From f02e2c5ce5018df02c49dcfa69c1cb4ac1add0eb Mon Sep 17 00:00:00 2001
From: cmoineau <cyril.moineau@cea.fr>
Date: Mon, 31 Mar 2025 13:35:13 +0000
Subject: [PATCH] Add a first instance of unit test for Cpp export.
---
aidge_export_cpp/unit_tests/.gitignore | 2 +
aidge_export_cpp/unit_tests/test_export.py | 124 ++++++++++++++++++++-
2 files changed, 120 insertions(+), 6 deletions(-)
create mode 100644 aidge_export_cpp/unit_tests/.gitignore
diff --git a/aidge_export_cpp/unit_tests/.gitignore b/aidge_export_cpp/unit_tests/.gitignore
new file mode 100644
index 0000000..2194471
--- /dev/null
+++ b/aidge_export_cpp/unit_tests/.gitignore
@@ -0,0 +1,2 @@
+# Ignore
+/*_test/
\ No newline at end of file
diff --git a/aidge_export_cpp/unit_tests/test_export.py b/aidge_export_cpp/unit_tests/test_export.py
index 449eebe..d900df8 100644
--- a/aidge_export_cpp/unit_tests/test_export.py
+++ b/aidge_export_cpp/unit_tests/test_export.py
@@ -4,18 +4,130 @@ import aidge_backend_cpu
import aidge_export_cpp
import numpy as np
+import subprocess
+import re
+from aidge_core.utils import run_command
+
+def initFiller(model):
+ # Initialize parameters (weights and biases)
+ for node in model.get_nodes():
+ if node.type() == "Producer":
+ prod_op = node.get_operator()
+ value = prod_op.get_output(0)
+ value.set_backend("cpu")
+ tuple_out = node.output(0)[0]
+ # No conv in current network
+ if tuple_out[0].type() == "Conv" and tuple_out[1] == 1:
+ # Conv weight
+ aidge_core.xavier_uniform_filler(value)
+ elif tuple_out[0].type() == "Conv" and tuple_out[1] == 2:
+ # Conv bias
+ aidge_core.constant_filler(value, 0.01)
+ elif tuple_out[0].type() == "FC" and tuple_out[1] == 1:
+ # FC weight
+ aidge_core.normal_filler(value)
+ elif tuple_out[0].type() == "FC" and tuple_out[1] == 2:
+ # FC bias
+ aidge_core.constant_filler(value, 0.01)
+ else:
+ pass
+
+
+class test_operator_export(unittest.TestCase):
-class test_export(unittest.TestCase):
- """Test tensor binding
- """
def setUp(self):
- pass
+ # TODO change seed at each test ?
+ RNG_SEED = 1234
+ np.random.seed(RNG_SEED)
+ aidge_core.random.Generator.set_seed(RNG_SEED)
def tearDown(self):
pass
- def test_export_cpp(self):
- print("Export test to do")
+ def unit_test_export(self, graph_view, op_name, in_dims):
+ """
+ TODO:
+ * Handle multiple dataformat
+ * Handle multiple datatype (currently only float32)
+
+ Here are the following steps of this test:
+ 1- Generate random inputs
+ 2- Forward random inputs to the graph
+ 3- Generate Cpp export with a main that compare the result of the inference with the result obtained at step 2.
+ 4- Retrieve standard output and using regex to now if the results are the same
+ """
+ graph_view.compile("cpu", aidge_core.dtype.float32, dims=in_dims)
+ scheduler = aidge_core.SequentialScheduler(graph_view)
+
+ in_tensor = [aidge_core.Tensor(np.random.random(in_dim).astype(np.float32)) for in_dim in in_dims]
+ scheduler.forward(data=in_tensor)
+
+ # Note the convention ``<op_name>_test`` is useful for gitignore to avoid pushing generated export by accident.
+ export_folder = op_name + "_test"
+
+ # Export the model in C++ standalone
+ aidge_core.export_utils.scheduler_export(
+ scheduler,
+ export_folder,
+ aidge_export_cpp.ExportLibCpp,
+ memory_manager=aidge_core.mem_info.generate_optimized_memory_info,
+ memory_manager_args={"stats_folder": f"{export_folder}/stats", "wrapping": False }
+ )
+
+ aidge_core.export_utils.generate_main_compare_cpp(export_folder, graph_view)
+ print("COMPILATION")
+
+ try:
+ for std_line in run_command(["make"], cwd=export_folder):
+ print(std_line, end="")
+ except subprocess.CalledProcessError as e:
+ self.assertTrue(1, f"An error occurred: {e}\nFailed to generate export.")
+
+ print("RUN EXPORT")
+ pattern = r"Number of equal outputs: (\d+) / (\d+)"
+ comparison_matched = False
+ result = False
+ try:
+ for std_line in run_command(["./bin/run_export"], cwd=export_folder):
+ print(std_line, end="")
+ matches = re.findall(pattern, std_line)
+ if matches:
+ self.assertFalse(comparison_matched, "Two comparison matched found!")
+ expected, infered = map(int, matches[0])
+ result = (expected == infered)
+ comparison_matched = True
+ except subprocess.CalledProcessError as e:
+ self.assertTrue(1, f"An error occurred: {e}\nFailed to run export for comparison.")
+
+ self.assertTrue(comparison_matched, "No comparison matched found!")
+ self.assertTrue(result, "Export result are different than backend ones.")
+
+
+ def test_export_FC_flatten_in(self):
+ """Test exporting a FC operator with a flattened input.
+ """
+ model = aidge_core.sequential([
+ aidge_core.FC(in_channels=6, out_channels=6, name="InputNode")
+ ])
+ initFiller(model)
+
+ self.unit_test_export(model, "FC_flat", [[1, 6, 1, 1]])
+
+ @unittest.skip("Currently this test is failing")
+ def test_export_FC_image_in(self):
+ """Test exporting a FC operator with a HWC input.
+ """
+ model = aidge_core.sequential([
+ aidge_core.FC(in_channels=12, out_channels=6, name="InputNode")
+ ])
+ initFiller(model)
+ self.unit_test_export(model, "FC_img", [[1, 3, 2, 2]])
+ def test_export_Conv(self):
+ model = aidge_core.sequential([
+ aidge_core.Conv2D(1, 1, [3, 3], name="InputNode")
+ ])
+ initFiller(model)
+ self.unit_test_export(model, "Conv", [[1, 1, 9, 9]])
if __name__ == '__main__':
unittest.main()
--
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