Arm backend: Add int16x8 LayerNorm test cases (#16015)

### Summary
- Updates test_rsqrt to use a lower epsilon
- Adds epsilon parameter to test_pipeline.py

Author: SaoirseARM

backends/arm/test/ops/test_layer_norm.py

@@ -137,3 +137,50 @@ def test_native_layer_norm_vgf_INT(test_data):
         tosa_version="TOSA-1.0+INT",
     )
     pipeline.run()
+
+
+@common.parametrize("test_data", test_data_suite)
+def test_native_layer_norm_tosa_INT_a16w8(test_data):
+    """Test layer_norm with int16 I/O quantization for TOSA INT."""
+    test_input, model = test_data()
+    pipeline = TosaPipelineINT[input_t](
+        model,
+        test_input,
+        "torch.ops.aten.sub.Tensor",  # check for sub op in decomposition
+        symmetric_io_quantization=True,
+        tosa_extensions=["int16"],
+        epsilon=2**16,
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data_suite)
+@common.XfailIfNoCorstone300
+def test_native_layer_norm_16a8w_u55_INT16(test_data):
+    """Test layer_norm with int16 I/O quantization for U55"""
+    test_input, model = test_data()
+    pipeline = EthosU55PipelineINT[input_t](
+        model,
+        test_input,
+        "torch.ops.aten.sub.Tensor",
+        symmetric_io_quantization=True,
+        a16w8_quantization=True,
+        epsilon=2**16,
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", test_data_suite)
+@common.XfailIfNoCorstone320
+def test_native_layer_norm_16a8w_u85_INT16(test_data):
+    """Test layer_norm with int16 I/O quantization for U85"""
+    test_input, model = test_data()
+    pipeline = EthosU85PipelineINT[input_t](
+        model,
+        test_input,
+        "torch.ops.aten.sub.Tensor",
+        symmetric_io_quantization=True,
+        a16w8_quantization=True,
+        epsilon=2**16,
+    )
+    pipeline.run()

backends/arm/test/ops/test_rsqrt.py

@@ -10,11 +10,8 @@
 
 import pytest
 import torch
-from executorch.backends.arm.quantizer.arm_quantizer import (
-    get_symmetric_a16w8_quantization_config,
-    TOSAQuantizer,
-)
-from executorch.backends.arm.test import common, conftest
+
+from executorch.backends.arm.test import common
 
 from executorch.backends.arm.test.tester.test_pipeline import (
     EthosU55PipelineINT,
@@ -23,8 +20,6 @@
     TosaPipelineINT,
     VgfPipeline,
 )
-from executorch.backends.arm.tosa import TosaSpecification
-from executorch.backends.xnnpack.test.tester import Quantize
 
 aten_op = "torch.ops.aten.rsqrt.default"
 input_t1 = Tuple[torch.Tensor]  # Input x
@@ -112,48 +107,18 @@ def test_rsqrt_vgf_INT(test_tensor: torch.Tensor):
     pipeline.run()
 
 
-def get_symmetric_a16w8_rsqrt_quantizer(
-    u55_config=False, per_channel_quantization=False
-):
-    tosa_version = conftest.get_option("tosa_version")
-    tosa_profiles = {
-        "1.0": TosaSpecification.create_from_string("TOSA-1.0+INT+int16"),
-    }
-
-    quantizer = TOSAQuantizer(tosa_profiles[tosa_version])
-    quantizer.set_global(
-        get_symmetric_a16w8_quantization_config(is_per_channel=per_channel_quantization)
-    )
-
-    return Quantize(
-        quantizer,
-        get_symmetric_a16w8_quantization_config(
-            is_per_channel=per_channel_quantization
-        ),
-    )
-
-
 @common.parametrize("test_tensor", Rsqrt.test_parameters)
-@pytest.mark.xfail(
-    reason="MLETORCH-707: AssertionError: Output 0 does not match reference output."
-)
-def test_rsqrt_16a8w_tosa_INT(test_tensor: torch.Tensor):
-    """Test rsqrt operation with int16 quantization"""
+def test_rsqrt_tosa_INT_a16w8(test_tensor: torch.Tensor):
+    """Test rsqrt operation with int16 I/O quantization for TOSA INT."""
+    # Use wider tolerances for int16 I/O quantization
     pipeline = TosaPipelineINT[input_t1](
         Rsqrt(),
         test_tensor(),
         aten_op,
         exir_op=[],
-        per_channel_quantization=False,
-        use_to_edge_transform_and_lower=True,
         tosa_extensions=["int16"],
+        epsilon=2**16,
     )
-
-    pipeline.change_args(
-        "quantize",
-        get_symmetric_a16w8_rsqrt_quantizer(per_channel_quantization=False),
-    )
-    # Run the pipeline
     pipeline.run()
 
