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| 1 | +# Copyright 2024 Arm Limited and/or its affiliates. |
| 2 | +# All rights reserved. |
| 3 | +# |
| 4 | +# This source code is licensed under the BSD-style license found in the |
| 5 | +# LICENSE file in the root directory of this source tree. |
| 6 | + |
| 7 | +import unittest |
| 8 | + |
| 9 | +from typing import Tuple |
| 10 | + |
| 11 | +import torch |
| 12 | +from executorch.backends.arm.test import common |
| 13 | +from executorch.backends.arm.test.tester.arm_tester import ArmTester |
| 14 | +from executorch.exir.backend.compile_spec_schema import CompileSpec |
| 15 | +from parameterized import parameterized |
| 16 | + |
| 17 | + |
| 18 | +test_data_suite = [ |
| 19 | + # (test_name, test_data, dim) |
| 20 | + ("zeros", torch.zeros(10, 10, 10, 10), 0), |
| 21 | + ("zeros_neg_dim", torch.zeros(10, 10, 10, 10), -4), |
| 22 | + ("ones", torch.ones(10, 10), 1), |
| 23 | + ("rand_neg_dim", torch.rand(10, 10, 10), -1), |
| 24 | + ("rand", torch.rand(10, 10, 10, 10), 2), |
| 25 | + ("rand_neg_dim", torch.rand(10, 10, 2, 3), -2), |
| 26 | + ("randn", torch.randn(10, 10, 5, 10), 3), |
| 27 | + ("randn_neg_dim", torch.randn(1, 10, 10, 10), -3), |
| 28 | +] |
| 29 | + |
| 30 | + |
| 31 | +class TestLogSoftmax(unittest.TestCase): |
| 32 | + """Tests logsoftmax.""" |
| 33 | + |
| 34 | + class LogSoftmax(torch.nn.Module): |
| 35 | + def __init__(self, dim: int = -1): |
| 36 | + super().__init__() |
| 37 | + self.logsoftmax = torch.nn.LogSoftmax(dim=dim) |
| 38 | + |
| 39 | + def forward(self, x): |
| 40 | + return self.logsoftmax(x) |
| 41 | + |
| 42 | + def _test_logsoftmax_tosa_MI_pipeline( |
| 43 | + self, module: torch.nn.Module, test_data: Tuple[torch.tensor] |
| 44 | + ): |
| 45 | + ( |
| 46 | + ArmTester( |
| 47 | + module, |
| 48 | + example_inputs=test_data, |
| 49 | + compile_spec=common.get_tosa_compile_spec(), |
| 50 | + ) |
| 51 | + .export() |
| 52 | + .check(["torch.ops.aten.log_softmax.int"]) |
| 53 | + .check_not(["torch.ops.quantized_decomposed"]) |
| 54 | + .to_edge() |
| 55 | + .partition() |
| 56 | + .check_not(["executorch_exir_dialects_edge__ops_aten__logsoftmax_default"]) |
| 57 | + .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) |
| 58 | + .to_executorch() |
| 59 | + .run_method_and_compare_outputs(inputs=test_data) |
| 60 | + ) |
| 61 | + |
| 62 | + def _test_logsoftmax_tosa_BI_pipeline( |
| 63 | + self, module: torch.nn.Module, test_data: Tuple[torch.tensor] |
| 64 | + ): |
| 65 | + ( |
| 66 | + ArmTester( |
| 67 | + module, |
| 68 | + example_inputs=test_data, |
| 69 | + compile_spec=common.get_tosa_compile_spec(), |
| 70 | + ) |
| 71 | + .quantize() |
| 72 | + .export() |
| 73 | + .check_not(["torch.ops.aten.log_softmax.int"]) |
| 74 | + .check(["torch.ops.quantized_decomposed", "torch.ops.aten.mul.Tensor"]) |
| 75 | + .to_edge() |
| 76 | + .partition() |
| 77 | + .check_not(["executorch_exir_dialects_edge__ops_aten__log_softmax_default"]) |
