| # 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. |
| |
| import unittest |
| |
| from typing import Tuple |
| |
| import torch |
| from executorch.backends.arm.test import common |
| from executorch.backends.arm.test.tester.arm_tester import ArmTester |
| from executorch.exir.backend.compile_spec_schema import CompileSpec |
| from parameterized import parameterized |
| |
| torch.manual_seed(1) |
| |
| |
| class TestBMM(unittest.TestCase): |
| """Tests Batch MatMul""" |
| |
| class BMM(torch.nn.Module): |
| test_parameters = [ |
| (torch.rand(5, 3, 5), torch.rand(5, 5, 2)), |
| (torch.rand(2, 1, 1), torch.rand(2, 1, 1)), |
| (torch.ones(1, 55, 3), torch.ones(1, 3, 44)), |
| (10000 * torch.randn(10, 1, 10), torch.randn(10, 10, 5)), |
| (-10 * torch.randn(2, 32, 64), 5 + 5 * torch.randn(2, 64, 32)), |
| ] |
| |
| def forward(self, x, y): |
| return torch.bmm(x, y) |
| |
| class MatMul(torch.nn.Module): |
| test_parameters = [(torch.rand(2, 3, 5), torch.rand(2, 5, 2))] |
| |
| def forward(self, x, y): |
| return torch.matmul(x, y) |
| |
| class BMMSingleInput(torch.nn.Module): |
| test_parameters = [ |
| (torch.rand(20, 3, 3),), |
| (torch.ones(2, 128, 128),), |
| (10000 * torch.randn(4, 25, 25),), |
| (5 + 5 * torch.randn(3, 64, 64),), |
| ] |
| |
| def forward(self, x): |
| return torch.bmm(x, x) |
| |
| def _test_bmm_tosa_MI_pipeline( |
| self, module: torch.nn.Module, test_data: Tuple[torch.Tensor, ...] |
| ): |
| ( |
| ArmTester( |
| module, |
| example_inputs=test_data, |
| compile_spec=common.get_tosa_compile_spec("TOSA-0.80.0+MI"), |
| ) |
| .export() |
| .check_not(["torch.ops.quantized_decomposed"]) |
| .to_edge() |
| .check_count({"executorch_exir_dialects_edge__ops_aten_bmm_default": 1}) |
| .partition() |
| .check_not(["executorch_exir_dialects_edge__ops_aten_bmm_default"]) |
| .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) |
| .to_executorch() |
| .run_method_and_compare_outputs(inputs=test_data) |
| ) |
| |
| def _test_bmm_tosa_BI_pipeline( |
| self, module: torch.nn.Module, test_data: Tuple[torch.Tensor, ...] |
| ): |
| ( |
| ArmTester( |
| module, |
| example_inputs=test_data, |
| compile_spec=common.get_tosa_compile_spec("TOSA-0.80.0+BI"), |
| ) |
| .quantize() |
| .export() |
| .check(["torch.ops.quantized_decomposed"]) |
| .to_edge() |
| .check_count({"executorch_exir_dialects_edge__ops_aten_bmm_default": 1}) |
| .partition() |
| .check_not(["executorch_exir_dialects_edge__ops_aten_bmm_default"]) |
| .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) |
| .to_executorch() |
| .run_method_and_compare_outputs(inputs=test_data) |
| ) |
| |
| def _test_bmm_ethosu_BI_pipeline( |
| self, |
| module: torch.nn.Module, |
| compile_spec: CompileSpec, |
| test_data: Tuple[torch.Tensor, ...], |
| ): |
| ( |
| ArmTester( |
| module, |
| example_inputs=test_data, |
| compile_spec=compile_spec, |
| ) |
| .quantize() |
| .export() |
| .check_count({"torch.ops.aten.bmm.default": 1}) |
| .check(["torch.ops.quantized_decomposed"]) |
| .to_edge() |
| .partition() |
| .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) |
| .to_executorch() |
| ) |
| |
| @parameterized.expand(BMM.test_parameters) |
| def test_bmm_tosa_MI(self, operand1: torch.Tensor, operand2: torch.Tensor): |
| test_data = (operand1, operand2) |
| self._test_bmm_tosa_MI_pipeline(self.BMM(), test_data) |
| |
| @parameterized.expand(BMMSingleInput.test_parameters) |
| def test_bmm_single_input_tosa_MI(self, operand1: torch.Tensor): |
| test_data = (operand1,) |
| self._test_bmm_tosa_MI_pipeline(self.BMMSingleInput(), test_data) |
| |
| @parameterized.expand(MatMul.test_parameters) |
| def test_matmul_tosa_MI(self, operand1: torch.Tensor, operand2: torch.Tensor): |
| test_data = (operand1, operand2) |
| self._test_bmm_tosa_MI_pipeline(self.MatMul(), test_data) |
| |
| @parameterized.expand(MatMul.test_parameters) |
| def test_matmul_tosa_BI(self, operand1: torch.Tensor, operand2: torch.Tensor): |
| test_data = (operand1, operand2) |
| self._test_bmm_tosa_BI_pipeline(self.MatMul(), test_data) |
| |
| @parameterized.expand(BMM.test_parameters) |
| def test_bmm_tosa_BI(self, operand1: torch.Tensor, operand2: torch.Tensor): |
| test_data = (operand1, operand2) |
| self._test_bmm_tosa_BI_pipeline(self.BMM(), test_data) |
| |
| @parameterized.expand(BMMSingleInput.test_parameters) |
| def test_bmm_single_input_tosa_BI(self, operand1: torch.Tensor): |
| test_data = (operand1,) |
| self._test_bmm_tosa_BI_pipeline(self.BMMSingleInput(), test_data) |
| |
| @parameterized.expand(BMM.test_parameters) |
| def test_bmm_u55_BI(self, operand1: torch.Tensor, operand2: torch.Tensor): |
| test_data = (operand1, operand2) |
| self._test_bmm_tosa_BI_pipeline(self.BMM(), test_data) |
| |
| # Expected to fail with error: Warning, unsupported fusing of TOSA Rescale previous operator is of type: Memcpy |
| @parameterized.expand(BMMSingleInput.test_parameters) |
| @unittest.expectedFailure |
| def test_bmm_single_input_u55_BI(self, operand1: torch.Tensor): |
| test_data = (operand1,) |
| self._test_bmm_ethosu_BI_pipeline( |
| self.BMMSingleInput(), common.get_u55_compile_spec(), test_data |
| ) |
| |
| @parameterized.expand(BMMSingleInput.test_parameters) |
| def test_bmm_single_input_u85_BI(self, operand1: torch.Tensor): |
| test_data = (operand1,) |
| self._test_bmm_ethosu_BI_pipeline( |
| self.BMMSingleInput(), common.get_u85_compile_spec(), test_data |
| ) |