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Sebastian-LarssonSebastian-Larsson
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Arm backend: Refactor gt, ge, lt, le and eq tests to pipeline (#8828)
Signed-off-by: Sebastian Larsson <[email protected]>
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6 files changed

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-640
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6 files changed

+620
-640
lines changed

‎backends/arm/operator_support/tosa_supported_operators.py

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@@ -195,6 +195,11 @@ def is_node_supported(
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exir_ops.edge.aten.bitwise_xor.Tensor,
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exir_ops.edge.aten.amax.default,
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exir_ops.edge.aten.amin.default,
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exir_ops.edge.aten.eq.Tensor,
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exir_ops.edge.aten.ge.Tensor,
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exir_ops.edge.aten.gt.Tensor,
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exir_ops.edge.aten.le.Tensor,
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exir_ops.edge.aten.lt.Tensor,
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]
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if node.target in unsupported_ops:

‎backends/arm/test/ops/test_eq.py

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@@ -1,145 +1,136 @@
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# Copyright 2025 Arm Limited and/or its affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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import unittest
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from typing import Tuple
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import pytest
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import torch
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from executorch.backends.arm.test import common
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from executorch.backends.arm.test.tester.arm_tester import ArmTester
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from executorch.exir.backend.compile_spec_schema import CompileSpec
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from parameterized import parameterized
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test_data_suite = [
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# (test_name, input, other,) See torch.eq() for info
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(
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"op_eq_rank1_ones",
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torch.ones(5),
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torch.ones(5),
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),
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(
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"op_eq_rank2_rand",
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torch.rand(4, 5),
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torch.rand(1, 5),
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),
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(
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"op_eq_rank3_randn",
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torch.randn(10, 5, 2),
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torch.randn(10, 5, 2),
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),
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(
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"op_eq_rank4_randn",
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torch.randn(3, 2, 2, 2),
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torch.randn(3, 2, 2, 2),
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),
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]
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class TestEqual(unittest.TestCase):
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class Equal(torch.nn.Module):
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def forward(
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self,
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input_: torch.Tensor,
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other_: torch.Tensor,
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):
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return input_ == other_
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def _test_eq_tosa_MI_pipeline(
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self,
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compile_spec: list[CompileSpec],
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module: torch.nn.Module,
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test_data: tuple[torch.Tensor, torch.Tensor],
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):
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(
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ArmTester(
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module,
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example_inputs=test_data,
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compile_spec=compile_spec,
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)
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.export()
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.check_count({"torch.ops.aten.eq.Tensor": 1})
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.to_edge()
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.partition()
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.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
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.to_executorch()
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.run_method_and_compare_outputs(inputs=test_data)
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)
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def _test_eq_tosa_BI_pipeline(
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self,
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compile_spec: list[CompileSpec],
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module: torch.nn.Module,
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test_data: tuple[torch.Tensor, torch.Tensor],
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):
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(
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ArmTester(
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module,
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example_inputs=test_data,
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compile_spec=compile_spec,
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)
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.quantize()
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.export()
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.check_count({"torch.ops.aten.eq.Tensor": 1})
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.check(["torch.ops.quantized_decomposed"])
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.to_edge()
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.partition()
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.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
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.to_executorch()
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.run_method_and_compare_outputs(inputs=test_data)
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)
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@parameterized.expand(test_data_suite)
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def test_eq_tosa_MI(
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self,
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test_name: str,
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input_: torch.Tensor,
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other_: torch.Tensor,
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):
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test_data = (input_, other_)
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self._test_eq_tosa_MI_pipeline(
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common.get_tosa_compile_spec("TOSA-0.80+MI"), self.Equal(), test_data
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)
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@parameterized.expand(test_data_suite)
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def test_eq_tosa_BI(
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self,
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test_name: str,
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input_: torch.Tensor,
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other_: torch.Tensor,
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):
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test_data = (input_, other_)
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self._test_eq_tosa_BI_pipeline(
