Arm backend: Skip int operation tests as for FP profile

backends/arm/test/ops/test_embedding.py

@@ -6,6 +6,7 @@
 
 from typing import Tuple
 
+import pytest
 import torch
 from executorch.backends.arm._passes import InsertCastForOpsWithInt64InputPass
 
@@ -57,6 +58,7 @@ def forward(self, weights: torch.Tensor, indices: torch.Tensor):
 }
 
 
+@pytest.mark.skip(reason="MLETORCH-1274 Improve data type checks during partitioning")
 @common.parametrize("test_input", test_input)
 def test_embedding_tosa_FP(test_input: input_params):
     op = Embedding()
@@ -87,6 +89,7 @@ def test_embedding_tosa_INT(test_input: input_params):
     pipeline.run()
 
 
+@pytest.mark.skip("reason=MLETORCH-1274 Improve data type checks during partitioning")
 @common.parametrize("test_input", test_input)
 @common.SkipIfNoModelConverter
 def test_embedding_vgf_FP(test_input: input_params):

backends/arm/test/ops/test_eye.py

@@ -3,6 +3,7 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
+import pytest
 import torch
 from executorch.backends.arm.test import common
 from executorch.backends.arm.test.tester.test_pipeline import (
@@ -48,6 +49,9 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
     }
 
 
+# skip test since int32 isn't support on FP profile
+# "int32_int32": "view/RESHAPE of integer tensor is not supported for +FP profile"
+@pytest.mark.skip(reason="MLETORCH-1274 Improve data type checks during partitioning")
 @common.parametrize("test_data", EyeAdd.test_data)
 def test_eye_tosa_FP(test_data: test_data_t):
     input_data, init_data = test_data
@@ -99,6 +103,9 @@ def test_eye_u85_INT(test_data: test_data_t):
     pipeline.run()
 
 
+# skip since int32 isn't support on FP profile
+# "int32_int32": "view/RESHAPE of integer tensor is not supported for +FP profile"
+@pytest.mark.skip(reason="MLETORCH-1274 Improve data type checks during partitioning")
 @common.parametrize(
     "test_data",
     EyeAdd.test_data,

backends/arm/test/ops/test_mul.py

@@ -129,7 +129,17 @@ def test_mul_tensor_tosa_FP_diff_input_ranks(test_data: torch.Tensor):
     pipeline.run()
 
 
-@common.parametrize("test_data", test_data_suite_int32)
+# MLETORCH-1274 Improve data type checks during partitioning
+# view/RESHAPE of integer tensor is not supported for +FP profile which causes issues
+# with view_copy (RESHAPE) which isn't supported in FP so removing the int32 tests
+# to allow for the dtype validation patches to land.
+# filter out the 'op_mul_rank4_randn_int32' only
+test_data_int32_without_broadcasting = {
+    k: v for k, v in test_data_suite_int32.items() if k != "op_mul_rank4_randn_int32"
+}
+
+
+@common.parametrize("test_data", test_data_int32_without_broadcasting)
 def test_mul_tensor_tosa_FP_int32(test_data: torch.Tensor):
     pipeline = TosaPipelineFP[input_t1](
         Mul(),
@@ -228,8 +238,14 @@ def test_mul_tensor_u85_INT_int32(test_data: torch.Tensor):
     pipeline.run()
 
 
+# view/RESHAPE of integer tensor is not supported for +FP profile which causes issues
+# with view_copy (RESHAPE) which isn't supported in FP so removing the int32 tests
+# to allow for the dtype validation patches to land.
+
+
 @common.parametrize(
-    "test_data", test_data_suite | test_data_suite_2 | test_data_suite_int32
+    "test_data",
+    test_data_suite | test_data_suite_2 | test_data_int32_without_broadcasting,
 )
 @common.SkipIfNoModelConverter
 def test_mul_tensor_vgf_FP(test_data: torch.Tensor):

backends/arm/test/ops/test_scalars.py

@@ -417,6 +417,9 @@ def test_div_scalar_u85_INT():
 
 
 # SHIFT ETHOS-U ------------------------------------------------------
+@pytest.mark.skip(
+    reason="integer operations (shift and sub) are not supported on FP profile"
+)
 def test_bitwise_right_shift_tensor_tosa_FP_inplace():
     pipeline = TosaPipelineFP[input_t1](
         ShiftInplaceSub(),