# Copyright (c) 2023 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 import paddle from paddle.fluid.variable_index import _setitem_static class TestSetitemInDygraph(unittest.TestCase): def setUp(self): paddle.disable_static() def test_combined_index_1(self): np_data = np.zeros((3, 4, 5, 6), dtype='float32') x = paddle.to_tensor(np_data) np_data[[0, 1], :, [1, 2]] = 10.0 x[[0, 1], :, [1, 2]] = 10.0 np.testing.assert_allclose(x.numpy(), np_data) def test_combined_index_2(self): np_data = np.ones((3, 4, 5, 6), dtype='float32') x = paddle.to_tensor(np_data) np_data[:, 1, [1, 2], 0] = 10.0 x[:, 1, [1, 2], 0] = 10.0 np.testing.assert_allclose(x.numpy(), np_data) def test_combined_index_3(self): np_data = np.ones((3, 4, 5, 6), dtype='int32') x = paddle.to_tensor(np_data) np_data[:, [True, False, True, False], [1, 4]] = 10 x[:, [True, False, True, False], [1, 4]] = 10 np.testing.assert_allclose(x.numpy(), np_data) class TestSetitemInStatic(unittest.TestCase): def setUp(self): paddle.enable_static() self.exe = paddle.static.Executor() def test_combined_index_1(self): # int tensor + slice (without decreasing axes) np_data = np.zeros((3, 4, 5, 6), dtype='float32') np_data[[0, 1], :, [1, 2]] = 10.0 with paddle.static.program_guard( paddle.static.Program(), paddle.static.Program() ): x = paddle.zeros((3, 4, 5, 6), dtype='float32') y = _setitem_static( x, ([0, 1], slice(None, None, None), [1, 2]), 10.0 ) res = self.exe.run(fetch_list=[y.name]) np.testing.assert_allclose(res[0], np_data) def test_combined_index_2(self): # int tensor + slice (with decreasing axes) np_data = np.ones((3, 4, 5, 6), dtype='float32') np_data[:, 1, [1, 2], 0] = 10.0 with paddle.static.program_guard( paddle.static.Program(), paddle.static.Program() ): x = paddle.ones((3, 4, 5, 6), dtype='float32') y = _setitem_static( x, (slice(None, None, None), 1, [1, 2], 0), 10.0 ) res = self.exe.run(fetch_list=[y.name]) np.testing.assert_allclose(res[0], np_data) def test_combined_index_3(self): # int tensor + bool tensor + slice (without decreasing axes) np_data = np.ones((3, 4, 5, 6), dtype='int32') np_data[:, [True, False, True, False], [1, 4]] = 10 with paddle.static.program_guard( paddle.static.Program(), paddle.static.Program() ): x = paddle.ones((3, 4, 5, 6), dtype='int32') y = _setitem_static( x, (slice(None, None, None), [True, False, True, False], [1, 4]), 10, ) res = self.exe.run(fetch_list=[y.name]) np.testing.assert_allclose(res[0], np_data) def test_combined_index_4(self): # int tensor (with ranks > 1) + bool tensor + slice (with decreasing axes) np_data = np.ones((3, 4, 5, 6), dtype='int32') np_data[[0, 0], [True, False, True, False], [[0, 2], [1, 4]], 4] = 16 with paddle.static.program_guard( paddle.static.Program(), paddle.static.Program() ): x = paddle.ones((3, 4, 5, 6), dtype='int32') y = _setitem_static( x, ([0, 0], [True, False, True, False], [[0, 2], [1, 4]], 4), 16, ) res = self.exe.run(fetch_list=[y.name]) np.testing.assert_allclose(res[0], np_data) def test_combined_index_5(self): # int tensor + slice + Ellipsis np_data = np.ones((3, 4, 5, 6), dtype='int32') np_data[..., [1, 4, 3], ::2] = 5 with paddle.static.program_guard( paddle.static.Program(), paddle.static.Program() ): x = paddle.ones((3, 4, 5, 6), dtype='int32') y = _setitem_static( x, (..., [1, 4, 3], slice(None, None, 2)), 5, ) res = self.exe.run(fetch_list=[y.name]) np.testing.assert_allclose(res[0], np_data)