 
@@ -163,46 +128,30 @@ def test_rsqrt_16a8w_tosa_INT(test_tensor: torch.Tensor):
     reason="MLETORCH-707: AssertionError: Output 0 does not match reference output."
 )
 def test_rsqrt_16a8w_u55_INT16(test_tensor: torch.Tensor):
-    """Test rsqrt operation with int16 quantization on U55"""
+    """Test rsqrt operation with int16 I/O quantization for U55"""
+    # Use wider tolerances for int16 I/O quantization on U55
     pipeline = EthosU55PipelineINT[input_t1](
         Rsqrt(),
         test_tensor(),
         aten_op,
         exir_ops=[],
-        per_channel_quantization=True,
-        use_to_edge_transform_and_lower=True,
-        atol=1e-03,
-        rtol=1e-03,
-        run_on_fvp=True,
-    )
-
-    pipeline.change_args(
-        "quantize",
-        get_symmetric_a16w8_rsqrt_quantizer(per_channel_quantization=True),
+        a16w8_quantization=True,
+        epsilon=2**16,
     )
     pipeline.run()
 
 
 @common.parametrize("test_tensor", Rsqrt.test_parameters)
 @common.XfailIfNoCorstone320
-@pytest.mark.xfail(
-    reason="MLETORCH-707: AssertionError: Output 0 does not match reference output."
-)
 def test_rsqrt_16a8w_u85_INT16(test_tensor: torch.Tensor):
-    """Test rsqrt operation with int16 quantization on U85"""
+    """Test rsqrt operation with int16 I/O quantization for U85"""
+    # Use wider tolerances for int16 I/O quantization on U85
     pipeline = EthosU85PipelineINT[input_t1](
         Rsqrt(),
         test_tensor(),
         aten_op,
         exir_ops=[],
-        use_to_edge_transform_and_lower=True,
-        atol=1e-03,
-        rtol=1e-03,
-        run_on_fvp=True,
-    )
-
-    pipeline.change_args(
-        "quantize",
-        get_symmetric_a16w8_rsqrt_quantizer(per_channel_quantization=False),
+        a16w8_quantization=True,
+        epsilon=2**16,
     )
     pipeline.run()

backends/arm/test/tester/test_pipeline.py

@@ -357,6 +357,7 @@ def __init__(
         qtol: int = 1,
         dynamic_shapes: Optional[Tuple[Any]] = None,
         tosa_extensions: Optional[List[str]] = None,
+        epsilon: float = 2**12,
     ):
         if tosa_extensions is None:
             tosa_extensions = []
@@ -377,7 +378,7 @@ def __init__(
         # choose 16A8W quantization config when int16 extension is requested
         if "int16" in tosa_extensions:
             quantization_config = get_symmetric_a16w8_quantization_config(
-                is_per_channel=per_channel_quantization
+                is_per_channel=per_channel_quantization, epsilon=epsilon
             )
         else:
             quantization_config = get_symmetric_quantization_config(
@@ -550,6 +551,7 @@ def __init__(
         atol: float = 1e-03,
         rtol: float = 1e-03,
         qtol: int = 1,
+        epsilon: float = 2**12,
     ):
         compile_spec = common.get_u55_compile_spec(
             custom_path=custom_path,
@@ -559,7 +561,7 @@ def __init__(
         # choose int8 or int16 activation quantization
         if a16w8_quantization:
             quantization_config = get_symmetric_a16w8_quantization_config(
-                is_per_channel=per_channel_quantization
+                is_per_channel=per_channel_quantization, epsilon=epsilon
             )
         else:
             quantization_config = get_symmetric_quantization_config(
@@ -650,6 +652,7 @@ def __init__(
         atol: float = 1e-03,
         rtol: float = 1e-03,
         qtol: int = 1,
+        epsilon: float = 2**12,
     ):
         compile_spec = common.get_u85_compile_spec(
             custom_path=custom_path,
@@ -659,7 +662,7 @@ def __init__(
         # choose int8 or int16 activation quantization
         if a16w8_quantization:
             quantization_config = get_symmetric_a16w8_quantization_config(
-                is_per_channel=per_channel_quantization
+                is_per_channel=per_channel_quantization, epsilon=epsilon
             )
         else:
             quantization_config = get_symmetric_quantization_config(