chore: use approximate in torch cifar training evaluation

zama-ai · Apr 16, 2024 · 69e5911 · 69e5911
1 parent 10a7f21
commit 69e5911
Show file tree

Hide file tree

Showing 2 changed files with 5 additions and 3 deletions.
diff --git a/use_case_examples/cifar/cifar_brevitas_training/Makefile b/use_case_examples/cifar/cifar_brevitas_training/Makefile
@@ -11,5 +11,7 @@ run_example: one two
 one:
 	@python evaluate_one_example_fhe.py
 
-two:
-	@python evaluate_torch_cml.py
+# FIXME: https://github.com/zama-ai/concrete-ml-internal/issues/4389
+# too slow on cpu
+# two:
+# 	@python evaluate_torch_cml.py
diff --git a/use_case_examples/cifar/cifar_brevitas_training/evaluate_torch_cml.py b/use_case_examples/cifar/cifar_brevitas_training/evaluate_torch_cml.py
@@ -118,7 +118,7 @@ def main(args):
             input_set,
             n_bits={"model_inputs": 8, "model_outputs": 8},
             configuration=cfg,
-            rounding_threshold_bits={"n_bits": rounding_threshold_bits, "method": "EXACT"}
+            rounding_threshold_bits={"n_bits": rounding_threshold_bits, "method": "APPROXIMATE"}
             if rounding_threshold_bits is not None
             else None,
         )