[Backend Tester] Reduce log verbosity / spam

backends/test/harness/stages/serialize.py

@@ -13,6 +13,7 @@
 try:
     from executorch.extension.pybindings.portable_lib import (  # @manual
         _load_for_executorch_from_buffer,
+        Verification,
     )
 except ImportError as e:
     logger.warning(f"{e=}")
@@ -39,7 +40,9 @@ def graph_module(self) -> None:
 
     def run_artifact(self, inputs):
         inputs_flattened, _ = tree_flatten(inputs)
-        executorch_module = _load_for_executorch_from_buffer(self.buffer)
+        executorch_module = _load_for_executorch_from_buffer(
+            self.buffer, program_verification=Verification.Minimal
+        )
         executorch_output = copy.deepcopy(
             executorch_module.run_method("forward", tuple(inputs_flattened))
         )

backends/test/harness/stages/to_edge_transform_and_lower.py

@@ -23,7 +23,9 @@ def __init__(
             if default_partitioner_cls is not None
             else []
         )
-        self.edge_compile_conf = edge_compile_config or EdgeCompileConfig()
+        self.edge_compile_conf = edge_compile_config or EdgeCompileConfig(
+            _check_ir_validity=False
+        )
         self.edge_dialect_program = None
 
     def stage_type(self) -> StageType:

backends/test/suite/context.py

@@ -1,13 +1,16 @@
 # Test run context management. This is used to determine the test context for reporting
 # purposes.
 class TestContext:
+    subtest_index: int
+
     def __init__(
         self, test_name: str, test_base_name: str, flow_name: str, params: dict | None
     ):
         self.test_name = test_name
         self.test_base_name = test_base_name
         self.flow_name = flow_name
         self.params = params
+        self.subtest_index = 0
 
     def __enter__(self):
         global _active_test_context

backends/test/suite/models/__init__.py

@@ -119,6 +119,7 @@ def run_model_test(
         flow,
         context.test_name,
         context.test_base_name,
+        0, # subtest_index - currently unused for model tests
         context.params,
         dynamic_shapes=dynamic_shapes,
     )

backends/test/suite/operators/__init__.py

@@ -152,12 +152,16 @@ def _test_op(
             flow,
             context.test_name,
             context.test_base_name,
+            context.subtest_index,
             context.params,
             generate_random_test_inputs=generate_random_test_inputs,
         )
 
         log_test_summary(run_summary)
 
+        # This is reset when a new test is started - it creates the context per-test.
+        context.subtest_index = context.subtest_index + 1
+
         if not run_summary.result.is_success():
             if run_summary.result.is_backend_failure():
                 raise RuntimeError("Test failure.") from run_summary.error

backends/test/suite/operators/test_amax.py

@@ -207,39 +207,39 @@ def test_amax_edge_cases(self, flow: TestFlow) -> None:
             AmaxModel(),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             AmaxModel(dim=0),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             AmaxModel(dim=1),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
 
         x = torch.tensor([[1.0, float("nan"), 3.0], [4.0, 5.0, float("nan")]])
         self._test_op(
             AmaxModel(),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             AmaxModel(dim=0),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             AmaxModel(dim=1),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
 
     def test_amax_scalar(self, flow: TestFlow) -> None:

backends/test/suite/operators/test_amin.py

@@ -209,39 +209,39 @@ def test_amin_edge_cases(self, flow: TestFlow) -> None:
             AminModel(),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             AminModel(dim=0),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             AminModel(dim=1),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
 
         x = torch.tensor([[1.0, float("nan"), 3.0], [4.0, 5.0, float("nan")]])
         self._test_op(
             AminModel(),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             AminModel(dim=0),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             AminModel(dim=1),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
 
     def test_amin_scalar(self, flow: TestFlow) -> None:

backends/test/suite/operators/test_argmax.py

@@ -149,39 +149,39 @@ def test_argmax_edge_cases(self, flow: TestFlow) -> None:
             ArgmaxModel(),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             ArgmaxModel(dim=0),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             ArgmaxModel(dim=1),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
 
         x = torch.tensor([[1.0, float("nan"), 3.0], [4.0, 5.0, float("nan")]])
         self._test_op(
             ArgmaxModel(),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             ArgmaxModel(dim=0),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             ArgmaxModel(dim=1),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
 
         x = torch.tensor([5.0])

backends/test/suite/operators/test_argmin.py

@@ -149,39 +149,39 @@ def test_argmin_edge_cases(self, flow: TestFlow) -> None:
             ArgminModel(),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             ArgminModel(dim=0),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             ArgminModel(dim=1),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
 
         x = torch.tensor([[1.0, float("nan"), 3.0], [4.0, 5.0, float("nan")]])
         self._test_op(
             ArgminModel(),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             ArgminModel(dim=0),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
         self._test_op(
             ArgminModel(dim=1),
             (x,),
             flow,
-            use_random_test_inputs=False,
+            generate_random_test_inputs=False,
         )
 
         x = torch.tensor([5.0])

backends/test/suite/operators/test_floor.py

@@ -18,8 +18,8 @@
 
 
 class FloorModel(torch.nn.Module):
-    def __init__(self):
-        super().__init__()
+    def forward(self, x):
+        return torch.floor(x)
 
 
 @operator_test