Arm backend: Add test for DeiT Tiny for TOSA BI (#10846)

Add test case for the DeiT Tiny model for the TOSA BI profile. At this
time the output of the model differs from the reference implementation
by a mean absolute error of around 2.5, which is too high. An internal
ticket has been raised to resolve this issue.

Signed-off-by: Martin Lindström <[email protected]>

Author: martinlsm

backends/arm/test/models/test_deit_tiny_arm.py

@@ -11,7 +11,10 @@
 
 import torch
 
-from executorch.backends.arm.test.tester.test_pipeline import TosaPipelineMI
+from executorch.backends.arm.test.tester.test_pipeline import (
+    TosaPipelineBI,
+    TosaPipelineMI,
+)
 
 from timm.data import IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
 from torchvision import transforms
@@ -42,3 +45,16 @@ def test_deit_tiny_tosa_MI():
         qtol=1,
     )
     pipeline.run()
+
+
+def test_deit_tiny_tosa_BI():
+    pipeline = TosaPipelineBI[input_t](
+        deit_tiny,
+        model_inputs,
+        aten_op=[],
+        exir_op=[],
+        use_to_edge_transform_and_lower=True,
+        atol=3.0,  # This needs to go down: MLETORCH-956
+        qtol=1,
+    )
+    pipeline.run()