Update mul int16 test for Ethos (#14646)

Summary:


bypass-github-export-checks
bypass-github-pytorch-ci-checks
bypass-github-executorch-ci-checks

Reviewed By: digantdesai

Differential Revision: D83437473

Author: 3l1

backends/arm/operators/op_repeat.py

@@ -44,7 +44,7 @@ def define_node(
         validate_valid_dtype(
             self.target,
             [inputs[0], output],
-            [ts.DType.INT8, ts.DType.INT32, ts.DType.FP32],
+            [ts.DType.INT8, ts.DType.INT32, ts.DType.INT16, ts.DType.FP32],
             output.tosa_spec,
         )
 

backends/arm/test/ops/test_mul.py

@@ -338,9 +338,6 @@ def test_mul_tensor_16a8w_tosa_INT(test_data: input_t1):
 
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone300
-@pytest.mark.xfail(
-    reason="Vela compilation fails with 'Invalid arguments' for int16 mul operations. See: https://github.com/pytorch/executorch/issues/13947"
-)
 def test_mul_tensor_16a8w_u55_INT16(test_data: input_t1):
     """Test mul operation with 16A8W quantization on U55 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False
@@ -365,9 +362,6 @@ def test_mul_tensor_16a8w_u55_INT16(test_data: input_t1):
 
 @common.parametrize("test_data", test_data_suite)
 @common.XfailIfNoCorstone320
-@pytest.mark.xfail(
-    reason="Vela compilation fails with 'Invalid arguments' for int16 mul operations. See: https://github.com/pytorch/executorch/issues/13947"
-)
 def test_mul_tensor_16a8w_u85_INT16(test_data: input_t1):
     """Test mul operation with 16A8W quantization on U85 (16-bit activations, 8-bit weights)"""
     per_channel_quantization = False