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common.get_tosa_compile_spec("TOSA-0.80+BI"), self.Equal(), test_data
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)
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@parameterized.expand(test_data_suite)
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@unittest.skip
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def test_eq_u55_BI(
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self,
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test_name: str,
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input_: torch.Tensor,
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other_: torch.Tensor,
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):
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test_data = (input_, other_)
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self._test_eq_tosa_BI_pipeline(
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common.get_u55_compile_spec(permute_memory_to_nhwc=True),
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self.Equal(),
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test_data,
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)
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@parameterized.expand(test_data_suite)
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@unittest.skip
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def test_eq_u85_BI(
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from executorch.backends.arm.test.tester.test_pipeline import (
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EthosU85PipelineBI,
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OpNotSupportedPipeline,
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TosaPipelineBI,
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TosaPipelineMI,
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)
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aten_op = "torch.ops.aten.eq.Tensor"
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exir_op = "executorch_exir_dialects_edge__ops_aten_eq_Tensor"
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input_t = Tuple[torch.Tensor]
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class Equal(torch.nn.Module):
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def __init__(self, input, other):
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super().__init__()
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self.input_ = input
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self.other_ = other
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def forward(
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self,
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test_name: str,
13733
input_: torch.Tensor,
13834
other_: torch.Tensor,
13935
):
140-
test_data = (input_, other_)
141-
self._test_eq_tosa_BI_pipeline(
142-
common.get_u85_compile_spec(permute_memory_to_nhwc=True),
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self.Equal(),
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test_data,
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)
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return input_ == other_
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38+
def get_inputs(self):
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return (self.input_, self.other_)
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op_eq_rank1_ones = Equal(
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torch.ones(5),
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torch.ones(5),
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)
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op_eq_rank2_rand = Equal(
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torch.rand(4, 5),
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torch.rand(1, 5),
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)
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op_eq_rank3_randn = Equal(
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torch.randn(10, 5, 2),
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torch.randn(10, 5, 2),
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)
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op_eq_rank4_randn = Equal(
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torch.randn(3, 2, 2, 2),
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torch.randn(3, 2, 2, 2),
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)
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59+
test_data_common = {
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"eq_rank1_ones": op_eq_rank1_ones,
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"eq_rank2_rand": op_eq_rank2_rand,
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"eq_rank3_randn": op_eq_rank3_randn,
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"eq_rank4_randn": op_eq_rank4_randn,
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}
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67+
@common.parametrize("test_module", test_data_common)
68+
def test_eq_tosa_MI(test_module):
69+
pipeline = TosaPipelineMI[input_t](
70+
test_module, test_module.get_inputs(), aten_op, exir_op
71+
)
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pipeline.run()
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75+
@common.parametrize("test_module", test_data_common)
76+
def test_eq_tosa_BI(test_module):
77+
pipeline = TosaPipelineBI[input_t](
78+
test_module, test_module.get_inputs(), aten_op, exir_op
79+
)
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pipeline.run()
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83+
@common.parametrize("test_module", test_data_common)
84+
def test_eq_u55_BI(test_module):
85+
# EQUAL is not supported on U55.
86+
pipeline = OpNotSupportedPipeline[input_t](
87+
test_module,
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test_module.get_inputs(),
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"TOSA-0.80+BI+u55",
90+
{exir_op: 1},
91+
)
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pipeline.run()
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95+
@common.parametrize("test_module", test_data_common)
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def test_eq_u85_BI(test_module):
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pipeline = EthosU85PipelineBI[input_t](
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test_module,
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test_module.get_inputs(),
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aten_op,
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exir_op,
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run_on_fvp=False,
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use_to_edge_transform_and_lower=True,
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)
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pipeline.run()
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@common.parametrize("test_module", test_data_common)
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@pytest.mark.skip(reason="The same as test_eq_u55_BI")
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def test_eq_u55_BI_on_fvp(test_module):
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# EQUAL is not supported on U55.
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pipeline = OpNotSupportedPipeline[input_t](
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test_module,
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test_module.get_inputs(),
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"TOSA-0.80+BI+u55",
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{exir_op: 1},
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)
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pipeline.run()
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@common.parametrize(
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"test_module",
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test_data_common,
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xfails={"eq_rank4_randn": "4D fails because boolean Tensors can't be subtracted"},
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)
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@common.SkipIfNoCorstone320
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def test_eq_u85_BI_on_fvp(test_module):
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pipeline = EthosU85PipelineBI[input_t](
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test_module,
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test_module.get_inputs(),
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aten_op,
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exir_op,
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run_on_fvp=True,
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use_to_edge_transform_and_lower=True,
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)
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pipeline.run()

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