# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import unittest import numpy as np from op_test import OpTest import paddle import paddle.fluid as fluid from paddle.fluid.framework import _test_eager_guard class TestTrilIndicesOp(OpTest): def setUp(self): self.op_type = "tril_indices" self.inputs = {} self.init_config() self.outputs = {'out': self.target} def test_check_output(self): paddle.enable_static() self.check_output() def init_config(self): self.attrs = {'rows': 4, 'cols': 4, 'offset': -1} self.target = np.tril_indices(self.attrs['rows'], self.attrs['offset'], self.attrs['cols']) self.target = np.array(self.target) class TestTrilIndicesOpCase1(TestTrilIndicesOp): def init_config(self): self.attrs = {'rows': 0, 'cols': 0, 'offset': 0} self.target = np.tril_indices(0, 0, 0) self.target = np.array(self.target) class TestTrilIndicesOpCase2(TestTrilIndicesOp): def init_config(self): self.attrs = {'rows': 4, 'cols': 4, 'offset': 2} self.target = np.tril_indices(self.attrs['rows'], self.attrs['offset'], self.attrs['cols']) self.target = np.array(self.target) class TestTrilIndicesAPICaseStatic(unittest.TestCase): def test_static(self): places = [ paddle.CPUPlace(), paddle.fluid.CUDAPlace(0) ] if fluid.core.is_compiled_with_cuda() else [paddle.CPUPlace()] paddle.enable_static() for place in places: with paddle.static.program_guard(paddle.static.Program(), paddle.static.Program()): data1 = paddle.tril_indices(4, 4, -1) exe1 = paddle.static.Executor(place) result1, = exe1.run(feed={}, fetch_list=[data1]) expected_result1 = np.tril_indices(4, -1, 4) np.testing.assert_allclose(result1, expected_result1, rtol=1e-05) class TestTrilIndicesAPICaseDygraph(unittest.TestCase): def test_dygraph(self): places = [ paddle.CPUPlace(), paddle.fluid.CUDAPlace(0) ] if fluid.core.is_compiled_with_cuda() else [paddle.CPUPlace()] for place in places: with fluid.dygraph.base.guard(place=place): out1 = paddle.tril_indices(4, 4, 2) expected_result1 = np.tril_indices(4, 2, 4) self.assertEqual((out1.numpy() == expected_result1).all(), True) def test_dygraph_eager(self): with _test_eager_guard(): self.test_dygraph() class TestTrilIndicesAPICaseError(unittest.TestCase): def test_case_error(self): def test_num_rows_type_check(): out1 = paddle.tril_indices(1.0, 1, 2) self.assertRaises(TypeError, test_num_rows_type_check) def test_num_columns_type_check(): out2 = paddle.tril_indices(4, -1, 2) self.assertRaises(TypeError, test_num_columns_type_check) def test_num_offset_type_check(): out3 = paddle.tril_indices(4, 4, 2.0) self.assertRaises(TypeError, test_num_offset_type_check) class TestTrilIndicesAPICaseDefault(unittest.TestCase): def test_default_CPU(self): paddle.enable_static() with paddle.static.program_guard(paddle.static.Program(), paddle.static.Program()): data = paddle.tril_indices(4, None, 2) exe = paddle.static.Executor(paddle.CPUPlace()) result, = exe.run(feed={}, fetch_list=[data]) expected_result = np.tril_indices(4, 2) np.testing.assert_allclose(result, expected_result, rtol=1e-05) with fluid.dygraph.base.guard(paddle.CPUPlace()): out = paddle.tril_indices(4, None, 2) expected_result = np.tril_indices(4, 2) self.assertEqual((out.numpy() == expected_result).all(), True) if __name__ == "__main__": unittest.main()