# Copyright (c) 2021 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. from __future__ import print_function import unittest import numpy as np import paddle import paddle.fluid as fluid import paddle.fluid.core as core class LinalgLstsqTestCase(unittest.TestCase): def setUp(self): self.devices = ["cpu"] self.init_config() if core.is_compiled_with_cuda() and self.driver == "gels": self.devices.append("gpu:0") self.generate_input() self.generate_output() np.random.seed(2022) def init_config(self): self.dtype = 'float64' self.rcond = 1e-15 self.driver = "gelsd" self._input_shape_1 = (5, 4) self._input_shape_2 = (5, 3) def generate_input(self): self._input_data_1 = np.random.random(self._input_shape_1).astype( self.dtype) self._input_data_2 = np.random.random(self._input_shape_2).astype( self.dtype) def generate_output(self): if len(self._input_shape_1) == 2: out = np.linalg.lstsq(self._input_data_1, self._input_data_2, rcond=self.rcond) self._output_solution = out[0] self._output_residuals = out[1] self._output_rank = out[2] self._output_sg_values = out[3] elif len(self._input_shape_1) == 3: self._output_solution = [] self._output_residuals = [] self._output_rank = [] self._output_sg_values = [] for i in range(self._input_shape_1[0]): out = np.linalg.lstsq(self._input_data_1[i], self._input_data_2[i], rcond=self.rcond) self._output_solution.append(out[0]) self._output_residuals.append(out[1]) self._output_rank.append(out[2]) self._output_sg_values.append(out[3]) def test_eager_dygraph(self): paddle.disable_static() paddle.fluid.framework._disable_legacy_dygraph() for dev in self.devices: paddle.set_device(dev) place = paddle.CPUPlace() if dev == "cpu" else paddle.CUDAPlace(0) x = paddle.to_tensor(self._input_data_1, place=place, dtype=self.dtype) y = paddle.to_tensor(self._input_data_2, place=place, dtype=self.dtype) results = paddle.linalg.lstsq(x, y, rcond=self.rcond, driver=self.driver) self._result_solution = results[0].numpy() self._result_residuals = results[1].numpy() self._result_rank = results[2].numpy() self._result_sg_values = results[3].numpy() self.assert_np_close() def test_legacy_dygraph(self): paddle.disable_static() paddle.fluid.framework._enable_legacy_dygraph() for dev in self.devices: paddle.set_device(dev) place = paddle.CPUPlace() if dev == "cpu" else paddle.CUDAPlace(0) x = paddle.to_tensor(self._input_data_1, place=place, dtype=self.dtype) y = paddle.to_tensor(self._input_data_2, place=place, dtype=self.dtype) results = paddle.linalg.lstsq(x, y, rcond=self.rcond, driver=self.driver) self._result_solution = results[0].numpy() self._result_residuals = results[1].numpy() self._result_rank = results[2].numpy() self._result_sg_values = results[3].numpy() self.assert_np_close() def test_static(self): paddle.enable_static() for dev in self.devices: paddle.set_device(dev) place = fluid.CPUPlace() if dev == "cpu" else fluid.CUDAPlace(0) with fluid.program_guard(fluid.Program(), fluid.Program()): x = paddle.fluid.data(name="x", shape=self._input_shape_1, dtype=self._input_data_1.dtype) y = paddle.fluid.data(name="y", shape=self._input_shape_2, dtype=self._input_data_2.dtype) results = paddle.linalg.lstsq(x, y, rcond=self.rcond, driver=self.driver) exe = fluid.Executor(place) fetches = exe.run(fluid.default_main_program(), feed={ "x": self._input_data_1, "y": self._input_data_2 }, fetch_list=[results]) self._result_solution = fetches[0] self._result_residuals = fetches[1] self._result_rank = fetches[2] self._result_sg_values = fetches[3] self.assert_np_close() def assert_np_close(self): if len(self._input_shape_1) == 2: np.testing.assert_allclose(self._result_solution, self._output_solution, rtol=1e-3) if self._input_shape_1[-2] > self._input_shape_1[ -1] and self._output_rank == self._input_shape_1[-1]: np.testing.assert_allclose(self._result_residuals, self._output_residuals, rtol=1e-5) if self.driver in ("gelsy", "gelsd", "gelss"): np.testing.assert_allclose(self._result_rank, self._output_rank, rtol=1e-5) if self.driver in ("gelsd", "gelss"): np.testing.assert_allclose(self._result_sg_values, self._output_sg_values, rtol=1e-5) else: for i in range(len(self._output_solution)): np.testing.assert_allclose(self._result_solution[i], self._output_solution[i], rtol=1e-3) if self._input_shape_1[-2] > self._input_shape_1[ -1] and self._output_rank[i] == self._input_shape_1[-1]: np.testing.assert_allclose(self._result_residuals[i], self._output_residuals[i], rtol=1e-5) if self.driver in ("gelsy", "gelsd", "gelss"): np.testing.assert_allclose(self._result_rank[i], self._output_rank[i], rtol=1e-5) if self.driver in ("gelsd", "gelss"): np.testing.assert_allclose(self._result_sg_values[i], self._output_sg_values[i], rtol=1e-5) class LinalgLstsqTestCase1(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float32' self.rcond = 1e-15 self.driver = "gels" self._input_shape_1 = (9, 9) self._input_shape_2 = (9, 5) class LinalgLstsqTestCase2(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float64' self.rcond = 1e-15 self.driver = "gels" self._input_shape_1 = (5, 10) self._input_shape_2 = (5, 8) class LinalgLstsqTestCase3(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float64' self.rcond = 1e-15 self.driver = "gels" self._input_shape_1 = (10, 7, 3) self._input_shape_2 = (10, 7, 6) class LinalgLstsqTestCaseRcond(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float64' self.rcond = 1e-7 self.driver = "gelsd" self._input_shape_1 = (3, 2) self._input_shape_2 = (3, 3) class LinalgLstsqTestCaseGelsFloat32(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float32' self.rcond = None self.driver = "gels" self._input_shape_1 = (10, 5) self._input_shape_2 = (10, 8) class LinalgLstsqTestCaseGelsFloat64(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float32' self.rcond = None self.driver = "gels" self._input_shape_1 = (3, 2, 8) self._input_shape_2 = (3, 2, 15) class LinalgLstsqTestCaseGelssFloat64(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float64' self.rcond = None self.driver = "gelss" self._input_shape_1 = (5, 5) self._input_shape_2 = (5, 1) class LinalgLstsqTestCaseGelsyFloat32(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float32' self.rcond = 1e-15 self.driver = "gelsy" self._input_shape_1 = (8, 2) self._input_shape_2 = (8, 10) class LinalgLstsqTestCaseBatch1(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float32' self.rcond = 1e-15 self.driver = "gelss" self._input_shape_1 = (2, 3, 10) self._input_shape_2 = (2, 3, 4) class LinalgLstsqTestCaseBatch2(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float64' self.rcond = 1e-15 self.driver = "gels" self._input_shape_1 = (10, 8, 6) self._input_shape_2 = (10, 8, 10) class LinalgLstsqTestCaseLarge1(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float64' self.rcond = 1e-15 self.driver = "gelsd" self._input_shape_1 = (200, 100) self._input_shape_2 = (200, 50) class LinalgLstsqTestCaseLarge2(LinalgLstsqTestCase): def init_config(self): self.dtype = 'float64' self.rcond = 1e-15 self.driver = "gelss" self._input_shape_1 = (50, 600) self._input_shape_2 = (50, 300) if __name__ == '__main__': unittest.main()