# Copyright (c) 2018 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 class TestLodResetOpByAttr(OpTest): def setUp(self): self.op_type = "lod_reset" x = np.random.random((10, 20)).astype("float32") lod = [[3, 2, 5]] # target_offset_lod and target_lod are the same lod info represented # in offset-based format and length-based format, respectively. target_offset_lod = [0, 7, 10] target_lod = [7, 3] self.inputs = {'X': (x, lod)} # The `target_lod` attribute is still based on offset self.attrs = {'target_lod': target_offset_lod} self.outputs = {'Out': (x, [target_lod])} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out") class TestLodResetOpByInput(OpTest): def setUp(self): self.op_type = "lod_reset" x = np.random.random((10, 20)).astype("float32") lod = [[3, 2, 5]] # target_offset_lod and target_lod are the same lod info represented # in offset-based format and length-based format, respectively. target_offset_lod = [0, 4, 7, 10] target_lod = [4, 3, 3] self.inputs = { 'X': (x, lod), 'Y': np.array([target_offset_lod]).astype('int32') } self.outputs = {'Out': (x, [target_lod])} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out", no_grad_set=set("Y")) class TestLodResetOpBoth(OpTest): def setUp(self): self.op_type = "lod_reset" x = np.random.random((10, 20)).astype("float32") lod = [[3, 2, 5]] target_offset_lod_attr = [0, 7, 10] target_offset_lod_in = [0, 4, 7, 10] target_lod_in = [4, 3, 3] self.inputs = { 'X': (x, lod), 'Y': np.array(target_offset_lod_in).astype('int32') } self.attrs = {'target_lod': target_offset_lod_attr} self.outputs = {'Out': (x, [target_lod_in])} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out", no_grad_set=set("Y")) class TestLodResetOpYIsLoDTensor(OpTest): def setUp(self): self.op_type = "lod_reset" x = np.random.random((10, 20)).astype("float32") lod = [[3, 2, 5]] y = np.random.random((10, 10)).astype("float32") target_lod = [[4, 3, 3]] self.inputs = {'X': (x, lod), 'Y': (y, target_lod)} self.outputs = {'Out': (x, target_lod)} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(["X"], "Out", no_grad_set=set("Y")) if __name__ == '__main__': unittest.main()