Add a16w8 per-op test for split (pytorch#19600)

Summary:
Add int16 activation / int8 weight (a16w8) quantization tests for
`aten.split` on Ethos-U55 and Ethos-U85.

## Changes
- Add `a16w8_split_test_parameters` dict with 3 test configurations
covering 1D, 2D, and 3D splits along different axes
- Add `test_split_a16w8_u55_INT` using `EthosU55PipelineINT` with
`a16w8_quantization=True, symmetric_io_quantization=True`
- Add `test_split_a16w8_u85_INT` using `EthosU85PipelineINT` with same
kwargs
- Register `ops/test_split.py` in `fbcode/` and `xplat/` `targets.bzl`

Differential Revision: D104533281

Author: christine-long-meta

backends/arm/test/ops/test_split.py

@@ -310,3 +310,38 @@ def test_split_tensor_vgf_quant(test_data: Tuple):
         quantize=True,
     )
     pipeline.run()
+
+
+a16w8_split_test_parameters = {
+    "a16w8_1d_split_2": lambda: (torch.rand(10), 2, 0),
+    "a16w8_2d_split_4": lambda: (torch.rand(8, 4), 4, 0),
+    "a16w8_3d_split_4": lambda: (torch.rand(4, 4, 8), 4, 2),
+}
+
+
+@common.parametrize("test_data", a16w8_split_test_parameters)
+@common.XfailIfNoCorstone300
+def test_split_a16w8_u55_INT(test_data: input_t1):
+    pipeline = EthosU55PipelineINT[input_t1](
+        Split(),
+        test_data(),
+        aten_ops=[],
+        exir_ops=exir_op,
+        a16w8_quantization=True,
+        symmetric_io_quantization=True,
+    )
+    pipeline.run()
+
+
+@common.parametrize("test_data", a16w8_split_test_parameters)
+@common.XfailIfNoCorstone320
+def test_split_a16w8_u85_INT(test_data: input_t1):
+    pipeline = EthosU85PipelineINT[input_t1](
+        Split(),
+        test_data(),
+        aten_ops=[],
+        exir_ops=exir_op,
+        a16w8_quantization=True,
+        symmetric_io_quantization=True,
+    )
+    pipeline.run()

backends/arm/test/ops/test_var.py

@@ -32,6 +32,11 @@ class Var(torch.nn.Module):
         ),
     }
 
+    test_parameters_ethosu = {
+        "var_4d_keep_dim_0_correction": lambda: (torch.randn(1, 50, 10, 20), True, 0),
+        "var_4d_keep_dim_1_correction": lambda: (torch.randn(1, 30, 15, 20), True, 1),
+    }
+
     def __init__(self, keepdim: bool = True, correction: int = 0):
         super().__init__()
         self.keepdim = keepdim

backends/arm/test/targets.bzl

@@ -43,6 +43,7 @@ def define_arm_tests():
         "ops/test_conv1d.py",
         "ops/test_gelu.py",
         "ops/test_bmm.py",
+        "ops/test_split.py",
     ]
 
     # Quantization