Updating tests for 16A8W ops which are supported (#14945)

Summary:

Updating the TOSA, U55 & U85 tests to remove xfails. These ops are supported now and updating tests to not expect failure.

Differential Revision: D84262200

Author: Ninja91

backends/arm/test/ops/test_add.py

@@ -260,9 +260,6 @@ def get_symmetric_a16w8_add_quantizer(per_channel_quantization=False):
 
 
 @common.parametrize("test_data", Add.test_data)
-@pytest.mark.xfail(
-    reason="missing int16 add ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13730"
-)
 def test_add_tensor_16a8w_tosa_INT(test_data: input_t1):
     """Test add operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False

backends/arm/test/ops/test_cat.py

@@ -178,9 +178,6 @@ def get_symmetric_a16w8_cat_quantizer(per_channel_quantization=False):
 
 
 @common.parametrize("test_data", Cat.test_parameters)
-@pytest.mark.xfail(
-    reason="missing int16 cat ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13978"
-)
 def test_cat_16a8w_tosa_INT(test_data: Tuple):
     """Test cat operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -206,9 +203,6 @@ def test_cat_16a8w_tosa_INT(test_data: Tuple):
 
 @common.parametrize("test_data", Cat.test_parameters)
 @common.XfailIfNoCorstone300
-@pytest.mark.xfail(
-    reason="Vela compilation fails with 'Invalid arguments' for int16 cat operations"
-)
 def test_cat_16a8w_u55_INT16(test_data: Tuple):
     """Test cat operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -233,9 +227,6 @@ def test_cat_16a8w_u55_INT16(test_data: Tuple):
 
 @common.parametrize("test_data", Cat.test_parameters)
 @common.XfailIfNoCorstone320
-@pytest.mark.xfail(
-    reason="Vela compilation fails with 'Invalid arguments' for int16 cat operations"
-)
 def test_cat_16a8w_u85_INT16(test_data: Tuple):
     """Test cat operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False

backends/arm/test/ops/test_mul.py

@@ -310,9 +310,6 @@ def get_symmetric_a16w8_mul_quantizer(per_channel_quantization=False):
 
 
 @common.parametrize("test_data", test_data_suite)
-@pytest.mark.xfail(
-    reason="missing int16 mul ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13947"
-)
 def test_mul_tensor_16a8w_tosa_INT(test_data: input_t1):
     """Test mul operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False

backends/arm/test/ops/test_slice.py

@@ -154,9 +154,6 @@ def get_symmetric_a16w8_slice_quantizer(per_channel_quantization=False):
 
 
 @common.parametrize("test_data", test_data_suite)
-@pytest.mark.xfail(
-    reason="missing int16 slice ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13976"
-)
 def test_slice_tensor_16a8w_tosa_INT(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -182,9 +179,6 @@ def test_slice_tensor_16a8w_tosa_INT(test_data: torch.Tensor):
 
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone300
-@pytest.mark.xfail(
-    reason="Vela compilation fails with 'Invalid arguments' for int16 slice operations"
-)
 def test_slice_tensor_16a8w_u55_INT16(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -209,9 +203,6 @@ def test_slice_tensor_16a8w_u55_INT16(test_data: torch.Tensor):
 
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone320
-@pytest.mark.xfail(
-    reason="Vela compilation fails with 'Invalid arguments' for int16 slice operations"
-)
 def test_slice_tensor_16a8w_u85_INT16(test_data: torch.Tensor):
     """Test slice operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False

backends/arm/test/ops/test_view.py

@@ -9,7 +9,6 @@
 
 from typing import Tuple
 
-import pytest
 import torch
 from executorch.backends.arm.quantizer.arm_quantizer import (
     get_symmetric_a16w8_quantization_config,
@@ -180,9 +179,6 @@ def get_symmetric_a16w8_view_quantizer(per_channel_quantization=False):
 
 
 @common.parametrize("test_data", View.needs_transpose_tests)
-@pytest.mark.xfail(
-    reason="missing int16 view ops support; fails at TOSA reference model with Unsupported operation type or rank. See: https://github.com/pytorch/executorch/issues/13977"
-)
 def test_view_16a8w_tosa_INT(test_data: Tuple):
     """Test view operation with 16A8W quantization (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -209,9 +205,6 @@ def test_view_16a8w_tosa_INT(test_data: Tuple):
 
 @common.parametrize("test_data", View.needs_transpose_tests)
 @common.XfailIfNoCorstone300
-@pytest.mark.xfail(
-    reason="Vela compilation fails with 'Invalid arguments' for int16 view operations"
-)
 def test_view_16a8w_u55_INT16(test_data: Tuple):
     """Test view operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -237,9 +230,6 @@ def test_view_16a8w_u55_INT16(test_data: Tuple):
 
 @common.parametrize("test_data", View.needs_transpose_tests)
 @common.XfailIfNoCorstone320
-@pytest.mark.xfail(
-    reason="Vela compilation fails with 'Invalid arguments' for int16 view operations"
-)
 def test_view_16a8w_u85_INT16(test_data: Tuple):
     """Test view operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False