name)
 
   string(REGEX REPLACE "[_]" "-" good_name "${name}")
   ROOT_ADD_TEST(pyunittests-${good_name}
-                COMMAND ${Python3_EXECUTABLE} -B -m unittest discover -s ${CMAKE_CURRENT_SOURCE_DIR} -p "*.py" -v
+                COMMAND ${Python3_EXECUTABLE_DEV} -B -m unittest discover -s ${CMAKE_CURRENT_SOURCE_DIR} -p "*.py" -v
                 ENVIRONMENT PYTHONPATH=${pythonpaths_native})
 endfunction()
 
@@ -2074,9 +2074,9 @@ function(ROOT_ADD_PYUNITTEST name file)
   string(REPLACE "-test-" "-" clean_name_with_path ${name_with_path})
 
   if(ARG_GENERIC)
-    set(test_cmd COMMAND ${Python3_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/${file_name})
+    set(test_cmd COMMAND ${Python3_EXECUTABLE_DEV} ${CMAKE_CURRENT_SOURCE_DIR}/${file_name})
   else()
-    set(test_cmd COMMAND ${Python3_EXECUTABLE} -B -m unittest discover -s ${CMAKE_CURRENT_SOURCE_DIR}/${file_dir} -p ${file_name} -v)
+    set(test_cmd COMMAND ${Python3_EXECUTABLE_DEV} -B -m unittest discover -s ${CMAKE_CURRENT_SOURCE_DIR}/${file_dir} -p ${file_name} -v)
   endif()
 
   set(test_name pyunittests${clean_name_with_path})
@@ -2993,7 +2993,7 @@ macro(ROOTTEST_SETUP_MACROTEST)
   # Add python script to CTest.
   elseif(ARG_MACRO MATCHES "[.]py")
     get_filename_component(realfp ${ARG_MACRO} REALPATH)
-    set(command ${Python3_EXECUTABLE} ${realfp} ${PYROOT_EXTRAFLAGS})
+    set(command ${Python3_EXECUTABLE_DEV} ${realfp} ${PYROOT_EXTRAFLAGS})
 
   elseif(DEFINED ARG_MACRO)
     set(command ${root_cmd} ${ARG_MACRO})
@@ -3029,7 +3029,7 @@ macro(ROOTTEST_SETUP_EXECTEST)
 
   if(MSVC)
     if(${realexec} MATCHES "[.]py" AND NOT ${realexec} MATCHES "[.]exe")
-      set(realexec ${Python3_EXECUTABLE} ${realexec})
+      set(realexec ${Python3_EXECUTABLE_DEV} ${realexec})
     else()
       set(realexec ${realexec})
     endif()

cmake/modules/SearchInstalledSoftware.cmake

@@ -626,6 +626,9 @@ if(tmva-pymva OR tmva-sofie)
 endif()
 find_package(Python3 3.10 COMPONENTS ${python_components})
 
+# The invocation of the Python 3 executable that should be used for testing:
+set(Python3_EXECUTABLE_DEV ${Python3_EXECUTABLE} -X dev -W error)
+
 #---Check for OpenGL installation-------------------------------------------------------
 # OpenGL is required by various graf3d features that are enabled with opengl=ON,
 # or by the Cocoa-related code that always requires it.

roottest/main/CMakeLists.txt

@@ -11,7 +11,7 @@ configure_file(RootcpReplaceEntireFileCheck.C . COPYONLY)
 # We should explicitly use the Python executable from the Python version that
 # was used to build ROOT. Otherwise, we risk picking up a different Python
 # version at test time.
-set(PY_TOOLS_PREFIX ${Python3_EXECUTABLE} ${ROOTSYS}/bin)
+set(PY_TOOLS_PREFIX ${Python3_EXECUTABLE_DEV} ${ROOTSYS}/bin)
 set(TOOLS_PREFIX ${ROOTSYS}/bin)
 
 if(MSVC)
@@ -519,7 +519,7 @@ if(pyroot)
 set(test_env PYTHONWARNINGS=ignore)
 
 ############################## PATTERN TESTS ############################
-set (TESTPATTERN_EXE ${Python3_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/testPatternToFileNameAndPathSplitList.py)
+set (TESTPATTERN_EXE ${Python3_EXECUTABLE_DEV} ${CMAKE_CURRENT_SOURCE_DIR}/testPatternToFileNameAndPathSplitList.py)
 ROOTTEST_ADD_TEST(SimplePattern1
                   COMMAND ${TESTPATTERN_EXE} test.root
                   OUTREF SimplePattern.ref

