chore: exact to appox

zama-ai · Jun 5, 2024 · c35c57e · c35c57e
1 parent 893e956
commit c35c57e
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Showing 2 changed files with 8 additions and 5 deletions.
diff --git a/use_case_examples/cifar/cifar_brevitas_training/evaluate_one_example_fhe.py b/use_case_examples/cifar/cifar_brevitas_training/evaluate_one_example_fhe.py
@@ -84,11 +84,13 @@ def wrapper(*args, **kwargs):
 # Multi-parameter strategy is used in order to speed-up the FHE executions
 base_configuration = Configuration()
 
+exactness = fhe.Exactness.APPROXIMATE
+
 tlu_optimizer = TLU1bitDecomposition(
     n_jumps_limit=2,
-    exactness=fhe.Exactness.EXACT,
+    exactness=exactness,
 )
-rounding = InsertRounding(6)
+rounding = InsertRounding(6, exactness=exactness)
 
 configuration = Configuration(
     dump_artifacts_on_unexpected_failures=False,

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
@@ -36,7 +36,7 @@ def evaluate(torch_model, cml_model, device, num_workers):
 
     # Import and load the CIFAR test dataset (following bnn_pynq_train.py)
     test_set = get_test_set(dataset="CIFAR10", datadir=CURRENT_DIR / ".datasets/")
-    test_set = Subset(test_set, np.arange(128))
+    # test_set = Subset(test_set, np.arange(128))
     test_loader = DataLoader(test_set, batch_size=128, shuffle=False, num_workers=num_workers)
 
     torch_top_1_batches = []
@@ -121,12 +121,13 @@ def main(args):
     # Eval mode
     model.eval()
 
+    exactness=fhe.Exactness.APPROXIMATE
     # Multi-parameter strategy is used in order to speed-up the FHE executions
     tlu_optimizer = TLU1bitDecomposition(
         n_jumps_limit=2,
-        exactness=fhe.Exactness.EXACT,
+        exactness=exactness,
     )
-    insert_rounding = InsertRounding(6)
+    insert_rounding = InsertRounding(6,exactness=exactness)
     # debug_processor = Debug()
     cfg = Configuration(
         verbose=True,