# Copyright (c) Meta Platforms, Inc. and affiliates. # 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 test_data_suite = [ # (test_name, test_data) ("zeros", torch.zeros(10, 10, 10, 10)), ("ones", torch.ones(10, 10, 10)), ("rand", torch.rand(10, 10) - 0.5), ("randn_pos", torch.randn(10) + 10), ("randn_neg", torch.randn(10) - 10), ("ramp", torch.arange(-16, 16, 0.2)), ] class TestTanh(unittest.TestCase): class Tanh(torch.nn.Module): def __init__(self): super().__init__() self.tanh = torch.nn.Tanh() def forward(self, x): return self.tanh(x) def _test_tanh_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(["torch.ops.aten.tanh.default"]) .check_not(["torch.ops.quantized_decomposed"]) .to_edge() .partition() .check_not(["executorch_exir_dialects_edge__ops_aten_tanh_default"]) .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) .to_executorch() .run_method_and_compare_outputs(inputs=test_data) ) def _test_tanh_tosa_BI_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+BI"), ) .quantize() .export() .check(["torch.ops.aten.tanh.default"]) .check(["torch.ops.quantized_decomposed"]) .to_edge() .partition() .check_not(["executorch_exir_dialects_edge__ops_aten_tanh_default"]) .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) .to_executorch() .run_method_and_compare_outputs(inputs=test_data) ) def _test_tanh_tosa_ethos_BI_pipeline( self, compile_spec: list[CompileSpec], module: torch.nn.Module, test_data: Tuple[torch.tensor], ): ( ArmTester( module, example_inputs=test_data, compile_spec=compile_spec, ) .quantize() .export() .check_count({"torch.ops.aten.tanh.default": 1}) .check(["torch.ops.quantized_decomposed"]) .to_edge() .partition() .check_not(["executorch_exir_dialects_edge__ops_aten_tanh_default"]) .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) .to_executorch() ) def _test_tanh_tosa_u55_BI_pipeline( self, module: torch.nn.Module, test_data: Tuple[torch.tensor] ): self._test_tanh_tosa_ethos_BI_pipeline( common.get_u55_compile_spec(), module, test_data ) def _test_tanh_tosa_u85_BI_pipeline( self, module: torch.nn.Module, test_data: Tuple[torch.tensor] ): self._test_tanh_tosa_ethos_BI_pipeline( common.get_u85_compile_spec(), module, test_data ) @parameterized.expand(test_data_suite) def test_tanh_tosa_MI( self, test_name: str, test_data: torch.Tensor, ): self._test_tanh_tosa_MI_pipeline(self.Tanh(), (test_data,)) @parameterized.expand(test_data_suite) def test_tanh_tosa_BI(self, test_name: str, test_data: torch.Tensor): self._test_tanh_tosa_BI_pipeline(self.Tanh(), (test_data,)) @parameterized.expand(test_data_suite) def test_tanh_tosa_u55_BI(self, test_name: str, test_data: torch.Tensor): self._test_tanh_tosa_u55_BI_pipeline(self.Tanh(), (test_data,)) @parameterized.expand(test_data_suite) def test_tanh_tosa_u85_BI(self, test_name: str, test_data: torch.Tensor): self._test_tanh_tosa_u85_BI_pipeline(self.Tanh(), (test_data,))