blob: 20c57ba749cd8adcc1ead7d798fa9fb262c5d049 [file]
# Copyright 2024 Arm Limited and/or its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
#
# Tests the repeat op which copies the data of the input tensor (possibly with new data format)
#
import unittest
from typing import Sequence, Tuple
import torch
from executorch.backends.arm.quantizer.arm_quantizer import (
ArmQuantizer,
get_symmetric_quantization_config,
)
from executorch.backends.arm.test import common
from executorch.backends.arm.test.tester.arm_tester import ArmTester
from executorch.backends.xnnpack.test.tester.tester import Quantize
from executorch.exir.backend.backend_details import CompileSpec
from parameterized import parameterized
class TestSimpleRepeat(unittest.TestCase):
"""Tests Tensor.repeat for different ranks and dimensions."""
class Repeat(torch.nn.Module):
# (input tensor, multiples)
test_parameters = [
(torch.randn(3), (2,)),
(torch.randn(3, 4), (2, 1)),
(torch.randn(1, 1, 2, 2), (1, 2, 3, 4)),
(torch.randn(3), (2, 2)),
(torch.randn(3), (1, 2, 3)),
(torch.randn((3, 3)), (2, 2, 2)),
]
def forward(self, x: torch.Tensor, multiples: Sequence):
return x.repeat(multiples)
def _test_repeat_tosa_MI_pipeline(self, module: torch.nn.Module, test_data: Tuple):
(
ArmTester(
module,
example_inputs=test_data,
compile_spec=common.get_tosa_compile_spec("TOSA-0.80.0+MI"),
)
.export()
.check_count({"torch.ops.aten.repeat.default": 1})
.to_edge()
.partition()
.check_not(["torch.ops.aten.repeat.default"])
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.to_executorch()
.run_method_and_compare_outputs(inputs=test_data)
)
def _test_repeat_tosa_BI_pipeline(self, module: torch.nn.Module, test_data: Tuple):
quantizer = ArmQuantizer().set_io(get_symmetric_quantization_config())
(
ArmTester(
module,
example_inputs=test_data,
compile_spec=common.get_tosa_compile_spec("TOSA-0.80.0+BI"),
)
.quantize(Quantize(quantizer, get_symmetric_quantization_config()))
.export()
.check_count({"torch.ops.aten.repeat.default": 1})
.to_edge()
.partition()
.check_not(["torch.ops.aten.repeat.default"])
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.to_executorch()
.run_method_and_compare_outputs(inputs=test_data, qtol=1)
)
def _test_repeat_ethosu_pipeline(
self, compile_spec: CompileSpec, module: torch.nn.Module, test_data: Tuple
):
quantizer = ArmQuantizer().set_io(get_symmetric_quantization_config())
(
ArmTester(
module,
example_inputs=test_data,
compile_spec=compile_spec,
)
.quantize(Quantize(quantizer, get_symmetric_quantization_config()))
.export()
.check_count({"torch.ops.aten.repeat.default": 1})
.to_edge()
.partition()
.check_not(["torch.ops.aten.repeat.default"])
.check_count({"torch.ops.higher_order.executorch_call_delegate": 1})
.to_executorch()
)
@parameterized.expand(Repeat.test_parameters)
def test_repeat_tosa_MI(self, test_input, multiples):
self._test_repeat_tosa_MI_pipeline(self.Repeat(), (test_input, multiples))
@parameterized.expand(Repeat.test_parameters)
def test_repeat_tosa_BI(self, test_input, multiples):
self._test_repeat_tosa_BI_pipeline(self.Repeat(), (test_input, multiples))
@parameterized.expand(Repeat.test_parameters)
def test_repeat_u55_BI(self, test_input, multiples):
self._test_repeat_ethosu_pipeline(
common.get_u55_compile_spec(), self.Repeat(), (test_input, multiples)
)
@parameterized.expand(Repeat.test_parameters)
def test_repeat_u85_BI(self, test_input, multiples):
self._test_repeat_ethosu_pipeline(
common.get_u85_compile_spec(), self.Repeat(), (test_input, multiples)
)