# 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 expand 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 TestSimpleExpand(unittest.TestCase): """Tests the Tensor.expand which should be converted to a repeat op by a pass.""" class Expand(torch.nn.Module): # (input tensor, multiples) test_parameters = [ (torch.ones(1), (2,)), (torch.ones(1, 4), (1, -1)), (torch.ones(1, 1, 2, 2), (4, 3, -1, 2)), (torch.ones(1), (2, 2, 4)), (torch.ones(3, 2, 4, 1), (-1, -1, -1, 3)), ] def forward(self, x: torch.Tensor, multiples: Sequence): return x.expand(multiples) def _test_expand_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.expand.default": 1}) .to_edge() .partition() .check_not(["torch.ops.aten.expand.default"]) .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) .to_executorch() .run_method_and_compare_outputs(inputs=test_data) ) def _test_expand_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.expand.default": 1}) .to_edge() .partition() .check_not(["torch.ops.aten.expand.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_expand_ethosu_BI_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.expand.default": 1}) .to_edge() .partition() .check_not(["torch.ops.aten.expand.default"]) .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) .to_executorch() ) @parameterized.expand(Expand.test_parameters) def test_expand_tosa_MI(self, test_input, multiples): self._test_expand_tosa_MI_pipeline(self.Expand(), (test_input, multiples)) @parameterized.expand(Expand.test_parameters) def test_expand_tosa_BI(self, test_input, multiples): self._test_expand_tosa_BI_pipeline(self.Expand(), (test_input, multiples)) @parameterized.expand(Expand.test_parameters) def test_expand_u55_BI(self, test_input, multiples): self._test_expand_ethosu_BI_pipeline( common.get_u55_compile_spec(), self.Expand(), (test_input, multiples) ) @parameterized.expand(Expand.test_parameters) def test_expand_u85_BI(self, test_input, multiples): self._test_expand_ethosu_BI_pipeline( common.get_u85_compile_spec(), self.Expand(), (test_input, multiples) )