roottest/python/JupyROOT/CMakeLists.txt

@@ -23,7 +23,7 @@ foreach(pyfile ${pyfiles})
   get_filename_component(SHORTPYFILE ${pyfile} NAME_WE)
   if (NOT ${SHORTPYFILE} STREQUAL "__init__")
     ROOTTEST_ADD_TEST(${SHORTPYFILE}_doctest
-                      COMMAND ${Python3_EXECUTABLE} ${DOCTEST_LAUNCHER} ${pyfile}
+                      COMMAND ${Python3_EXECUTABLE_DEV} ${DOCTEST_LAUNCHER} ${pyfile}
                       PYTHON_DEPS IPython)
   endif()
 endforeach()
@@ -33,7 +33,7 @@ foreach(NOTEBOOK ${NOTEBOOKS})
   get_filename_component(NOTEBOOKBASE ${NOTEBOOK} NAME_WE)
   ROOTTEST_ADD_TEST(${NOTEBOOKBASE}_notebook
                     COPY_TO_BUILDDIR ${NOTEBOOK}
-                    COMMAND ${Python3_EXECUTABLE} ${NBDIFFUTIL} ${NOTEBOOK}
+                    COMMAND ${Python3_EXECUTABLE_DEV} ${NBDIFFUTIL} ${NOTEBOOK}
                     RUN_SERIAL
                     PYTHON_DEPS jupyter)
 endforeach()
@@ -44,7 +44,7 @@ if(imt)
   get_filename_component(NOTEBOOKBASE ${IMT_NB} NAME_WE)
   ROOTTEST_ADD_TEST(${NOTEBOOKBASE}_notebook
                     COPY_TO_BUILDDIR ${IMT_NB}
-                    COMMAND ${Python3_EXECUTABLE} ${NBDIFFUTIL} ${IMT_NB} "OFF"
+                    COMMAND ${Python3_EXECUTABLE_DEV} ${NBDIFFUTIL} ${IMT_NB} "OFF"
                     RUN_SERIAL
                     PYTHON_DEPS jupyter)
 endif()

roottest/root/meta/CMakeLists.txt

@@ -26,7 +26,7 @@ ROOTTEST_ADD_TEST(ROOT5268
                   PASSREGEX "error: unknown type name 'Tbrowser'")
 
 ROOTTEST_ADD_TEST(rlibmap
-                  COMMAND ${Python3_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/rlibmapLauncher.py
+                  COMMAND ${Python3_EXECUTABLE_DEV} ${CMAKE_CURRENT_SOURCE_DIR}/rlibmapLauncher.py
                   PASSRC 1
                   OUTREF  rlibmap.ref)
 

roottest/root/rint/CMakeLists.txt

@@ -1,15 +1,15 @@
 if(${CMAKE_SYSTEM_PROCESSOR} MATCHES "x86_64.*|x86.*|amd64.*|AMD64.*|i686.*|i386.*")
   # All platforms except of ARM/AARCH64
   ROOTTEST_ADD_TEST(TabCom
-                    COMMAND ${Python3_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/driveTabCom.py
+                    COMMAND ${Python3_EXECUTABLE_DEV} ${CMAKE_CURRENT_SOURCE_DIR}/driveTabCom.py
                     INPUT TabCom_input.txt
                     OUTCNV filterOpt.sh
                     OUTREF TabCom.oref
                     ERRREF TabCom.eref
                     COPY_TO_BUILDDIR MyClass.h)
 
   ROOTTEST_ADD_TEST(BackslashNewline
-                    COMMAND ${Python3_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/driveTabCom.py
+                    COMMAND ${Python3_EXECUTABLE_DEV} ${CMAKE_CURRENT_SOURCE_DIR}/driveTabCom.py
                     INPUT BackslashNewline_input.txt)
 endif()
 

tutorials/CMakeLists.txt

@@ -687,7 +687,7 @@ if(geom)
 endif()
 # define Python GNN parsing tutorial needed to run before
 if (ROOT_SONNET_FOUND AND ROOT_GRAPH_NETS_FOUND)
-  ROOT_ADD_TEST(tutorial-machine_learning-TMVA_SOFIE_GNN_Parser COMMAND ${Python3_EXECUTABLE}
+  ROOT_ADD_TEST(tutorial-machine_learning-TMVA_SOFIE_GNN_Parser COMMAND ${Python3_EXECUTABLE_DEV}
   ${CMAKE_CURRENT_SOURCE_DIR}/machine_learning/TMVA_SOFIE_GNN_Parser.py
   PASSRC 0 FAILREGEX "Error in" ": error:" LABELS tutorial ENVIRONMENT ${TUTORIAL_ENV})
   set (machine_learning-TMVA_SOFIE_GNN_Application-depends tutorial-machine_learning-TMVA_SOFIE_GNN_Parser)
@@ -1043,7 +1043,7 @@ if(pyroot)
     endif()
 
     ROOT_ADD_TEST(${tutorial_name}
-                COMMAND ${Python3_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/${t}
+                COMMAND ${Python3_EXECUTABLE_DEV} ${CMAKE_CURRENT_SOURCE_DIR}/${t}
                 PASSRC ${rc} FAILREGEX "Error in" ": error:" "segmentation violation"
                 LABELS ${labels}
                 DEPENDS ${tutorial_dependency}