Arm backend: Remove pytest.mark.fails fomr testcases

Change-Id: I1bcd5e1188b2562195f7b81d51a2ab3da3d114ca

Author: SaoirseARM

backends/arm/test/ops/test_slice.py

@@ -153,9 +153,6 @@ 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
@@ -181,9 +178,6 @@ def test_slice_tensor_16a8w_tosa_INT(test_data: torch.Tensor):
 
 @common.parametrize("test_data", test_data_suite, x_fails)
 @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
@@ -208,9 +202,6 @@ def test_slice_tensor_16a8w_u55_INT16(test_data: torch.Tensor):
 
 @common.parametrize("test_data", test_data_suite, x_fails)
 @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