executorch/backends/qualcomm/tests

Reviewed By: avikchaudhuri

Differential Revision: D67381442

Author: gmagogsfm

backends/qualcomm/tests/test_qnn_delegate.py

@@ -1617,7 +1617,7 @@ def test_qnn_backend_multi_contexts_composite(self):
         )
         sample_input = module.get_random_input()
         edge_prog = to_edge(
-            torch.export.export(module, sample_input),
+            torch.export.export(module, sample_input, strict=True),
         )
         update_spill_fill_size(edge_prog.exported_program())
         exec_prog = edge_prog.to_executorch()
@@ -1957,7 +1957,7 @@ def calibrator(gm):
         self.assertEqual(len(exported_progs), 1)
         # lower all graph again, the skipped operators will be left in CPU
         exec_prog = to_edge(
-            torch.export.export(graph_module, sample_input),
+            torch.export.export(graph_module, sample_input, strict=True),
         ).to_executorch()
         self.verify_output(module, sample_input, exec_prog)
 
@@ -2004,7 +2004,7 @@ def calibrator(gm):
         self.assertEqual(len(exported_progs), 2)
         # lower all graph again, the skipped operators will be left in CPU
         exec_prog = exec_prog = to_edge(
-            torch.export.export(graph_module, sample_input),
+            torch.export.export(graph_module, sample_input, strict=True),
         ).to_executorch()
         self.verify_output(module, sample_input, exec_prog)
 
@@ -2041,7 +2041,7 @@ def calibrator(gm):
         self.assertEqual(len(exported_progs), 5)
         # lower all graph again, the skipped operators will be delegated with fp16
         exec_prog = to_edge(
-            torch.export.export(graph_module, sample_input),
+            torch.export.export(graph_module, sample_input, strict=True),
         ).to_executorch()
         self.verify_output(module, sample_input, exec_prog)
 
@@ -2086,7 +2086,7 @@ def test_qnn_backend_multi_contexts_composite(self):
         )
         sample_input = module.get_random_input()
         edge_prog = to_edge(
-            torch.export.export(module, sample_input),
+            torch.export.export(module, sample_input, strict=True),
         )
         update_spill_fill_size(edge_prog.exported_program())
         exec_prog = edge_prog.to_executorch()
@@ -2721,7 +2721,6 @@ def test_ssd300_vgg16(self):
 
 
 class TestExampleQaihubScript(TestQNN):
-
     def required_envs(self, conditions=None) -> bool:
         conditions = [] if conditions is None else conditions
         return all(

backends/qualcomm/tests/utils.py

@@ -385,7 +385,7 @@ def get_qdq_module(
         custom_quant_annotations: Tuple[Callable] = (),
         quant_dtype: QuantDtype = QuantDtype.use_8a8w,
     ) -> torch.fx.GraphModule:
-        m = torch.export.export(module, inputs).module()
+        m = torch.export.export(module, inputs, strict=True).module()
 
         quantizer = QnnQuantizer()
         quantizer.add_custom_quant_annotations(custom_quant_annotations)