| 78 | + .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) |
| 79 | + .to_executorch() |
| 80 | + .run_method_and_compare_outputs(inputs=test_data, qtol=1) |
| 81 | + ) |
| 82 | + |
| 83 | + def _test_logsoftmax_tosa_ethos_BI_pipeline( |
| 84 | + self, |
| 85 | + compile_spec: list[CompileSpec], |
| 86 | + module: torch.nn.Module, |
| 87 | + test_data: Tuple[torch.tensor], |
| 88 | + ): |
| 89 | + ( |
| 90 | + ArmTester( |
| 91 | + module, |
| 92 | + example_inputs=test_data, |
| 93 | + compile_spec=compile_spec, |
| 94 | + ) |
| 95 | + .quantize() |
| 96 | + .export() |
| 97 | + .check_not(["torch.ops.aten.log_softmax.int"]) |
| 98 | + .check(["torch.ops.quantized_decomposed", "torch.ops.aten.mul.Tensor"]) |
| 99 | + .to_edge() |
| 100 | + .partition() |
| 101 | + .check_not(["executorch_exir_dialects_edge__ops_aten__logsoftmax_default"]) |
| 102 | + .check_count({"torch.ops.higher_order.executorch_call_delegate": 1}) |
| 103 | + .to_executorch() |
| 104 | + ) |
| 105 | + |
| 106 | + def _test_logsoftmax_tosa_u55_BI_pipeline( |
| 107 | + self, module: torch.nn.Module, test_data: Tuple[torch.tensor] |
| 108 | + ): |
| 109 | + self._test_logsoftmax_tosa_ethos_BI_pipeline( |
| 110 | + common.get_u55_compile_spec(), module, test_data |
| 111 | + ) |
| 112 | + |
| 113 | + def _test_logsoftmax_tosa_u85_BI_pipeline( |
| 114 | + self, module: torch.nn.Module, test_data: Tuple[torch.tensor] |
| 115 | + ): |
| 116 | + self._test_logsoftmax_tosa_ethos_BI_pipeline( |
| 117 | + common.get_u85_compile_spec(), module, test_data |
| 118 | + ) |
| 119 | + |
| 120 | + @parameterized.expand(test_data_suite) |
| 121 | + def test_logsoftmax_tosa_MI( |
| 122 | + self, |
| 123 | + test_name: str, |
| 124 | + test_data: torch.Tensor, |
| 125 | + dim: int, |
| 126 | + ): |
| 127 | + self._test_logsoftmax_tosa_MI_pipeline(self.LogSoftmax(dim=dim), (test_data,)) |
| 128 | + |
| 129 | + @parameterized.expand(test_data_suite) |
| 130 | + def test_logsoftmax_tosa_BI( |
| 131 | + self, |
| 132 | + test_name: str, |
| 133 | + test_data: torch.Tensor, |
| 134 | + dim: int, |
| 135 | + ): |
| 136 | + self._test_logsoftmax_tosa_BI_pipeline(self.LogSoftmax(dim=dim), (test_data,)) |
| 137 | + |
| 138 | + @parameterized.expand(test_data_suite) |
| 139 | + def test_logsoftmax_tosa_u55_BI( |
| 140 | + self, |
| 141 | + test_name: str, |
| 142 | + test_data: torch.Tensor, |
| 143 | + dim: int, |
| 144 | + ): |
| 145 | + self._test_logsoftmax_tosa_u55_BI_pipeline( |
| 146 | + self.LogSoftmax(dim=dim), (test_data,) |
| 147 | + ) |
| 148 | + |
| 149 | + @parameterized.expand(test_data_suite) |
| 150 | + def test_logsoftmax_tosa_u85_BI( |
| 151 | + self, |
| 152 | + test_name: str, |
| 153 | + test_data: torch.Tensor, |
| 154 | + dim: int, |
| 155 | + ): |
| 156 | + self._test_logsoftmax_tosa_u55_BI_pipeline( |
| 157 | + self.LogSoftmax(dim=dim), (test_data,) |
| 158 | + ) |
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